Author: "Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)" - Searchworks@Jio Institute Digital Library Search Results

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1,983 results on '"Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)"'

1. A non-inferiority randomized phase III trial of standard immunotherapy by checkpoint inhibitors vs. reduced dose intensity in responding patients with metastatic cancer: the MOIO protocol study

Author: Gravis, Gwenaelle, Marino, Patricia, Olive, Daniel, Penault-Llorca, Frederique, Delord, Jean-Pierre, Simon, Clotilde, Lamrani-Ghaouti, Assia, Sabatier, Renaud, Ciccolini, Joseph, Boher, Jean-Marie, Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale (SESSTIM - U1252 INSERM - Aix Marseille Univ - UMR 259 IRD), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut des sciences de la santé publique [Marseille] (ISSPAM), Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC), Imagerie Moléculaire et Stratégies Théranostiques (IMoST), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Clermont Auvergne (UCA), Centre Jean Perrin [Clermont-Ferrand] (UNICANCER/CJP), UNICANCER, Institut Universitaire du Cancer de Toulouse - Oncopole (IUCT Oncopole - UMR 1037), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Claudius Regaud, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), and Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes
Subjects: Cancer Research, Oncology, Genetics, [SDV.CAN]Life Sciences [q-bio]/Cancer
Abstract: Background Immunotherapy (IO) has become a standard of care for treating various types of metastatic cancers and has significantly improved clinical outcome. With the exception of metastatic melanoma in complete response for which treatment can be stopped at 6 months, these treatments are currently administered until either disease progression for some IO, 2 years for others, or unacceptable toxicity. However, a growing number of studies are reporting maintenance of response despite discontinuation of therapy. There is currently no evidence of a dose effect of IO in pharmacokinetic studies. Maintaining efficacy despite a reduction in treatment intensity by decreasing the frequency of administration in patients with highly selected metastatic cancer, is the hypothesis evaluated in the MOIO study. Method/design This non-inferiority, randomized phase III study aims to compare the standard regimen to a 3 monthly regimen of variousIO drugs in adult patients with metastatic cancer in partial (PR) or complete response (CR) after 6 months of standard IO dosing (except melanoma in CR). This is a French national study conducted in 36 centers. The main objective is to demonstrate that the efficacy of a three-monthly administration is not unacceptably less efficacious than a standard administration. Secondary objectives are cost-effectiveness, quality of life (QOL), anxiety, fear of relapse, response rate, overall survival and toxicity. After 6 months of standard IO, patients with partial or complete response will be randomized 1:1 between standard IO or a reduced intensity dose of IO, administered every 3 months. The randomization will be stratified on therapy line,, tumor type, IO type and response status. The primary endpoint is the hazard ratio of progression-free survival. With a planned study duration of 6 years, including 36 months enrolment time, 646 patients are planned to demonstrate with a statistical level of evidence of 5% that the reduced IO regimen is non-inferior to the standard IO regimen, with a relative non-inferiority margin set at 1.3. Discussion Should the hypothesis of non-inferiority with an IO reduced dose intensity be validated, alternate scheduling could preserve efficacy while being cost-effective and allowing a reduction of the toxicity, with an increase in patient’s QOL. Trial registration NCT05078047.
Published: 2023

2. Molecular profiling of non-small-cell lung cancer patients with or without brain metastases included in the randomized SAFIR02-LUNG trial and association with intracranial outcome

Author: Alice Mogenet, Fabrice Barlesi, Benjamin Besse, Stefan Michiels, Maryam Karimi, Alicia Tran-Dien, Nicolas Girard, Julien Mazieres, Clarisse Audigier-Valette, Myriam Locatelli-Sanchez, Maud Kamal, Pierre Gestraud, Abderaouf Hamza, Alexandra Jacquet, Marta Jimenez, Sabrina Yara, Laurent Greillier, François Bertucci, David Planchard, Jean-Charles Soria, Ivan Bieche, Pascale Tomasini, Aix-Marseille Université - École de médecine (AMU SMPM MED), Aix-Marseille Université - Faculté des sciences médicales et paramédicales (AMU SMPM), Aix Marseille Université (AMU)-Aix Marseille Université (AMU), Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut Gustave Roussy (IGR), Département de médecine oncologique [Gustave Roussy], Service de biostatistique et d'épidémiologie (SBE), Direction de la recherche clinique [Gustave Roussy], Institut Gustave Roussy (IGR)-Institut Gustave Roussy (IGR), Oncostat (U1018 (Équipe 2)), Institut Gustave Roussy (IGR)-Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Tarbiat Modares University [Tehran], Prédicteurs moléculaires et nouvelles cibles en oncologie (PMNCO), Institut Gustave Roussy (IGR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, ENGIE GREEN, parent, Service de pneumologie [Toulouse], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Centre Hospitalier Intercommunal Toulon-La Seyne sur Mer - Hôpital Sainte-Musse, Centre Hospitalier Lyon Sud [CHU - HCL] (CHLS), Hospices Civils de Lyon (HCL), Institut Curie [Paris], Centre de Bioinformatique (CBIO), Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Imagine - Institut des maladies génétiques (IHU) (Imagine - U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Centre d'Investigation Clinique en Biotherapie des cancers (CIC 1428 , CBT 507 ), Institut Gustave Roussy (IGR)-Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), UNICANCER, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Multidisciplinary Oncology and Therapeutic Innovations Unit, and Hôpital Nord [CHU - APHM]
Subjects: Pulmonary and Respiratory Medicine, Cancer Research, Lung Neoplasms, MESH: Mutation, DNA Copy Number Variations, Molecular biology, [SDV.CAN]Life Sciences [q-bio]/Cancer, [SDV.MHEP.PSR]Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, Targeted therapy, Carcinoma, Non-Small-Cell Lung, MESH: Tumor Microenvironment, Tumor Microenvironment, Humans, MESH: Lung, Lung, Randomized Controlled Trials as Topic, Comparative Genomic Hybridization, MESH: Humans, Brain Neoplasms, Brain metastases, MESH: Lung Neoplasms, MESH: Comparative Genomic Hybridization, MESH: Randomized Controlled Trials as Topic, Oncology, Mutation, MESH: Brain Neoplasms, MESH: DNA Copy Number Variations, Immunotherapy, Lung cancer, MESH: Carcinoma, Non-Small-Cell Lung
Abstract: Lung cancer remains the most frequent cause of brain metastases (BMs) and is responsible for high morbidity and mortality. Intracranial response to systemic treatments is inconsistent due to several mechanisms: genomic heterogeneity, blood-tumor barrier, and the brain-specific microenvironment. We conducted a study using data from the SAFIR02-LUNG trial. The primary objective was to compare the molecular profiles of non-small-cell lung cancer (NSCLC) with or without BMs. The secondary objective was to explore central nervous system (CNS) outcomes with various maintenance treatment regimens.In total, 365 patients harboring interpretable molecular data were included in this analysis. Clinical and biological data were collected. Genomic analyses were based on array-comparative genomic hybridization and next-generation sequencing (NGS) following the trial recommendations.Baseline genomic analyses of copy number variations identified a 24-gene signature specific to lung cancer BM occurrence, all previously known to take part in oncogenesis. NGS analysis identified a higher proportion of KRAS mutations in the BM-positive group (44.3% versus 32.3%), especially G12C mutations (63% versus 47%). Protein interaction analyses highlighted several functional interactions centered on EGFR. Furthermore, the risk of CNS progression was decreased with standard pemetrexed maintenance therapy. The highest rate of CNS progression was observed with durvalumab, probably because of the specific intracranial immune microenvironment.This work identified a 24-gene signature specific to lung cancer with BM. Further studies are needed to precisely determine the functional implications of these genes to identify new therapeutic targets for the treatment of lung cancer with BM.
Published: 2022

3. Mechanistic modeling of brain metastases in NSCLC provides computational markers for personalized prediction of outcome

Author: Sébastien Benzekry, Pirmin Schlicke, Pascale Tomasini, Eléonore Simon, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Aix-Marseille Université - Faculté de pharmacie (AMU PHARM), Aix Marseille Université (AMU), Technische Universität München = Technical University of Munich (TUM), Multidisciplinary Oncology and Therapeutic Innovations Unit, Hôpital Nord [CHU - APHM], Aix-Marseille Université - École de médecine (AMU SMPM MED), Aix-Marseille Université - Faculté des sciences médicales et paramédicales (AMU SMPM), and Aix Marseille Université (AMU)-Aix Marseille Université (AMU)
Subjects: [SDV.CAN]Life Sciences [q-bio]/Cancer
Abstract: BackgroundIntracranial progression after curative treatment of early-stage non-small cell lung cancer (NSCLC) occurs from 10 to 50% and is difficult to manage, given the heterogeneity of clinical presentations and the variability of treatments available.The objective of this study was to develop a mechanistic model of intracranial progression to predict survival following a first brain metastasis (BM) event.MethodsData included early-stage NSCLC patients treated with a curative intent who had a BM as the first and single relapse site (N=31).We propose a mechanistic mathematical model to estimate the amount and sizes of (visible and invisible) BMs. The two key parameters of the model areα, the proliferation rate of a single tumor cell; andμ, the per day, per cell, probability to metastasize. The predictive value of these individual computational biomarkers was evaluated.FindingsThe model was able to correctly describe the number and size of metastases at the time of first BM relapse for 20 patients. Parametersαandμwere significantly associated with overall survival (OS) (HR 1.65 (1.07-2.53) p=0.0029 and HR 1.95 (1.31-2.91) p=0.0109, respectively). Adding the computational markers to the clinical ones significantly improved the predictive value of OS (c-index increased from 0.585 (95% CI 0.569-0.602) to 0.713 (95% CI 0.700-0.726), pInterpretationWe demonstrated that our model was applicable to brain oligoprogressive patients in NSCLC and that the resulting computational markers had predictive potential. This may help lung cancer physicians to guide and personalize the management of NSCLC patients with intracranial oligoprogression.SIGNIFICANCE STATEMENTNon-small cell lung cancer is difficult to manage when brain metastases are present. This study presents a mathematical model that can be calibrated on individual patients’ data early in the treatment course to explain the growth dynamics of brain metastases and demonstrates that the mathematically derived parameters can serve as predictive tool in clinical routine care.Highlights-Mechanistic mathematical modeling allows individualized prognosis for lung cancer patients at first brain metastatic relapse-Individual model-derived computational parameters identifies high-risk patients in terms of brain metastasis progression and survival-Prognostic features include quantification of the number and sizes of both clinically visible and invisible brain metastases
Published: 2023

4. Treatment strategies for thymic carcinoma in a real-life setting. Insights from the RYTHMIC network

Author: Arthur Petat, Eric Dansin, Fabien Calcagno, Laurent Greillier, Eric Pichon, Mallorie Kerjouan, Christelle Clement-Duchene, Bertrand Mennecier, Virginie Westeel, François Thillays, Xavier Quantin, Youssef Oulkhouir, Luc Thiberville, Charles Ricordel, Vincent Thomas De Montpreville, Lara Chalabreysse, Véronique Hofman, Thierry Molina, Pierre Fournel, Laurence Bigay Game, Benjamin Besse, Nicolas Girard, Hospices Civils de Lyon (HCL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon, Centre Régional de Lutte contre le Cancer Oscar Lambret [Lille] (UNICANCER/Lille), Université de Lille-UNICANCER, Service d'Oncologie Médicale [CHRU Besançon], Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Service d'oncologie multidisciplinaire innovations thérapeutiques [Hôpital Nord - APHM], Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital Nord [CHU - APHM], Centre Hospitalier Régional Universitaire de Tours (CHRU Tours), CHU Pontchaillou [Rennes], Institut de Cancérologie de Lorraine - Alexis Vautrin [Nancy] (UNICANCER/ICL), UNICANCER, CHU Strasbourg, Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon), Institut de Cancérologie de l'Ouest [Angers/Nantes] (UNICANCER/ICO), Institut de Recherche en Cancérologie de Montpellier (IRCM - U1194 Inserm - UM), CRLCC Val d'Aurelle - Paul Lamarque-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN), CHU Rouen, Normandie Université (NU), Centre Chirurgical Marie Lannelongue (CCML), Hôpital Pasteur [Nice] (CHU), Département de Pathologie [CHU Necker], Université Sorbonne Paris Cité (USPC)-CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris Cité (UPCité), Institut de Cancérologie de la Loire Lucien Neuwirth, Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Département de médecine oncologique [Gustave Roussy], Institut Gustave Roussy (IGR), and Institut Curie [Paris]
Subjects: Cancer Research, Thymoma, Radiotherapy, [SDV.CAN]Life Sciences [q-bio]/Cancer, Thymus Neoplasms, Guidelines, Cohort Studies, Thymic carcinoma, Oncology, Humans, Chemotherapy, Surgery, Neoplasms, Glandular and Epithelial, Prospective Studies, Neoplasm Staging, Retrospective Studies
Abstract: Thymic carcinomas are aggressive and difficult to treat a subset of thymic epithelial tumours that represent a heterogeneous group of rare intrathoracic malignancies. The treatment strategy of thymic carcinomas is based on whether surgical resection may be achieved, which represents the most significant favourable prognostic factor on survival. For this study, we took advantage of the unique prospective Réseau tumeurs THYMiques et Cancer (RYTHMIC) database to describe baseline characteristics, analyse treatment strategies in light of existing guidelines and provide landmark patient outcomes data with regards to response and survival of patients in a real-life clinical practice setting.Inclusion criteria for this analysis were the following: (1) histologically-confirmed thymic carcinomas - excluding neuroendocrine tumours-after pathological review by the RYTHMIC pathology panel, (2) discussion of the case at the RYTHMIC multidisciplinary tumour board, (3) at least one active treatment modality.A total of 213 patients were analysed. Overall, 60 (28%) patients were considered as surgical candidates upfront, 91 (43%) patients received primary chemotherapy, and 62 (29%) patients received exclusive chemotherapy. Median overall survival (OS) was 49.2 months (IC95%: 34.8-63.6); OS was significantly longer in patients with a lower stage at diagnosis (p 0.001), who were operated on upfront, as opposed to patients who received primary or exclusive chemotherapy (p 0.001). Surgery, conducted upfront or after primary chemotherapy, was significantly associated with more prolonged OS (p 0.001); complete resection and postoperative radiotherapy were also predictors of better outcome (p = 0.018 and p = 0.051, respectively).Our cohort is the first to analyse in-depth outcomes and treatment strategies in a prospective cohort of consecutive patients with thymic carcinoma. While we confirm the major prognostic impact of surgery, our data highlight the need for optimised multidisciplinary management and innovative therapies as the survival of patients remains limited.
Published: 2022

5. Pharmacokinetics of oral vinorelbine in French children with recurrent or progressive primary low‐grade glioma

Author: Alicia Probst, Emilie De Carli, Isabelle Aerts, Pascal Chastagner, Natacha Entz-Werle, Caroline Solas, Anne-Isabelle Bertozzi-Salamon, Nicolas André, Anne Pagnier, Emmanuelle Tresch-Bruneel, Pierre Leblond, Jacques Grill, Didier Frappaz, Mourad Hamimed, Florence Gattacceca, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Simulation and Modeling of Adaptive Response for Therapeutics in Cancer (SMARTc), Centre de Recherche en Cancérologie de Marseille (CRCM), Pédiatrie et oncologie pédiatrique [Hôpital de la Timone - APHM], Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE), Centre Régional de Lutte contre le Cancer Oscar Lambret [Lille] (UNICANCER/Lille), Université de Lille-UNICANCER, Centre Hospitalier Universitaire de Nancy (CHU Nancy), Centre Hospitalier Universitaire [Grenoble] (CHU), Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM), Laboratoire de Bioimagerie et Pathologies (LBP), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), CHU Strasbourg, Vectorologie et thérapeutiques anti-cancéreuses [Villejuif] (UMR 8203), Université Paris-Sud - Paris 11 (UP11)-Institut Gustave Roussy (IGR)-Centre National de la Recherche Scientifique (CNRS), Département de cancérologie de l'enfant et de l'adolescent [Gustave Roussy], Institut Gustave Roussy (IGR), Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology (MCMCC), Centre Léon Bérard [Lyon], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Unité des Virus émergents [Marseille] (UVE - Faculté de Médecine), Université de la Méditerranée - Aix-Marseille 2-Faculté de Médecine [Marseille], Université de la Méditerranée - Aix-Marseille 2, and Hôpital de la Timone [CHU - APHM] (TIMONE)
Subjects: medicine.medical_specialty, Adolescent, Phases of clinical research, Vinorelbine, Gastroenterology, 03 medical and health sciences, 0302 clinical medicine, Pharmacokinetics, Bayesian multivariate linear regression, Glioma, Internal medicine, Humans, Medicine, Pharmacology (medical), Child, Infusions, Intravenous, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, Pharmacology, Body surface area, Volume of distribution, 0303 health sciences, business.industry, [SDV.SP]Life Sciences [q-bio]/Pharmaceutical sciences, medicine.disease, 3. Good health, 030220 oncology & carcinogenesis, Low-Grade Glioma, Neoplasm Recurrence, Local, business, Half-Life, medicine.drug
Abstract: AIM There is a crucial need for pharmacokinetic (PK) data of oral vinorelbine (VNR) in pediatric population. The aim of this work was to assess the PK profile of orally administered VNR in children with recurrent/progressive primary low-grade glioma (LGG). METHODS A multicentric, open-label, single-arm intervention phase II study was conducted. Patients, aged between 6 and 18 years, with histologically confirmed recurrent or progressive primary LGG or non-documented typical optic pathway tumors, were included. PK parameters were estimated by non-compartmental analysis using Phoenix WinNonlin® software (version 8.0, Certara, Inc.). The Influence of demographic and biological covariates on VNR PK parameters was investigated using a multivariate linear regression analysis. RESULTS PK analysis included 36 patients with a median age (range) of 11 (6-17) years. Estimates of apparent oral clearance (CL/F), apparent volume of distribution (V/F), half-life (t1/2 ) and their between-subject variability (CV%) at 60 mg.m-2 dose level, were 472 L.h-1 (51.8%), 7002 L (57.9%) and 10 h (21.0%), respectively. Negligible accumulation of VNR between C1 and C2 was observed. CL/F and V/F were found to increase with body surface area (BSA) (p = 0.004). Lower area under the concentration-time curve (AUC) levels were observed among children in comparison to adults. CONCLUSION Higher doses may be necessary for children with LGG. BSA showed a significant impact on VNR systemic exposure. We believe that our findings will serve as a basis for further studies to better characterize the concentration-response relationships of VNR among pediatric patients.
Published: 2021

6. Pharmacokinetics and pharmacogenetics of liposomal cytarabine in AML patients treated with CPX-351

Author: Yael Berda-Haddad, Laure Farnault, Mourad Hamimed, Joseph Ciccolini, Geoffroy Venton, Régis Costello, L'Houcine Ouafik, Mélanie Donnette, Raphaelle Fanciullino, Elise Kaspi, Bruno Lacarelle, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Simulation and Modeling of Adaptive Response for Therapeutics in Cancer (SMARTc), Centre de Recherche en Cancérologie de Marseille (CRCM), Hôpital de la Conception [CHU - APHM] (LA CONCEPTION), Laboratoire de Biologie Cellulaire [Hôpital de la Timone - APHM], Assistance Publique - Hôpitaux de Marseille (APHM)-Hôpital de la Timone [CHU - APHM] (TIMONE), Hôpital Nord [CHU - APHM], Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Aix Marseille Université (AMU), and Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE)
Subjects: Adult, Daunorubicin, [SDV]Life Sciences [q-bio], Pharmaceutical Science, Pharmacology, 030226 pharmacology & pharmacy, 03 medical and health sciences, 0302 clinical medicine, Pharmacokinetics, Humans, Medicine, ComputingMilieux_MISCELLANEOUS, business.industry, Cytarabine, Myeloid leukemia, [SDV.SP]Life Sciences [q-bio]/Pharmaceutical sciences, medicine.disease, 3. Good health, Leukemia, Myeloid, Acute, medicine.anatomical_structure, Pharmacogenetics, [SDV.TOX]Life Sciences [q-bio]/Toxicology, 030220 oncology & carcinogenesis, Toxicity, Bone marrow, business, Febrile neutropenia, medicine.drug
Abstract: CPX-351 is a liposome encapsulating cytarabine and daunorubicin for treating Acute Myeloid Leukemia (AML) patients. To what extent differences in cytidine deaminase (CDA) activity, the enzyme that catabolizes free cytarabine in the liver, can affect the pharmacokinetics of liposomal cytarabine as well, is unknown. We have studied the pharmacokinetics (PK) of released, liposomal and total cytarabine using a population-modeling approach in 9 adult AML patients treated with liposomal CPX-351. Exposure levels and PK parameters were compared with respect to the patient's CDA status (i.e., Poor Metabolizer (PM) vs. Extensive Metabolizer (EM)). Overall response rate was 75%, and 56% of patients had non-hematological severe toxicities, including one lethal toxicity. All patients had febrile neutropenia. A large (>60%) inter-individual variability was observed on pharmacokinetics parameters and subsequent drug levels. A trend towards severe toxicities was observed in patients with higher exposure of cytarabine. Results showed that liposomal CPX-351 led to sustained exposure with reduced clearance (Cl = 0.16 L/h) and prolonged half-life (T1/2 = 28 h). Liposomal nanoparticles were observed transiently in bone marrow with cytarabine levels 2.3-time higher than in plasma. Seven out of 9 patients were PM with a strong impact on the PK parameters, i.e., PM patients showing higher cytarabine levels as compared with EM patients (AUC: 5536 vs. 1784 ng/mL.h), sustained plasma exposure (T1/2: 33.9 vs. 13.7 h), and reduced clearance (Cl: 0.12 vs. 0.29 L/h). This proof-of-concept study suggests that CDA status has a major impact on cytarabine PK and possibly safety in AML patients even when administered as a liposome.
Published: 2021

7. Epidemiological Study to Assess the Prevalence of Lung Cancer in patients with smoking-associated atherosclerotic cardiovascular diseases: PREVALUNG study protocol

Author: David Boulate, Marine Fidelle, Caroline Caramella, Justin Issard, Olivier Planché, Pauline Pradère, Daniel Garelik, Océane Hache, Lilia Lamrani, Marc Zins, Hélène Beaussier, Gilles Chatellier, Elie Fadel, Laurence Zitvogel, Benjamin Besse, Olaf Mercier, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), Hôpital Marie-Lannelongue, Immunologie anti-tumorale et immunothérapie des cancers (ITIC), Institut Gustave Roussy (IGR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Institut Gustave Roussy (IGR), and Département de médecine oncologique [Gustave Roussy]
Subjects: Thoracic medicine, [SDV]Life Sciences [q-bio], Vascular medicine, General Medicine, Respiratory tract tumours, Chest imaging
Abstract: IntroductionEligibility criteria definition for a lung cancer screening (LCS) is an unmet need. We hypothesised that patients with a history of atheromatous cardiovascular disease (ACVD) associated with tobacco consumption are at risk of lung cancer (LC). The main objective is to assess LC prevalence among patients with ACVD and history of tobacco consumption by using low-dose chest CT scan. Secondary objectives include the evaluation LCS in this population and the constitution of a biological biobank to stratify risk of LC.Methods and analysisWe are performing a monocentric ‘single-centre’ prospective study among patients followed up in adult cardiovascular programmes of vascular surgery, cardiology and cardiac surgery recruited from 18 November 2019 to 18 May 2021. The inclusion criteria are (1) age 45–75 years old, (2) history of ACVD and (3) history of daily tobacco consumption for 10 years prior to onset of ACVD. Exclusion criteria are symptoms of LC, existing follow-up for pulmonary nodule, fibrosis, pulmonary hypertension, resting dyspnoea and active pulmonary infectious disease. We targeted the inclusion of 500 patients. After inclusion (V0), patients are scheduled for a low-dose chest CT and blood and faeces harvesting within 7 months (V1). Each patient is scheduled for a follow-up by telephonic visits at month 3 (V2), month 6 (V3) and month 12 (V4) after V1. Each patient is followed up until 1 year after V1 (14 February 2023). We measure LC prevalence and quantify the National Lung Screening Trial and Dutch-Belgian Randomized Lung Cancer Screening Trial (NELSON) trial eligibility criteria, radiation, positive screening, false positivity, rate of localised LC diagnosis, quality of life with the Short Form 12 (SF-12) and anxiety with the Spielberger State-Trait Anxiety Inventory A and B (STAI-YA and STAI-YB, respectively), smoking cessation and onset of cardiovascular and oncological events within 1 year of follow-up. A case–control study nested in the cohort is performed to identify clinical or biological candidate biomarkers of LC.Ethics and disseminationThe study was approved according the French Jardé law; the study is referenced at the French ‘Agence Nationale de Sécurité du Médicament et des Produits de Santé’ (reference ID RCB: 2019-A00262-55) and registered on clinicaltrial.gov. The results of the study will be presented after the closure of the follow-up scheduled on 14 February 2023 and disseminated through peer-reviewed journals and national and international conferences.Trial registration numberNCT03976804.
Published: 2022

8. Therapeutic Drug Monitoring of Biotherapies in oncology: hype or hope

Author: Ciccolini, Joseph, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), European Organization for Research and Treatment of Cancer, and Ciccolini, Joseph
Subjects: [SDV] Life Sciences [q-bio], [SDV]Life Sciences [q-bio]
Abstract: International audience
Published: 2022

9. Place des anti-BRAF dans le mCRC BRAF-mut: aspects pharmacologiques

Author: Ciccolini, Joseph, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Ciccolini, Joseph
Subjects: [SDV] Life Sciences [q-bio], [SDV]Life Sciences [q-bio]
Abstract: National audience
Published: 2022

10. Stereotactic radiosurgery for post operative brain metastasic surgical cavities: a single institution experience

Author: Cantaloube, Marie, Boucekine, Mohamed, Balossier, Anne, Muracciole, Xavier, Meyer, Mickael, Delsanti, Christine, Carron, Romain, Beltaifa, Yassine Mohamed, Figarella-Branger, Domnique, Regis, Jean, Padovani, Laetitia, Service de radiothérapie - [Hôpital de la Timone - Hôpital Nord - APHM], Hôpital de la Timone [CHU - APHM] (TIMONE)- Hôpital Nord [CHU - APHM], Genome Instability and Carcinogenesis, Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre d'études et de recherche sur les services de santé et la qualité de vie (CEReSS), Aix Marseille Université (AMU), APHM, Hôpital de la Timone, Service de Neurochirurgie Fonctionnelle et Stéréotaxique, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Service d'Anatomo-Cyto-Pathologie et de NeuroPathologie [Hôpital de la Timone - APHM] (ACPNP), and Aix Marseille Université (AMU)- Hôpital de la Timone [CHU - APHM] (TIMONE)
Subjects: Salvage Therapy, MESH: Humans, Brain Neoplasms, Gamma Knife, Brain metastasis, Brain, MESH: Retrospective Studies, [SDV.CAN]Life Sciences [q-bio]/Cancer, Radiosurgery, Resection, MESH: Salvage Therapy, MESH: Brain, Treatment Outcome, Oncology, MESH: Radiosurgery, MESH: Brain Neoplasms, Humans, Radiology, Nuclear Medicine and imaging, Neoplasm Recurrence, Local, MESH: Neoplasm Recurrence, Local, Tumor bed, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Retrospective Studies, MESH: Treatment Outcome
Abstract: Background The standard therapy for brain metastasis was surgery combined with whole brain radiotherapy (WBRT). The latter is however, associated with important neurocognitive toxicity. To reduce this toxicity, postoperative stereotactic radiosurgery (SRS) is a promising technique. We assessed the efficacy and the tolerance to postoperative Gamma Knife radiosurgery (GK) on the tumor bed after resection of brain metastases. Methods Between February 2011 and December 2016, following macroscopic complete surgical resection, 64 patients and 65 surgical cavities were treated by GK in our institution. The indication for adjuvant radiosurgery was a multidisciplinary decision. The main assessment criteria considered in this study were local control, intracranial metastasis-free survival (ICMFS), overall survival and toxicity. Results Median follow-up: 11.1 months. Median time between surgery and radiosurgery: 35 days. Median dose was 20 Gy prescribed to the 50% isodose line, for a median treated volume of 5.6 cc. Four patients (7%) suffered from local recurrence. Local recurrence-free, intracranial recurrence-free and overall survival at 1 year were 97.5%, 57.6% and 62.4% respectively. In total, 23 patients (41%) suffered from intracranial recurrence outside the tumor bed. In univariate analysis: concomitant GK treatment of multiple lesions and the tumor bed was associated with a decrease in ICMFS (HR = 1.16 [1.005–1.34] p = 0.04). In multivariate analysis: a non-lung primary tumor was significantly associated with a decrease in ICMFS (HR = 8.04 [1.82–35.4] p = 0.006). An increase in performance status (PS) and in the initial number of cerebral metastases significantly reduced overall survival (HR = 5.4 [1.11–26.3] p = 0.037, HR = 2.7 [1.004–7.36] p = 0.049, respectively) and One radiation necrosis histologically proven. Conclusion Our study confirmed that postoperative GK after resection of cerebral metastases is an efficient and well-tolerated technique, to treat volumes of all sizes (0.8 to 40 cc). Iterative SRS or salvage WBRT can be performed in cases of intracranial relapse, postponing WBRT with its potential side effects.
Published: 2022

11. Anti CDK4/6: aspects pharmacologiques et PK/PD

Author: Ciccolini, Joseph, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, and Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
Subjects: [SDV]Life Sciences [q-bio], [SDV.CAN]Life Sciences [q-bio]/Cancer
Abstract: National audience
Published: 2022

12. Renal impairment and DPD testing: Watch out for false‐positive results!

Author: Laure Carriat, Sylvie Quaranta, Caroline Solas, Maelle Rony, Joseph Ciccolini, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, and Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Pharmacology, renal impairment, safety, MESH: Antimetabolites, Antineoplastic, MESH: Uracil, MESH: Humans, [SDV]Life Sciences [q-bio], MESH: Capecitabine, DPD testing, MESH: Renal Insufficiency, dialysis, Pharmacology (medical), MESH: Dihydropyrimidine Dehydrogenase Deficiency, MESH: Neoplasms, 5-FU, MESH: Dihydrouracil Dehydrogenase (NADP), MESH: Fluorouracil
Abstract: International audience; Measuring uracil (U) levels in plasma is a convenient surrogate to establish dihydropyrimidine dehydrogenase (DPD) status in patients scheduled with 5-fluorouracil (5-FU) or capecitabine. To what extent renal impairment could impact on U levels and thus be a confounding factor is a rising concern. Here, we report the case of a cancer patient with severe renal impairment scheduled for 5-FU-based regimen. Determination of his DPD status was complicated because of his condition and the influence of intermittent haemodialysis when monitoring U levels. The patient was initially identified as markedly DPD-deficient upon U measurement (i.e., U = 40 ng/mL), but further monitoring between and immediately after dialysis showed mild deficiency only (i.e., U = 34 and U = 19 ng/mL, respectively). Despite this discrepancy, a starting dose of 5-FU was cut by 50% upon treatment initiation. Tolerance was good and 5-FU dosing was next shifted to 25% reduction, then further shifted to normal dosing at the 5th course, with still no sign for drug-related toxicities. Further DPYD genotyping showed none of the four allelic variants usually associated with loss of DPD activity. Of note, the excellent tolerance upon standard dosing strongly suggests that this patient was actually not DPD-deficient, despite U values always above normal concentrations. This case report highlights how critical is the information regarding the renal function of patients with cancer when phenotyping DPD using U plasma as a surrogate, and that U accumulation in patients with such condition is likely to yield false-positive results.
Published: 2022

13. Model-informed and PK-guided dosing in the era of immunotherapy

Author: Ciccolini, Joseph, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Australasian Pharmaceutical Science Association and Australasian Society of Clinical and Experimental Pharmacologists and Toxicologists, and Ciccolini, Joseph
Subjects: [SDV] Life Sciences [q-bio], [SDV]Life Sciences [q-bio]
Abstract: International audience
Published: 2022

14. Nanotherapeutics Plus Immunotherapy in Oncology: Who Brings What to the Table?

Author: Elise, Timon-David, Carla, Perez, Anne, Rodallec, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Simulation and Modeling of Adaptive Response for Therapeutics in Cancer (SMARTc), and Centre de Recherche en Cancérologie de Marseille (CRCM)
Subjects: Pharmaceutical Science, [SDV.CAN]Life Sciences [q-bio]/Cancer
Abstract: International audience; While the number of oncology-related nanotherapeutics and immunotherapies is constantly increasing, cancer patients still suffer from a lack of efficacy and treatment resistance. Among the investigated strategies, patient selection and combinations appear to be of great hope. This review will focus on combining nanotherapeutics and immunotherapies together, how they can dually optimize each other to face such limits, bringing us into a new field called nano-immunotherapy. While looking at current clinical trials, we will expose how passive immunotherapies, such as antibodies and ADCs, can boost nanoparticle tumor uptake and tumor cell internalization. Conversely, we will study how immunotherapies can benefit from nanotherapeutics which can optimize their lipophilicity, permeability, and distribution (e.g., greater tumor uptake, BBB crossing, etc.), tumor, tumor microenvironment, and immune system targeting properties.
Published: 2022

15. Cefotaxime dosage optimization in intensive care patients by population pharmacokinetic analysis

Author: Deschamps, Anthéa, Gattacceca, Florence, Velly, Lionel, Jouve, Elisabeth, Guilhaumou, Romain, Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de Pharmacologie Clinique [Hôpital de la Timone - APHM], Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE), Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Service d'anesthésie et de réanimation [Hôpital de la Timone - APHM], Hôpital de la Timone [CHU - APHM] (TIMONE), Aix-Marseille Université, Faculté de Pharmacie, and karlsen, melanie
Subjects: Antibiotics, [SDV.SP.PHARMA] Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, [SDV.SP.PHARMA]Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, Pharmaco-kinetics, Therapeutic drug monitoring TDM, ComputingMilieux_MISCELLANEOUS
Abstract: National audience; Background: Cefotaxime is a beta-lactam antibiotics commonly used in intensive care unit (ICU). In this population, pathophysiological modifications induce a high inter-individual and intra-individual pharmacokinetic variability. This variability can result in supra or sub-therapeutic concentrations of cefotaxime and adapted drug regimen are required. The aim of this study was to propose optimized cefotaxime treatment in ICU patients by a population pharmacokinetic approach. Methods: In this prospective, multicenter, observational study (October 2015 – May 2017), patients hospitalized in ICU received continuous administration of cefotaxime. The cefotaxime dosing regimen was a loading dose (2g-4g/0.5h) then a continuous infusion (1-24g/24h). Therapeutic drug monitoring allowed the measurement of cefotaxime concentration at day 1, 4 and 7 after drug initiation. Concentrations were assayed by a validated HPLC-UV method, and nonlinear mixed-effects modeling was performed (NONMEM version 7.4). After determination of the base model that best described the data set, the influence of several covariates was tested on the model. Simulations were realized to propose adapted dosing regimens allowing to achieve the PK/PD target, namely 100% of time during a dosing interval with the free drug concentration exceeding 4 times the Minimum Inhibitory Concentration (MIC).Results: From 77 ICU hospitalized patients (31 females, 45 males, age = 55.84 ± 18.1 years), 255 cefotaxime plasma concentrations were available for analysis. The data were best described by a one-compartment model with proportional residual error. The model was qualified based on goodness-of-fit plots and precision of the parameter estimates. Typical population clearance (11.4 L/min) and volume of distribution (27 L) were in line with previously published results in different adult and pediatric population. Model-based simulations were performed under various cefotaxime regimen to assess target attainment and identify optimal protocols. Conclusions: To our knowledge, we developed the first pharmacokinetic model of cefotaxime in critically ill adult population. After external evaluation, this model will allow to adapt empirical cefotaxime treatment dose to improve antibiotic exposure and PK/PD target attainment in ICU patients.
Published: 2022

16. Pharmacokinetics of intact lipid nanocapsules using new quantitative FRET technique

Author: Lebreton, Vincent, Kaeokhamloed, Norraseth, Vasylaki, Anastasiia, Hilairet, Grégory, Mellinger, Adélie, Béjaud, Jérôme, Saulnier, Patrick, Lagarce, Frédéric, Gattacceca, Florence, Legeay, Samuel, Roger, Emilie, Micro et Nanomédecines Translationnelles (MINT), Université d'Angers (UA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), SFR UA 4208 Interactions Cellulaires et Applications Thérapeutiques (ICAT), Université d'Angers (UA), Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, and Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Nanocapsules, Drug Compounding, Fluorescence Resonance Energy Transfer, [SDV.SP.PHARMA]Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, Pharmaceutical Science, Animals, Lipids, Rats
Abstract: International audience; The present study investigated the pharmacokinetics of intact lipid nanocapsules (LNCs) after intravenous administration in rats. Six different Förster resonance energy transfer LNCs (FRET-LNCs) have been studied with 2 sizes (50 and 85 nm) and 3 coating types (none, DSPE-mPEG 2000 or stearylamine). A FRET-LNCs blood extraction method was developed to retain an accurate FRET signal. Intact FRET-LNCs were specifically quantified through combination of FRET signal and Nano Tracker Analysis. Pharmacokinetic data were first described by non-compartmental analysis, then used to develop a population pharmacokinetic model. The pharmacokinetic elimination of FRET-LNCs was non-linear and dependent on size and surface modification, while the distribution was dependent on size. The LNCs 85 nm volume of distribution was lower than LNCs 50 nm. As expected, LNCs 85 nm with PEG coating displayed a lower clearance than other formulations. Surprisingly, this study highlighted a faster elimination of LNCs 50 nm with PEG compared to other formulations which could be explained by instability in blood. This first pharmacokinetic model of intact LNCs allowed a thorough understanding of the influence of size and coating on pharmacokinetic properties and paves the way for future mechanistic modeling approaches to predict the fate of LNCs in vivo.
Published: 2022

17. Semi-mechanistic modelling to show the impact of structural modifications on radiolabeled-dendrimers pharmacokinetics

Author: Ou, Jessica, Louis, Béatrice, Nail, Vincent, Balasse, Laure, Bouhlel, Ahlem, Chabert, Adrien, Roussel, Tom, Peng, Ling, Garrigue, Philippe, Guillet, Benjamin, Gattacceca, Florence, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), Centre recherche en CardioVasculaire et Nutrition = Center for CardioVascular and Nutrition research (C2VN), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre Interdisciplinaire de Nanoscience de Marseille (CINaM), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), and Ou, Jessica
Subjects: [SDV.SP.PHARMA] Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, [SDV.SP.PHARMA]Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology
Abstract: International audience
Published: 2022

18. Cancer nanomedicine - from the bench to the bedside: rise of ADC in oncology

Author: Ciccolini, Joseph, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Ciccolini, Joseph
Subjects: [SDV] Life Sciences [q-bio], [SDV.CAN] Life Sciences [q-bio]/Cancer, [SDV]Life Sciences [q-bio], [SDV.CAN]Life Sciences [q-bio]/Cancer
Abstract: International audience
Published: 2022

19. Pharmacometrics of immune checkpoint Inhibitors

Author: Ciccolini, Joseph, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), EuroBiomed, and Ciccolini, Joseph
Subjects: [SDV] Life Sciences [q-bio], [SDV]Life Sciences [q-bio]
Abstract: National audience
Published: 2022

20. A Phase 1–2 Study of Rovalpituzumab Tesirine in Combination With Nivolumab Plus or Minus Ipilimumab in Patients With Previously Treated Extensive-Stage SCLC

Author: John Wrangle, Ticiana Leal, Gilles Robinet, Neal Ready, David Maag, Jyoti Malhotra, Melissa Lynne Johnson, Satwant Lally, Petros Nikolinakos, Jyoti D. Patel, Daniel Morgensztern, Benjamin Besse, Vincent Blot, Giuseppe Curigliano, Ricardo Valenzuela, Laurent Greillier, Jonathan M. Lehman, Rutgers cancer institute of New Jersey [Newark, NJ], University Cancer and Blood Center (UCBC), University of Wisconsin-Madison, Vanderbilt University Medical Center [Nashville], Vanderbilt University [Nashville], Washington University School of Medicine in St. Louis, Washington University in Saint Louis (WUSTL), Feinberg School of Medicine, Northwestern University [Evanston], Medical University of South Carolina [Charleston] (MUSC), Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS), Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Sarah Cannon Research Institute [Nashville, Tennessee], Duke University Medical Center, Hôpital Morvan - CHRU de Brest (CHU - BREST ), Abbvie Inc. [North Chicago], Institut Gustave Roussy (IGR), Université Paris-Saclay, and Département de médecine oncologique [Gustave Roussy]
Subjects: 0301 basic medicine, Pulmonary and Respiratory Medicine, medicine.medical_specialty, Immunoconjugates, Lung Neoplasms, Combination therapy, [SDV.CAN]Life Sciences [q-bio]/Cancer, Ipilimumab, Antibodies, Monoclonal, Humanized, [SDV.MHEP.PSR]Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, Gastroenterology, MESH: Benzodiazepinones, MESH: Ipilimumab, 03 medical and health sciences, Clinical trials, 0302 clinical medicine, Internal medicine, Antineoplastic Combined Chemotherapy Protocols, MESH: Immunoconjugates, medicine, Humans, Antibody-drug conjugates, Adverse effect, Benzodiazepinones, MESH: Humans, business.industry, Rovalpituzumab tesirine, respiratory tract diseases, MESH: Lung Neoplasms, MESH: Antineoplastic Combined Chemotherapy Protocols, Nivolumab, 030104 developmental biology, Oncology, Tolerability, MESH: Antibodies, Monoclonal, Humanized, Response Evaluation Criteria in Solid Tumors, 030220 oncology & carcinogenesis, Cohort, Small-molecule agents, MESH: Nivolumab, [SDV.IMM]Life Sciences [q-bio]/Immunology, Immunotherapy, Lung cancer, business, medicine.drug
Abstract: Introduction This open-label, phase 1–2 study evaluated the safety and efficacy of rovalpituzumab tesirine (Rova-T), an antibody-drug conjugate targeting DLL3, plus immune checkpoint inhibitors nivolumab plus or minus ipilimumab in previously treated extensive-stage SCLC (ES SCLC). Methods Patients with histologically or cytologically confirmed, previously treated (two or more lines of therapy) ES SCLC were enrolled into two cohorts. Cohort 1 received 0.3 mg/kg Rova-T (once every 6 wk for two cycles) plus 360 mg nivolumab (two 3-wk cycles beginning on week 4). Cohort 2 received the same dosage of Rova-T as cohort 1 plus 1 mg/kg nivolumab (four 3-wk cycles) and 1 mg/kg ipilimumab (beginning week 4). Both cohorts received 480 mg nivolumab every 4 weeks starting at week 10. Key objectives were to evaluate safety and tolerability and efficacy (per Response Evaluation Criteria in Solid Tumors version 1.1). The response-related results are based on centrally read data. Results A total of 42 patients received therapy: cohort 1, n = 30; cohort 2, n = 12. Overall, 43% received two or more previous lines of therapy. All patients experienced one or more treatment-emergent adverse event (TEAE); 41 patients reported AEs considered related to the study drug by the investigator. The most frequent TEAE was pleural effusion (n = 20, 48%); most common grade greater than or equal to 3 was anemia (n = 9, 21%). Three grade 5 TEAEs considered related to the study drug were reported (cohort 1): pneumonitis (n = 2), acute kidney injury (n = 1). The objective response rate was 30% (12 of 40): cohort 1, 27.6% (8 of 29); cohort 2, 36.4% (4 of 11); all partial responses. Conclusions Despite encouraging antitumor activity in previously treated ES SCLC, combination therapy with Rova-T and nivolumab plus or minus ipilimumab was not well tolerated at the dose levels and administration schedules evaluated.
Published: 2021

21. Tumor growth monitoring in breast cancer xenografts: A good technique for a strong ethic

Author: Anne Rodallec, Cristina Vaghi, Joseph Ciccolini, Raphaelle Fanciullino, Sebastien Benzekry, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Simulation and Modeling of Adaptive Response for Therapeutics in Cancer (SMARTc), Centre de Recherche en Cancérologie de Marseille (CRCM), Modélisation Mathématique pour l'Oncologie (MONC), Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Institut Bergonié [Bordeaux], UNICANCER-UNICANCER-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), and Assistance Publique - Hôpitaux de Marseille (APHM)
Subjects: Mice, Multidisciplinary, Transplantation, Heterologous, Animals, Heterografts, Humans, Breast Neoplasms, Female, [SDV.CAN]Life Sciences [q-bio]/Cancer, Models, Theoretical, Tumor Burden
Abstract: Purpose Although recent regulations improved conditions of laboratory animals, their use remains essential in cancer research to determine treatment efficacy. In most cases, such experiments are performed on xenografted animals for which tumor volume is mostly estimated from caliper measurements. However, many formulas have been employed for this estimation and no standardization is available yet. Methods Using previous animal studies, we compared all formulas used by the scientific community in 2019. Data were collected from 93 mice orthotopically xenografted with human breast cancer cells. All formulas were evaluated and ranked based on correlation and lower mean relative error. They were then used in a Gompertz quantitative model of tumor growth. Results Seven formulas for tumor volume estimation were identified and a statistically significant difference was observed among them (ANOVA test, p < 2.10−16), with the ellipsoid formula (1/6 π × L × W × (L + W)/2) being the most accurate (mean relative error = 0.272 ± 0.201). This was confirmed by the mathematical modeling analysis where this formula resulted in the smallest estimated residual variability. Interestingly, such result was no longer valid for tumors over 1968 ± 425 mg, for which a cubic formula (L x W x H) should be preferred. Main findings When considering that tumor volume remains under 1500mm3, to limit animal stress, improve tumor growth monitoring and go toward mathematic models, the following formula 1/6 π × L × W x (L + W)/2 should be preferred.
Published: 2022

22. Lack of Prognostic Value of CTNNB1 Mutation Profile in Desmoid-Type Fibromatosis

Author: Nicolas Penel, Sylvie Bonvalot, André-Michel Bimbai, Alexandra Meurgey, François Le Loarer, Sébastien Salas, Sophie Piperno-Neumann, Christine Chevreau, Pascaline Boudou-Rouquette, Pascale Dubray-Longeras, Jean-Emmanuel Kurtz, Cécile Guillemet, Emmanuelle Bompas, Antoine Italiano, Axel Le Cesne, Daniel Orbach, Julien Thery, Marie-Cécile Le Deley, Jean-Yves Blay, Olivier Mir, Centre Régional de Lutte contre le Cancer Oscar Lambret [Lille] (UNICANCER/Lille), Université de Lille-UNICANCER, Institut Curie [Paris], Université de Bordeaux (UB), Service d’Oncologie Médicale [Hôpital de la Timone - APHM], Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE), Marseille medical genetics - Centre de génétique médicale de Marseille (MMG), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Département d'Oncologie Médicale [Institut Curie, Paris], Institut Claudius Regaud, Hôpital Cochin [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre Jean Perrin [Clermont-Ferrand] (UNICANCER/CJP), UNICANCER, Les Hôpitaux Universitaires de Strasbourg (HUS), Service d'Oncologie Médicale, CRLCC Haute Normandie-Centre de Lutte Contre le Cancer Henri Becquerel Normandie Rouen (CLCC Henri Becquerel), Institut de Cancérologie de l'Ouest [Angers/Nantes] (UNICANCER/ICO), Laboratory of Solid Tumors Genetics, Nice University Hospital, Institut de signalisation, biologie du développement et cancer (ISBDC), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Institut Gustave Roussy (IGR), Département de médecine oncologique [Gustave Roussy], Centre d'Etudes Médiévales de Montpellier (CEMM), Université Paul-Valéry - Montpellier 3 (UPVM), Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Sud - Paris 11 (UP11)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de biostatistique et d'épidémiologie (SBE), Direction de la recherche clinique [Gustave Roussy], Institut Gustave Roussy (IGR)-Institut Gustave Roussy (IGR), Université Paris Descartes - Faculté de Médecine (UPD5 Médecine), and Université Paris Descartes - Paris 5 (UPD5)
Subjects: Cancer Research, MESH: Humans, Oncology, MESH: beta Catenin, MESH: Fibromatosis, Aggressive, MESH: Adult, [SDV.CAN]Life Sciences [q-bio]/Cancer, MESH: Female, MESH: Cohort Studies, MESH: Neoplasm Recurrence, Local, MESH: Male, MESH: Prognosis, MESH: Prospective Studies
Abstract: Purpose: This prospective nationwide cohort study aimed to investigate desmoid-type fibromatosis (DF) outcomes, focusing on the prognostic value of CTNNB1 mutations. Experimental Design: ALTITUDES (NCT02867033) was a nationwide prospective cohort study of DF diagnosed between January 2016 and December 2020. At diagnosis, CTNNB1 molecular alterations were identified using next-generation sequencing or Sanger sequencing. The primary endpoint was event-free survival (EFS; progression, relapse, or death). We enrolled 628 patients managed by active surveillance, surgical resection, or systemic treatment as first-line therapy. Results: Overall, 516 (82.2%) patients [368 females (71.3%), median age 40.3 years (range, 1–89)] were eligible for analysis. In 435 (84.3%) cases, there was one CTNNB1 molecular alteration: p.T41A, p.S45F, or p.S45P. The first-line management was active surveillance in 352 (68.2%), surgical resection in 120 (23.3%), and systemic treatments in 44 (8.5%) patients. CTNNB1 mutation distribution was similar across the three therapeutic groups. The median follow-up period was 24.7 (range, 0.4–59.7) months. The estimated 3-year EFS rate was 66.2% [95% confidence interval (CI), 60.5%–71.2%]. DF harboring p.S45F was significantly associated with male sex (P = 0.03), non-abdominal wall sites (P = 0.05), pain (P = 0.007), and large tumor size (P = 0.025). CTNNB1 p.S45F mutation was not significantly associated with EFS, either in univariate (HR, 1.06; 95% CI, 0.65–1.73; P = 0.81) or in multivariate analysis (HR, 0.91; 95% CI, 0.55–1.49; P = 0.71). Conclusions: We found that CTNNB1 mutation profile was associated with unfavorable prognostic factors but was not a prognostic factor for EFS. See related commentary by Greene and Van Tine, p. 3911
Published: 2022

23. Practical identifiability analysis of a mechanistic model for the time to distant metastatic relapse and its application to renal cell carcinoma

Author: Arturo Álvarez-Arenas, Wilfried Souleyreau, Andrea Emanuelli, Lindsay S. Cooley, Jean-Christophe Bernhard, Andreas Bikfalvi, Sebastien Benzekry, Modélisation Mathématique pour l'Oncologie (MONC), Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Institut Bergonié [Bordeaux], UNICANCER-UNICANCER-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire Angiogenèse et Micro-environnement des Cancers (LAMC), Université Sciences et Technologies - Bordeaux 1 (UB)-Institut National de la Santé et de la Recherche Médicale (INSERM), service d'urologie [CHU Bordeaux], CHU Bordeaux [Bordeaux], Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Centre de Recherche en Cancérologie de Marseille (CRCM)
Subjects: [STAT.AP]Statistics [stat]/Applications [stat.AP], Ecology, [SDV.CAN]Life Sciences [q-bio]/Cancer, Survival Analysis, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Kidney Neoplasms, Receptors, G-Protein-Coupled, Cellular and Molecular Neuroscience, Computational Theory and Mathematics, Modeling and Simulation, Genetics, [SDV.SP.PHARMA]Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, Humans, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Neoplasm Recurrence, Local, Carcinoma, Renal Cell, Molecular Biology, Ecology, Evolution, Behavior and Systematics, [PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis, Statistics and Probability [physics.data-an]
Abstract: Distant metastasis-free survival (DMFS) curves are widely used in oncology. They are classically analyzed using the Kaplan-Meier estimator or agnostic statistical models from survival analysis. Here we report on a method to extract more information from DMFS curves using a mathematical model of primary tumor growth and metastatic dissemination. The model depends on two parameters, α and μ, respectively quantifying tumor growth and dissemination. We assumed these to be lognormally distributed in a patient population. We propose a method for identification of the parameters of these distributions based on least-squares minimization between the data and the simulated survival curve. We studied the practical identifiability of these parameters and found that including the percentage of patients with metastasis at diagnosis was critical to ensure robust estimation. We also studied the impact and identifiability of covariates and their coefficients in α and μ, either categorical or continuous, including various functional forms for the latter (threshold, linear or a combination of both). We found that both the functional form and the coefficients could be determined from DMFS curves. We then applied our model to a clinical dataset of metastatic relapse from kidney cancer with individual data of 105 patients. We show that the model was able to describe the data and illustrate our method to disentangle the impact of three covariates on DMFS: a categorical one (Führman grade) and two continuous ones (gene expressions of the macrophage mannose receptor 1 (MMR) and the G Protein-Coupled Receptor Class C Group 5 Member A (GPRC5a) gene). We found that all had an influence in metastasis dissemination (μ), but not on growth (α).
Published: 2022

24. Revisiting metronomic vinorelbine with mathematical modelling: a Phase I trial in lung cancer

Author: Fabrice Barlesi, Laure Deyme, Diane-Charlotte Imbs, Elissa Cousin, Mathieu Barbolosi, Sylvanie Bonnet, Pascale Tomasini, Laurent Greillier, Melissa Galloux, Albane Testot-Ferry, Annick Pelletier, Nicolas André, Joseph Ciccolini, Dominique Barbolosi, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, and Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Mesothelioma, Cancer Research, Lung Neoplasms, Neutropenia, MESH: Neutropenia, [SDV]Life Sciences [q-bio], MESH: Vinblastine, Toxicology, Vinblastine, Carcinoma, Non-Small-Cell Lung, Antineoplastic Combined Chemotherapy Protocols, Humans, Pharmacology (medical), MESH: Vinorelbine, Metronomic, MESH: Models, Theoretical, Pharmacology, MESH: Humans, Mathematical modelling, Vinorelbine, Models, Theoretical, MESH: Lung Neoplasms, MESH: Antineoplastic Combined Chemotherapy Protocols, MESH: Administration, Metronomic, Oncology, Administration, Metronomic, Lung cancer, MESH: Carcinoma, Non-Small-Cell Lung
Abstract: A phase Ia/Ib trial of metronomic oral vinorelbine (MOV) driven by a mathematical model was performed in heavily pretreated metastatic Non-Small Cell Lung Cancer or Pleural Mesothelioma patients. Disease Control Rate, progression free survival, toxicity and PK/PD were the main endpoints.Best MOV scheduling was selected using a simplified phenomenological, semi-mechanistic model with a total weekly dose of 150-mg vinorelbine. Computation of individual PK parameters was performed using population approach.The mathematical model proposed the following metronomic schedule for a 150-mg weekly dose of vinorelbine: 60 mg D1, 30 mg D2, 60 mg D4. A total of 37 heavily pre-treated patients (30 evaluable) were enrolled. Grade III/IV neutropenia was observed in 30% patients. Median PFS was 11 weeks. Disease Control Rate was 73% (i.e.; 13% partial response and 60% stable disease). A large variability in drug exposure (AUCMOV was characterized by important variability in drug exposure among patients. However, and despite being all heavily pre-treated, 73% of disease control rate and 11 weeks PFS were achieved with manageable toxicities. PK/PD relationships yielded conflicting results depending on the initial tumor burden and BSA, suggesting that patients should be carefully selected prior to be scheduled for metronomic regimen. Possible role NLR could play as a predictive marker suggests immunomodulating features with MOV.
Published: 2022

25. Mechanistic modeling of metastatic relapse in early breast cancer to investigate the biological impact of prognostic biomarkers

Author: Célestin Bigarré, François Bertucci, Pascal Finetti, Gaëtan Macgrogan, Xavier Muracciole, Sébastien Benzekry, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratory of Predictive Oncology [Marseille], Centre de Recherche en Cancérologie de Marseille (CRCM), Département d’Oncologie Médicale [IPC, Marseille], Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC), Actions for OnCogenesis understanding and Target Identification in ONcology (ACTION), Institut Bergonié [Bordeaux], UNICANCER-UNICANCER-Université Bordeaux Segalen - Bordeaux 2-Institut National de la Santé et de la Recherche Médicale (INSERM), Département de Biopathologie (Institut Bergonié - CRLCC Bordeaux), UNICANCER-UNICANCER, Service de radiothérapie - [Hôpital de la Timone - Hôpital Nord - APHM], Hôpital de la Timone [CHU - APHM] (TIMONE)- Hôpital Nord [CHU - APHM], Inria-Inserm 'digital heath' Phd Grant, and BIGARRÉ, Célestin
Subjects: [STAT.AP]Statistics [stat]/Applications [stat.AP], Mechanistic modeling, Mixed-effect modeling, Health Informatics, NLME, [SDV.CAN]Life Sciences [q-bio]/Cancer, identifiability, Computer Science Applications, survival analysis, mechanistic modelling, Pai-1, distant metastasis free survival, [SDV.CAN] Life Sciences [q-bio]/Cancer, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Breast Cancer, cancer, metastasis, metastases, [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], Ki67, Software
Abstract: International audience; Estimating the risk of metastatic relapse is a major challenge to decide adjuvant treatment options in early-stage breast cancer (eBC). To date, distant metastasis-free survival (DMFS) analysis mainly relies on classical, agnostic, statistical models (e.g., Cox regression). Instead, we propose here to derive mechanistic models of DMFS.
Published: 2022

26. Exercise in lung Cancer, the healthcare providers opinion (E.C.H.O.): Results of the EORTC lung cancer Group (LCG) survey

Author: Sara Pilotto, Alice Avancini, Jessica Menis, Isabella Sperduti, Matteo Giaj Levra, Thierry Berghmans, Paolo Bironzo, Mariana Brandão, Dirk De Ruysscher, John Edwards, Corinne Faivre-Finn, Nicolas Girard, Laurent Greillier, Lizza Hendriks, Sylvie Lantuejoul, Murielle Mauer, Silvia Novello, Mary O'Brien, Martin Reck, Noemi Reguart, Jordi Remon, Jan von der Thüsen, Anne-Marie C. Dingemans, Benjamin Besse, Michele Milella, Centre Hospitalier Universitaire [Grenoble] (CHU), Institut Jules Bordet [Bruxelles], Faculté de Médecine [Bruxelles] (ULB), Université libre de Bruxelles (ULB)-Université libre de Bruxelles (ULB), Instituto de Ciências Biomédicas de Abel Salazar (ICBAS), Universidade do Porto = University of Porto, Maastricht University Medical Centre (MUMC), Maastricht University [Maastricht], Royal Holloway [University of London] (RHUL), University of Manchester [Manchester], Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Multidisciplinary Oncology and Therapeutic Innovations Unit, Hôpital Nord [CHU - APHM], Département d'hématologie [Gustave Roussy], Institut Gustave Roussy (IGR), School for Oncology and Developmental Biology [Maastricht] (GROW), Maastricht University [Maastricht]-Maastricht University Medical Centre (MUMC), Centre de Recherche en Cancérologie de Lyon (UNICANCER/CRCL), Centre Léon Bérard [Lyon]-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), European Organisation for Research and Treatment of Cancer [Bruxelles] (EORTC), European Cancer Organisation [Bruxelles] (ECCO), Università degli studi di Torino = University of Turin (UNITO), German Center for Lung Research, August Pi i Sunyer Biomedical Research Institute - IDIBAPS [Barcelona, Spain], Centro Integral Oncologico Clara Campal, RS: GROW - R3 - Innovative Cancer Diagnostics & Therapy, Radiotherapie, Pulmonologie, Pathology, and Pulmonary Medicine
Subjects: Pulmonary and Respiratory Medicine, REHABILITATION, Cancer Research, Lung Neoplasms, Facilitators, Clinicians, Health Personnel, [SDV.CAN]Life Sciences [q-bio]/Cancer, AMERICAN-COLLEGE, GUIDELINES, [SDV.MHEP.PSR]Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, MESH: Referral and Consultation, SDG 3 - Good Health and Well-being, QUALITY-OF-LIFE, Surveys and Questionnaires, Humans, Barriers, Current practice, Exercise, Lung cancer, Oncologist, Physical activity, Recommendation, Referral and Consultation, MESH: Surveys and Questionnaires, MEDICINE ROUND-TABLE, MESH: Humans, RANDOMIZED CONTROLLED-TRIAL, CHEMOTHERAPY, MESH: Lung Neoplasms, PHYSICAL-ACTIVITY, Oncology, MESH: Exercise, MESH: Health Personnel, INTERVENTION
Abstract: Objectives: Exercise has been reported to alleviate disease as well as treatment impact in patients with lung cancer. Nevertheless, there is limited information available regarding the perception of lung cancer dedicated healthcare professionals’ and their advice on exercise. Materials and Methods: An online survey exploring healthcare professionals’ practice patterns, perceptions, barriers, and facilitators of exercise in patients with lung cancer was conducted within members of the EORTC Lung Cancer Group (LCG). Results: One hundred forty-one healthcare providers completed the survey, mainly medical and radiation oncologists. Overall, 63% of the study participants declared that they frequently assessed exercise level in their patients, and 43% of them reinforced the importance of exercise. However, only 10% referred patients to an exercise program or specialist. Although the majority of the respondents had a positive perception regarding the benefits and safety of exercise (even in patients with advanced disease and/or bone metastasis), two-thirds of clinicians reported not having adequate training about exercise counselling. Moreover, 53% reported to lack of knowledge of guidelines referring to exercise in patients with cancer. Several obstacles and facilitators to improve exercise promotion in lung cancer care were identified. Conclusion: Healthcare providers recognize the relevance and feasibility of exercise as part of cancer treatment intervention, but specific pathways to do the referral are frequently missing. Future structured and well-designed strategies and initiatives are needed to support an effective referral in order to implement exercise interventions routinely in clinical practice.
Published: 2022

27. Acceptance, efficacy, and safety of COVID-19 vaccination in older patients with cancer

Author: Anne-Laure Couderc, Laetitia Ninove, Emilie Nouguerède, Dominique Rey, Marina Rebroin, Aurélie Daumas, Pascale Tomasini, Laurent Greillier, Sebastien Salas, Florence Duffaud, Laetitia Dahan, Muriel Duluc, Marie-Eve Garcia, Johan Pluvy, Solène Chaléat, Laure Farnault, Geoffroy Venton, Toscane Fourié, Elif Nurtop, Xavier de Lamballerie, Patrick Villani, Remi Charrel, Florian Correard, Anthropologie bio-culturelle, Droit, Ethique et Santé (ADES), Aix Marseille Université (AMU)-EFS ALPES MEDITERRANEE-Centre National de la Recherche Scientifique (CNRS), Assistance Publique - Hôpitaux de Marseille (APHM), Unité des Virus Emergents (UVE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Hospitalier Universitaire Méditerranée Infection (IHU Marseille), Unité de coordination en oncogériatrie (UCOG Paca ouest), Centre recherche en CardioVasculaire et Nutrition = Center for CardioVascular and Nutrition research (C2VN), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Multidisciplinary Oncology and Therapeutic Innovations Unit, Hôpital Nord [CHU - APHM], Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Aix Marseille Université (AMU), Service d’Oncologie Médicale [Hôpital de la Timone - APHM], Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE), Hôpital de la Timone [CHU - APHM] (TIMONE), AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), CHU Marseille, Theories and Approaches of Genomic Complexity (TAGC), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Assistance Publique - Hôpitaux de Marseille (APHM)-Hôpital de la Timone [CHU - APHM] (TIMONE)
Subjects: Male, COVID-19 Vaccines, Medical oncology, Second-line, Drug-related side effects and adverse reactions, MESH: Aged, 80 and over, Neoplasms, Humans, Lenvatinib, MESH: COVID-19, Thymic epithelial tumors, MESH: Neoplasms, MESH: BNT162 Vaccine, BNT162 Vaccine, Aged, Aged, 80 and over, MESH: Aged, Vaccines, MESH: Humans, Vaccination, COVID-19, MESH: Vaccination, Geriatric assessment, MESH: Male, MESH: Vaccines, Oncology, MESH: COVID-19 Vaccines, Female, Immunotherapy, Geriatrics and Gerontology, Pembrolizumab, MESH: Female, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract: The COVID-19 vaccination campaign began in December 2020, in France, and primarily targeted the oldest people. Our study aimed to determine the level of acceptance of vaccination in a population of older patients with cancer.From January 2021, we offered vaccination with the BNT162b2 COVID-19 vaccine to all patients 70 years and older referred to our geriatric oncology center in Marseille University Hospital (AP-HM) for geriatric assessment before initiation of an oncological treatment. Objectives were to evaluate acceptance rate of COVID-19 vaccination and to assess vaccine safety, reactogenicity, and efficacy two months after the first dose.Between January 18, 2021 and May 7, 2021, 150 older patients with cancer were offered vaccination after a geriatric assessment. The majority were men (61.3%), with a mean age of 81 years. The two most frequent primary tumors were digestive (29.4%) and thoracic (18%). The vaccine acceptance rate was 82.6% and the complete vaccination rate (2 doses) reached 75.3%. Among the vaccinated patients, 15.9% reported mild side effects after the first dose and 23.4% after the second dose, mostly arm pain and fatigue. COVID-19 cases were observed in 5.1% of vaccinated patients compared with 16.7% in unvaccinated patients. Of the 22 vaccinated patients who agreed to have their serum tested, 15 had antibodies against the spike protein at day 21 after the first dose.Our study showed a high acceptance rate of COVID-19 vaccination, with good tolerance in this frail population. These results highlight the benefits of organizing vaccination campaigns at the very beginning of oncological management in older patients.This study was registered May 23, 2019 in ClinicalTrials.gov (NCT03960593).
Published: 2022

28. Population pharmacokinetic model of irinotecan and its four main metabolites in patients treated with FOLFIRI or FOLFIRINOX regimen

Author: Florence Gattacceca, Alexandre Evrard, Marc Ychou, Laure Deyme, Dominique Barbolosi, Nicole Tubiana-Mathieu, Litaty Mbatchi, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Hôpital Universitaire Carémeau [Nîmes] (CHU Nîmes), Centre Hospitalier Universitaire de Nîmes (CHU Nîmes), CHU Limoges, Institut de Recherche en Cancérologie de Montpellier (IRCM - U1194 Inserm - UM), CRLCC Val d'Aurelle - Paul Lamarque-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), and GATTACCECA, Florence
Subjects: Male, 0301 basic medicine, Oncology, Cancer Research, FOLFIRINOX, Leucovorin, Toxicology, 0302 clinical medicine, CPT-11, Antineoplastic Combined Chemotherapy Protocols, Pharmacology (medical), Population pharmacokinetics, ComputingMilieux_MISCELLANEOUS, education.field_of_study, [SDV.SP]Life Sciences [q-bio]/Pharmaceutical sciences, [SDV.SP] Life Sciences [q-bio]/Pharmaceutical sciences, Oxaliplatin, 030220 oncology & carcinogenesis, FOLFIRI, Female, Fluorouracil, Folfirinox Regimen, Colorectal Neoplasms, medicine.drug, medicine.medical_specialty, Population, [SDV.CAN]Life Sciences [q-bio]/Cancer, Context (language use), Irinotecan, Nonlinear mixed effect modelling, 03 medical and health sciences, [SDV.CAN] Life Sciences [q-bio]/Cancer, Pharmacokinetics, Internal medicine, medicine, Humans, education, Pharmacology, business.industry, [SDV.MHEP.HEG]Life Sciences [q-bio]/Human health and pathology/Hépatology and Gastroenterology, stomatognathic diseases, 030104 developmental biology, [SDV.SP.PHARMA]Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, Camptothecin, Topoisomerase I Inhibitors, business
Abstract: International audience; PurposeThe aim of the present study was to characterize the pharmacokinetics of irinotecan and its four main metabolites (SN-38, SN-38G, APC and NPC) in metastatic colorectal cancer patients treated with FOLFIRI and FOLFIRINOX regimens and to quantify and explain the inter-individual pharmacokinetic variability in this context.MethodsA multicenter study including 109 metastatic colorectal cancer patients treated with FOLFIRI or FOLFIRINOX regimen, associated or not with a monoclonal antibody, was conducted. Concentrations of irinotecan and its four main metabolites were measured in 506 blood samples during the first cycle of treatment. Collected data were analyzed using the population approach. First, fixed and random effects models were selected using statistical and graphical methods; second, the impact of covariates on pharmacokinetic parameters was evaluated to explain the inter-individual variability in pharmacokinetic parameters.ResultsA seven-compartment model best described the pharmacokinetics of irinotecan and its four main metabolites. First-order rates were assigned to distribution, elimination, and metabolism processes, except for the transformation of irinotecan to NPC which was nonlinear. Addition of a direct conversion of NPC into SN-38 significantly improved the model. Co-administration of oxaliplatin significantly modified the distribution of SN-38.ConclusionTo our knowledge, the present model is the first to allow a simultaneous description of irinotecan pharmacokinetics and of its four main metabolites. Moreover, a direct conversion of NPC into SN-38 had never been described before in a population pharmacokinetic model of irinotecan. The model will be useful to develop pharmacokinetic-pharmacodynamic models relating SN-38 concentrations to efficacy and digestive toxicities.
Published: 2021

29. [Survey on HIV, HBV and HCV screening practices in cancerology, France]

Author: Marianne Veyri, Isabelle Poizot-Martin, Sylvie Bregigeon, Caroline Solas, Anne-Geneviève Marcelin, Myriam Taouqi, Michèle Pibarot, Alain Makinson, Jean-Philippe Spano, Sylvain Choquet, Plateforme Cancer et Fertilité ONCOPACA-Corse / CECOS [Hôpital La Conception - APHM], Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Hôpital Sainte-Marguerite [CHU - APHM] (Hôpitaux Sud ), Aix Marseille Université (AMU), Simulation and Modeling of Adaptive Response for Therapeutics in Cancer (SMARTc), Centre de Recherche en Cancérologie de Marseille (CRCM), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Aix Marseille Université (AMU), Hôpital de la Timone [CHU - APHM] (TIMONE), Infectious and Tropical Diseases Department [Montpellier], Institut de Recherche pour le Développement (IRD)-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Montpellier (UM), Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale (SESSTIM - U1252 INSERM - Aix Marseille Univ - UMR 259 IRD), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Malbec, Odile, Assistance Publique - Hôpitaux de Marseille (APHM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Recherches Translationnelles sur le VIH et les maladies infectieuses endémiques er émergentes (TransVIHMI), and Institut de Recherche pour le Développement (IRD)-Université de Yaoundé I-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM)
Subjects: 0301 basic medicine, Cancer Research, medicine.medical_specialty, VHB, [SDV]Life Sciences [q-bio], Human immunodeficiency virus (HIV), Hiv testing, VHC, medicine.disease_cause, Patient care, 03 medical and health sciences, 0302 clinical medicine, Regional cancer, HBV, medicine, Radiology, Nuclear Medicine and imaging, National level, Medical prescription, Cancer, business.industry, HIV, VIH, virus diseases, Hematology, General Medicine, medicine.disease, 3. Good health, [SDV] Life Sciences [q-bio], 030104 developmental biology, Dépistage, Oncology, 030220 oncology & carcinogenesis, Family medicine, HCV, Screening, business
Abstract: HIV testing is recommended at time of cancer diagnosis, HBV and HCV screening because of the risk of reactivation with certain anticancer drugs.This is a cross-sectional study. The objectives were to assess the screening practices in cancer patients and the satisfaction of professionals in the event of use of the CancerHIV network. A questionnaire drafted by the CancerHIV expert and the OncoPaca-Corse Regional Cancer Network (RCN) was distributed in the region at the end of 2018 (part 1: V1) before being extended to the national level via the CancerHIV network (part 2: V2). Participation reached 160 and 130 respondents (V1 and V2, respectively). At the initial cancer assessment, 23% of respondents declared that they systematically screened for HIV at V1 (V2: 17%), 25% for HBV (V2: 20%) and 24% for HCV (V2: 19%). Before immunotherapy, the rates were 54% for HIV in V1 (V2: 52%), 57% for HBV (V2: 60%) and 55% for HCV (V2: 57%). Among the respondents, satisfaction when requesting a regional or national remedy was high (almost 100%). Screening for HIV, HBV and HCV allows supervised prescription of immunosuppressive or cytotoxic treatment to a potentially immunosuppressed patient. This study, resulting of an original collaboration between a RCN and a national expert network, underlines the lack of screening at the 2 examined stages of patient care, and the need for raising practitioners' awareness to recommendations., Le dépistage de l’infection par le VIH est recommandé lors du bilan initial de tout cancer, celui de l’hépatite B et C en raison d’un risque de réactivation avec certains anticancéreux. Il s’agit d’une étude descriptive transversale. Les objectifs étaient d’évaluer les pratiques de dépistage chez des patients atteints de cancer et la satisfaction des professionnels en cas de recours au réseau CancerVIH. Un questionnaire élaboré par l’expert CancerVIH et le Réseau Régional de Cancérologie (RRC) OncoPaca-Corse a été diffusé fin 2018 en région (volet 1 : V1) avant une extension au niveau national via le réseau CancerVIH (volet 2 : V2). La participation a atteint 160 et 130 répondants (V1 et V2, respectivement). Au bilan initial de cancer, 23 % des répondants déclaraient dépister systématiquement le VIH au V1 (V2 : 17 %), 25 % le VHB (V2 : 20 %) et 24 % le VHC (V2 :19 %). Avant immunothérapie, les chiffres étaient de 54 % pour le VIH dans le V1 (V2 : 52 %), 57 % pour le VHB (V2 : 60 %) et 55 % pour le VHC (V2 : 57 %). Parmi les répondants, la satisfaction en cas de sollicitation du recours régional ou national était élevée (près de 100 %). Le dépistage du VIH, VHB et VHC permet la prescription encadrée d’un traitement immunosuppresseur ou cytotoxique à un patient potentiellement immunodéprimé. Cette enquête, fruit d’une collaboration originale entre RRC et réseau expert national, souligne l’insuffisance du dépistage aux 2 étapes de la prise en charge étudiées et la nécessité de sensibiliser les professionnels aux recommandations existantes.
Published: 2021

30. Supporting decision making and early prediction of survival for oncology drug development using a pharmacometrics-machine learning based model

Author: Benzekry, Sébastien, Karlsen, Mélanie, Elkaoutari, Abdessamad, Bruno, René, Neubert, Aleš, Mercier, François, Gomes, Bruno, Vatakuti, Suresh, Curle, Peter, Jamois, Candice, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Genentech/Roche [Marseille], Roche Pharma Research and Early Development [Basel] (pRED), and F. Hoffmann-La Roche [Basel]
Subjects: [STAT.AP]Statistics [stat]/Applications [stat.AP], [SDV.SP.PHARMA]Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, [SDV.CAN]Life Sciences [q-bio]/Cancer, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis, Statistics and Probability [physics.data-an]
Abstract: International audience
Published: 2022

31. 'Fortunately I felt pain, or I would have thought I was on my way out': experiencing pain and negotiating analgesic treatment in the context of cancer

Author: Léa Restivo, Éric Dudoit, Florence Duffaud, Sébastien Salas, Lionel Dany, Laboratoire de Psychologie Sociale (LPS), Aix Marseille Université (AMU), Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale (SESSTIM - U1252 INSERM - Aix Marseille Univ - UMR 259 IRD), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service d’Oncologie Médicale [Hôpital de la Timone - APHM], Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE), Marseille medical genetics - Centre de génétique médicale de Marseille (MMG), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Espace éthique méditerranéen, Hôpital de la Timone [CHU - APHM] (TIMONE), Anthropologie bio-culturelle, Droit, Ethique et Santé (ADES), and Aix Marseille Université (AMU)-EFS ALPES MEDITERRANEE-Centre National de la Recherche Scientifique (CNRS)
Subjects: Psychiatry and Mental health, experience, Oncology, representations, beliefs, pain, [SDV.CAN]Life Sciences [q-bio]/Cancer, coping strategies, Applied Psychology, analgesic treatments, Cancer
Abstract: International audience; Objectives: To explore cancer patients' experience of pain and coping strategies as well as beliefs and representations associated with pain, pain management and treatments.Method and participants: A qualitative study based on semi-structured interviews was conducted among 16 patients with cancer. The inductive research strategy adopted derived from the Grounded Theory approach and the data transcribed verbatim were gradually analyzed involving researcher triangulation.Findings: The experience of pain and the coping strategies developed by patients to deal with it are shaped by the experience and representations of cancer associated with death and suffering. Pain acts both as an indication to the patients that they are still alive and as an indicator of the progression of the disease. Cancer also models patients' relationships to analgesic treatments and health care providers, since pain is an area in which patients can take back control of what is happening to them. Patients' expression of reluctance to accept analgesic treatments is also influenced by the significance of opioid treatments in this context, which are perceived as an indication that the end of life is close.Conclusions: The contextualization of pain through the particularities of cancer is critical in order to understand cancer patients' experience of pain.Implications for psychosocial providers: Not only patients' knowledge but also the meaning-making of pain should be incorporated in interventions targeting pain management.
Published: 2022

32. Desmoid tumors located in the abdomen or associated with adenomatous polyposis: French intergroup clinical practice guidelines for diagnosis, treatment, and follow-up (SNFGE, FFCD, GERCOR, UNICANCER, SFCD, SFED, SFRO, ACHBT, SFR)

Author: Nicolas Benech, Sylvie Bonvalot, Armelle Dufresne, Afshin Gangi, Cécile Le Péchoux, Daniel Lopez-Trabada-Ataz, Alexandra Meurgey, Nayla Nicolas, Daniel Orbach, Nicolas Penel, Sébastien Salas, Jean-Christophe Saurin, Thomas Walter, Thierry Lecomte, Olivier Bouché, Centre de Recherche en Cancérologie de Lyon (UNICANCER/CRCL), Centre Léon Bérard [Lyon]-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Paris sciences et lettres (PSL), Centre Léon Bérard [Lyon], UNICANCER, Radiothérapie Moléculaire et Innovation Thérapeutique (RaMo-IT), Institut Gustave Roussy (IGR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Institut Gustave Roussy (IGR), Service de Pathologie [Centre Leon Berard], Service de pédiatrie, adolescents, jeunes adultes [Institut Curie], Institut Curie [Paris], Centre Régional de Lutte contre le Cancer Oscar Lambret [Lille] (UNICANCER/Lille), Université de Lille-UNICANCER, Service d’Oncologie Médicale [Hôpital de la Timone - APHM], Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE), Marseille medical genetics - Centre de génétique médicale de Marseille (MMG), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Hospices Civils de Lyon (HCL), Swiss Federal Research Station for Agroecology and Agriculture, CHU Trousseau [Tours], Centre Hospitalier Régional Universitaire de Tours (CHRU Tours), and Centre Hospitalier Universitaire de Reims (CHU Reims)
Subjects: Familial adenomatous polyposis, Soft tissue sarcoma, MESH: Combined Modality Therapy, MESH: Humans, Hepatology, Mesenchymal tumors, Gastroenterology, Desmoid tumors, [SDV.CAN]Life Sciences [q-bio]/Cancer, MESH: Follow-Up Studies, MESH: Abdomen, MESH: Prospective Studies, French clinical practice guidelines, MESH: Fibromatosis, Aggressive, Desmoid-type fibromatosis
Abstract: International audience; Introduction: Desmoid tumor (DT) of the abdomen is a challenging and rare disease. The level of evidence available to document their treatment is relatively low, however, recent publications of prospective studies have allowed to precise their management.Methods: This document is a summary of the French intergroup guidelines realized by all French medical and surgical societies involved in the management of DT located in the abdomen or associated with adenomatous polyposis. Recommendations are graded in four categories (A, B, C and D), according to the level of evidence found in the literature until January 2021.Results: When the diagnosis of DT is suspected a percutaneous biopsy should be performed when possible. A molecular analysis looking for pathogenic mutations of the CTNNB1 and APC genes should be systematically performed. When a somatic pathogenic variant of the APC gene is present, an intestinal polyposis should be searched. Due to a high rate of spontaneous regression, non-complicated DT should first benefit from an active surveillance with MRI within 2 months after diagnosis to assess the dynamic of tumor growth. The treatment decision must be discussed in an expert center, favoring the less toxic treatments which can include broad spectrum tyrosine kinase inhibitor or conventional chemotherapy (methotrexate-vinblastine). Surgery, outside the context of emergency, should only be considered for favorable location in an expert center.Conclusion: French guidelines for DT management were elaborated to help offering the best personalized therapeutic strategy in daily clinical practice as the DT therapeutic landscape is complexifying. Each individual case must be discussed within a multidisciplinary expert team.
Published: 2022

33. La Pharmacie Clinique en Oncologie

Author: Fanciullino, Raphaëlle, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Société Française des Pharmaciens Oncologues, and Ciccolini, Joseph
Subjects: [SDV] Life Sciences [q-bio], [SDV]Life Sciences [q-bio]
Abstract: National audience
Published: 2022

34. Monitoring of mAbs: is PK actionable?

Author: Ciccolini, Joseph, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), European Association for Clinical Pharmacology and Therapeutics, and Ciccolini, Joseph
Subjects: [SDV] Life Sciences [q-bio], [SDV]Life Sciences [q-bio]
Abstract: International audience
Published: 2022

35. Comprehensive biomarkers analysis to explain resistances to PD1-L1 ICIs: The precision immuno-oncology for advanced non-small cell lung cancer (PIONeeR) trial

Author: Greillier, Laurent, Monville, Florence, Leca, Vanina, Vely, Frédéric, Garcia, Stephane, Ciccolini, Joseph, Sabatier, Florence, Ferrani, Gilbert, Boudai, Nawel, Ghezali, Lamia, Landri, Marcellin, Marin, Clémence, Hamimed, Mourad, Arnaud, Laurent, Karlsen, Melanie, Atsou, Kevin, Bokobza, Sivan, Fleury, Pauline, Boyer, Arnaud, Audigier-Valette, Clarisse, Martinez, Stéphanie, Pegliasco, Hervé, Ray, Patrice, Falchero, Lionel, Serre, Antoine, Cloarec, Nicolas, Lebas, Louisiane, Hominal, Stephane, Barre, Patricia, Zahi, Sarah, Frikha, Ahmed, Bory, Pierre, Ray, Maryannick Le, Laborde, Lilian, Martin, Virginie, Malkoun, Richard, Roumieux, Marie, Mazieres, Julien, Perol, Maurice, Vivier, Eric, Benzekry, Sébastien, Fieschi, Jacques, Barlesi, Fabrice, Service d'oncologie multidisciplinaire innovations thérapeutiques [Hôpital Nord - APHM], Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital Nord [CHU - APHM], Veracyte SAS, Aix Marseille Université (AMU), Assistance Publique - Hôpitaux de Marseille (APHM), Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Innate Pharma, Hôpital Saint-Joseph [Marseille], Centre Hospitalier Intercommunal Toulon-La Seyne sur Mer - Hôpital Sainte-Musse, Centre Hospitalier d'Aix en Provence [Aix-en-Provence] (CHIAP ), Hôpital Européen [Fondation Ambroise Paré - Marseille], Centre Hospitalier Universitaire de Nîmes (CHU Nîmes), Hôpital Nord-Ouest de Villefranche-sur-Saône, Institut de Cancérologie du GARD ICG - CHU Nîmes (Instit Cancéro - GARD), Centre Hospitalier Henri Duffaut (Avignon), Centre Hospitalier du Val d'Ariège, Centre Hospitalier Annecy-Genevois [Saint-Julien-en-Genevois], Centre hospitalier Jean Rougier, Centre hospitalier de Montauban (CH Montauban), Polyclinique Maymard, Centre Hospitalier de Bastia, Partenaires INRAE, Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC), Hôpitaux de Toulouse, Centre Léon Bérard [Lyon], Institut Gustave Roussy (IGR), and Université Paris-Saclay
Subjects: [SDV.CAN]Life Sciences [q-bio]/Cancer, [SDV.IMM.IMM]Life Sciences [q-bio]/Immunology/Immunotherapy
Abstract: International audience; Abstract Background: Resistance to PD1/L1 immune checkpoint inhibitors (ICIs) in advanced NSCLC patients is observed in about 80% of individuals with no robust predictive biomarker yet. The PIONeeR trial (NCT03493581) aims to predict such resistances through a comprehensive multiparametric biomarkers analysis. Methodology: Among the >300 advanced NSCLC patients (pts) recruited in PIONeeR, we focused on the first 137 ≥2nd line ECOG PS0-1 pts treated with single-agent nivolumab, pembrolizumab or atezolizumab. Tumor tissue was collected at baseline and pts were re-biopsied at 6 weeks, and blood-sampled every cycle throughout the 24 weeks post C1D1. Response to PD1/L1 ICIs was assessed by RECIST 1.1 every 6 weeks. Immune contexture was characterized in tumor & blood of each pt through FACS for circulating immune cell subtypes quantification and endothelial activation, blood soluble factors dosage, dual- & multiplex IHC/digital pathology to quantify immune cells infiltrating the tumor, WES for TMB & ICI plasma dosage, leading to 331 measured biomarkers in addition to routine clinical parameters. Multivariable (MV) logistic regression was used to examine the association of each biomarker (controlled by sex, age, smoking status, histological type & PDL1+ Tumor Cells) with the risk of Early Progression (EP), i.e. within 3.5 months of treatment. Multivariable Cox regression analysis was conducted for association with PFS and OS. Results: Overall, the 137 pts were mainly male (64%), smokers (92%) and 1% PDL1+ TC in 36% of the cases, and 21% of pts were still on treatment at data cut-off. Archived samples were available for 80% of pts at inclusion and re-biopsy was available in 52.9% of these cases. The median follow up was 19.8 months, 22.5% of pts did not progress at data cut-off while 62% presented EP. Tumor Cytotoxic T-cells density, especially PD1+ were lower in EP (MV OR=0.45, p=0.022); conversely, higher proportions of circulating cytotoxic T-cells and activated T-cells (HLA-DR+) were observed in EP (MV OR=3.8, p65% inter-pt variability was observed in plasma exposures for all ICIs, with 8-10% of pts displaying trough levels below the target engagement threshold. Data will be presented through unsupervised clustering algorithms & multi-modal supervised learning methods. Changes after 6 weeks of treatment will be analyzed to further investigate drugs mechanisms of action. Conclusion: The PIONeeR trial provides with the 1st comprehensive biomarkers’ analysis to establish predictive models of resistance in advanced NSCLC pts treated with PD1/L1 ICIs and highlights how tumor and circulating biomarkers are complementary.
Published: 2022

36. A mechanistic model for prediction of metastatic relapse in early-stage breast cancer using routine clinical features

Author: Bigarré, Célestin, Finetti, Pascal, Bertucci, François, Muracciole, Xavier, Benzekry, Sébastien, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), Service de radiothérapie - [Hôpital de la Timone - Hôpital Nord - APHM], Hôpital de la Timone [CHU - APHM] (TIMONE)- Hôpital Nord [CHU - APHM], BIGARRÉ, Célestin, and Hôpital de la Timone [CHU - APHM] (TIMONE)-Hôpital Nord [CHU - APHM]
Subjects: mechanistic modelling, breast cancer, [STAT.ME] Statistics [stat]/Methodology [stat.ME], [SDV.CAN] Life Sciences [q-bio]/Cancer, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], metastasis-free survival, PAI-1, uPA, [SDV.CAN]Life Sciences [q-bio]/Cancer, [STAT.ME]Statistics [stat]/Methodology [stat.ME], [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], mathematical model
Abstract: International audience; Estimation of the risk of metastatic relapse is a major challenge to decide treatment options for early-stage breast cancer patients. To date, metastasis free survival (MFS) analysis mainly relies on classical - agnostic - statistical models (e.g., Cox regression). Instead, we propose to derive mechanistic models to predict MFS.The data consisted of patients who did not receive adjuvant systemic therapy from two databases: one (data 1, N = 163) with routine clinical features and the PAI-1 and uPA biomarkers and two (data 2, N = 692) with 11 routine clinical features. The mathematical models are based on a partial differential equation describing a size-structured population of metastases. They predict MFS from the size of the tumor at diagnosis and two mathematical parameters, α and μ describing respectively the tumor growth speed and metastatic dissemination potential. Using mixed-effects modeling, the population distributions of α and μ were assumed to be lognormal and to depend on routine clinical variables, whereas the observation error was assumed lognormal on the time-to-relapse. Variable selection consisted first in a univariate Wald test for all covariates with effect either on α or μ. We then used a backward elimination procedure. Significance of the covariates in the final model was assessed by a multivariable Wald test. Concordance indexes (c-index) were computed to assess the predictive power in cross-validation procedures as well as test sets.The model was implemented as an R package using optimized C++ code for the mechanistic part and enabling parallelization, resulting in a 4-fold reduction of the computing compared to a former python implementation. Nevertheless, over 4 hours are still needed to run a 100 samples bootstrap on a distributed computing cluster. The model selection procedure on data 1 revealed an association of PAI1 and age with μ, and of Estrogen receptor level with alpha, consistent with the established biological link between PAI-1 and tumor invasiveness. The resulting model achieved good prediction performances with a c-index of 0.72 in 5 folds cross-validation. Using only routine clinical markers, the algorithm on data 2 selected a model with the grade and Progesterone Receptors in α, Ki67 and node status in μ. These were able to adequately describe the data on calibration plots but performed poorly in prediction with a cross validated c-index of 0.60.Mechanistic modeling was able to unravel the biological and predictive role of PAI-1 but showed limited predictive power when using only on routine clinical features.
Published: 2022

37. Intensive end-of-life care in acute leukemia from a French national hospital database study (2017–2018)

Author: Sébastien, Salas, Vanessa, Pauly, Margaux, Damge, Veronica, Orleans, Guillaume, Fond, Régis, Costello, Laurent, Boyer, Karine, Baumstarck, Service d’Oncologie Médicale [Hôpital de la Timone - APHM], Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE), Marseille medical genetics - Centre de génétique médicale de Marseille (MMG), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre d'études et de recherche sur les services de santé et la qualité de vie (CEReSS), Aix Marseille Université (AMU), Aix-Marseille Université - École de médecine (AMU SMPM MED), Aix-Marseille Université - Faculté des sciences médicales et paramédicales (AMU SMPM), Aix Marseille Université (AMU)-Aix Marseille Université (AMU), Service de Santé Publique et d'Information Médicale (SSPIM), Assistance Publique - Hôpitaux de Marseille (APHM), and Theories and Approaches of Genomic Complexity (TAGC)
Subjects: Medical oncology, [SDV.CAN]Life Sciences [q-bio]/Cancer, Drug-related side effects and adverse reactions, Young Adult, MESH: Leukemia, Humans, Health services research, MESH: Neoplasms, Retrospective Studies, Aged, Terminal Care, Acute leukemia, Leukemia, MESH: Humans, MESH: Retrospective Studies, [SDV.MHEP.HEM]Life Sciences [q-bio]/Human health and pathology/Hematology, MESH: Vaccination, General Medicine, MESH: Hospitals, Hospitals, Geriatric assessment, MESH: Male, MESH: Vaccines, Registry database, MESH: Terminal Care, Hospice Care, End-of-life care, MESH: Hospice Care, MESH: Young Adult, Palliative care, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
Abstract: Background A better understanding of how the care of acute leukemia patients is managed in the last days of life would help clinicians and health policy makers improve the quality of end-of-life care. This study aimed: (i) to describe the intensity of end-of-life care among patients with acute leukemia who died in the hospital (2017–2018) and (ii) to identify the factors associated with the intensity of end-of-life care. Methods This was a retrospective cohort study of decedents based on data from the French national hospital database. The population included patients with acute leukemia who died during a hospital stay between 2017 and 2018, in a palliative care situation (code palliative care Z515 and-or being in a inpatient palliative care support bed during the 3 months preceding death). Intensity end-of-life care was assessed using two endpoints: High intensive end-of-life (HI-EOL: intensive care unit admission, emergency department admission, acute care hospitalization, intravenous chemotherapy) care and most invasive end-of-life (MI-EOL: orotracheal intubation, mechanical ventilation, artificial feeding, cardiopulmonary resuscitation, gastrostomy, or hemodialysis) care. Results A total of 3658 patients were included. In the last 30 days of life, 63 and 13% of the patients received HI-EOL care and MI-EOL care, respectively. Being younger, having comorbidities, being care managed in a specialized hospital, and a lower time in a palliative care structure were the main factors associated with HI-EOL. Conclusions A large majority of French young adults and adults with acute leukemia who died at the hospital experienced high intensity end-of-life care. Identification of factors associated with high-intensity end-of-life care, such as the access to palliative care and specialized cancer center care management, may help to improve end-of-life care quality.
Published: 2022

38. Abstract 1145: Therapeutic drug monitoring of Sunitinib in real-world patients

Author: Laurent Ferrer, Jonathan Chauvin, Dr Jean-Laurent Deville, Joseph Ciccolini, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and AACR
Subjects: Cancer Research, Oncology, [SDV]Life Sciences [q-bio]
Abstract: Therapeutic Drug Monitoring (TDM) with model-based adaptive dosing is expected to quickly ensure that exposure levels of anticancer agents are in the adequate range of plasma concentrations. Here, we have compared such TDM + in silico approach with empirical changes in dosing performed upon clinical signs in patients with metastatic renal cell carcinoma treated with Sunitinib. A total of 31 patients were monitored in our institute. All patients were treated with a standard starting dose of 50 mg QD following the 4/2 schedule. Sunitinib and n-desethyl sunitinib trough levels were assayed at steady state by a fully validated LC-MS/MS analysis. A PK-pop model with Bayesian estimate implemented on Monolix helped to identify individual PK parameters from a single time-point. Two different target exposures were considered (i.e., trough levels comprised between 50 and 100 ng/ml or 0-24h AUC comprised between 1250 and 2150 ng/ml.h). The PK model enabled to simulate both trough levels and 0-24h AUC from a single sample, regardless of the sampling time. Overall, dosing was modified empirically in about 54% of the patients after treatment started, mostly (46%) for reducing the dosing after that toxicities showed. Clinical benefit (i.e., stable disease + partial response + complete reponse) was achieved in 54% of patients but treatment discontinuation was observed in 58% of the patients eventually, mostly because of severe side-effects. A relationship between baseline exposure levels and early onset treatment-related toxicities was found. Because of the various changes in dosing, no such relationship was found between baseline exposure levels and efficacy evaluated at 3 months. TDM showed that only 45% of the patients were in the right window for trough levels (i.e., 50-100 ng/ml) and only 26% when considering AUC as the target exposure (i.e., 1200-2150 ng/ml.h). Consequently, the PK/PD model would have suggested to rapidly customize dosing in a much larger part of the patients (i.e., 84% with respect to the target AUCs). Importantly, Sunitinib dosing was empirically reduced only in 41% patients who displayed early-onset severe toxicities, whereas modelling would have immediately proposed to cut the dosing in more than 80% of those patients, thus suggesting that the safety of Sunitinib could have been improved when using our model. Although performed on a limited number of patients, this real-world study supports the hypothesis that TDM associated with PK modelling could help the prescriber to identify the best Sunitinib dosing in a quicker way than empirical change in dosing. Citation Format: Laurent Ferrer, Jonathan Chauvin, Dr Jean-Laurent Deville, Joseph Ciccolini. Therapeutic drug monitoring of Sunitinib in real-world patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1145.
Published: 2022

39. Mathematical modelling of immunotherapies associated with radiotherapyin the treatment of cancers

Author: Serre, Raphaël, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Aix-marseille université, Dominique Barbolosi, and serre, raphael
Subjects: inhibiteurs de checkpoint, [SDV]Life Sciences [q-bio], linear quadratic model, mathematical modeling, [MATH] Mathematics [math], immuno-radiotherapy, immunothérapie, radiation therapy, [SDV] Life Sciences [q-bio], immune checkpoint inhibitors, oncologie, oncology, modèle linéaire-quadratique, modélisation mathématique, immunotherapy, dose immunologique efficace, immunologically effective dose, [MATH]Mathematics [math], radiothérapie, radiotherapy
Abstract: Radiation therapy and immunotherapy are two fundamental modalities in anti-cancer therapeutic strategies: almost half of the patients are treated by radiation therapy at least once during their treatment, while the indications for immunotherapies have greatly progressed in recent years with the rapid development of immune checkpoint inhibitors and CAR T cells. These modalities have a strong potential for synergy in combination: animal experiments have shown that antigenic release induced by radiotherapy can potentiate the efficacy of immunotherapy. Numerous combination clinical trials are currently underway, some of which have been published recently. The clinical results are encouraging, but further progress is needed to specify the optimal modalities of administration of immuno-radiotherapy. In particular, the sequencing of the two modalities and the fractionation of the radiotherapy need to be clarified. In this thesis, we have provided answers by proposing a numerical modeling approach. Two mathematical models are presented, with the two corresponding papers, which address the issues of sequencing and fractionation for immuno-radiotherapy. The validity of the predictions of these models in the light of the most recent clinical data will be highlighted and discussed and their relevance will be highlighted. A detailed review of the available safety data for the combinations of radiotherapy with some of the most common immune checkpoint inhibitors has been performed: it is shown that tolerance and toxicity could be limiting factors in the widespread adoption of immuno-radiotherapy, as some recent clinical studies have shown an increased rate of toxicities. We hope that this theoretical advance will allow the design of radiotherapy regimens with excellent immunogenicity, without compromising radiocurability. Further studies will be needed to confirm these preliminary results in a larger number of patients and to integrate the toxicity data of immuno-radiotherapy., La radiothérapie et les immunothérapies sont deux modalités fondamentales dans les stratégies thérapeutiques anti cancéreuses: près de la moitié des patients est traitée par radiothérapie au moins une fois au cours de sa prise en charge, tandis que les indications des immunothérapies ont largement progressé depuis ces dernières années avec le développement rapide des inhibiteurs de checkpoint immunitaires mais aussi des CAR T cells. Ces modalités ont un fort potentiel de synergie en combinaison: des expériences animales ont montré que le relargage antigénique induit par la radiothérapie peut potentialiser l’efficacité de l’immunothérapie. De nombreux essais cliniques de combinaison sont actuellement en cours, quelques-uns ont été publiés récemment. Les résultats cliniques sont encourageants mais des avancées sont nécessaires pour préciser les modalités d’administration optimale de l’immuno-radiothérapie. En particulier, le séquencement des deux modalités et le fractionnement de la radiothérapie doivent être précisés. Dans cette thèse, nous avons apporté des réponses en proposant une approche de modélisation numérique. Deux modèles mathématiques sont présentés, avec les deux articles correspondants, qui adressent entre autres les questions du séquencement et du fractionnement pour l’immuno-radiothérapie. La validité des prédictions de ces modèles à la lumière des données cliniques les plus récentes sera discutée et leur pertinence sera soulignée et critiquée. Une revue détaillée des données de tolérance disponibles a été entreprise pour les combinaisons de radiothérapie avec les inhibiteurs de checkpoint les plus répandus actuellement: il est montré que la tolérance et les toxicités pourraient constituer un facteur limitant pour le développement de l’immuno-radiothérapie, alors que certains essais cliniques ont montré une augmentation des taux de toxicité. Nous espérons que cette avancée théorique permettra de concevoir des schémas de radiothérapie avec une excellente immunogénicité, sans compromis sur la radiocurabilité. Des études supplémentaires seront nécessaires pour confirmer ces résultats préliminaires sur un plus grand nombre de patients et pour intégrer les données de toxicité de l’immuno-radiothérapie.
Published: 2022

40. Combination of Trastuzumab, Pertuzumab, and Docetaxel in Patients With Advanced Non–Small-Cell Lung Cancer Harboring HER2 Mutations: Results From the IFCT-1703 R2D2 Trial

Author: Julien Mazieres, Claire Lafitte, Charles Ricordel, Laurent Greillier, Elodie Negre, Gérard Zalcman, Charlotte Domblides, Jeannick Madelaine, Jaafar Bennouna, Céline Mascaux, Denis Moro-Sibilot, François Pinquie, Alexis B. Cortot, Josiane Otto, Jacques Cadranel, Alexandra Langlais, Franck Morin, Virginie Westeel, Benjamin Besse, Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Services de Pneumologie, Exploration Fonctionnelle Respiratoire et Cardiologie (Hôpital Louis Pradel), Hospices Civils de Lyon (HCL), Oncogenesis, Stress, Signaling (OSS), Université de Rennes (UR)-CRLCC Eugène Marquis (CRLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM), CRLCC Eugène Marquis (CRLCC), Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Multidisciplinary Oncology and Therapeutic Innovations Unit, Hôpital Nord [CHU - APHM], Thèses d'exercice et mémoires - UFR de Médecine Montpellier-Nîmes, Université de Montpellier (UM), Service d’oncologie thoracique et essais précoces [CHU Bichat], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), CHU Bordeaux [Bordeaux], Immunology from Concept and Experiments to Translation (ImmunoConcept), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), Service de pneumologie [CHU Caen], Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Tumorothèque de Caen Basse-Normandie (TCBN), Hôpital Foch [Suresnes], Service de Pneumologie [Strasbourg], Université de Strasbourg (UNISTRA)-Nouvel Hôpital Civil, Hospices Civils de Strasbourg, CHU de Grenoble-Alpes, Université Côte d'Azur (UCA), Centre de Lutte contre le Cancer Antoine Lacassagne [Nice] (UNICANCER/CAL), UNICANCER-Université Côte d'Azur (UCA), Groupe de recherche clinique Biomarqueurs Théranostiques des Cancers Bronchiques Non à Petites Cellules (GRC 4 - Theranoscan), Sorbonne Université (SU), CHU Tenon [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Interactions hôte-greffon-tumeur, ingénierie cellulaire et génique - UFC (UMR INSERM 1098) (RIGHT), Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang [Bourgogne-Franche-Comté] (EFS BFC)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Institut Gustave Roussy (IGR), and Département de médecine oncologique [Gustave Roussy]
Subjects: MESH: Aged, MESH: Docetaxel, Cancer Research, MESH: Humans, MESH: Middle Aged, MESH: Mutation, MESH: Survival Rate, MESH: Non-Randomized Controlled Trials as Topic, MESH: Adult, [SDV.CAN]Life Sciences [q-bio]/Cancer, MESH: Follow-Up Studies, [SDV.MHEP.PSR]Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, MESH: Male, MESH: Prognosis, MESH: Lung Neoplasms, MESH: Receptor, ErbB-2, MESH: Antineoplastic Combined Chemotherapy Protocols, MESH: Aged, 80 and over, Oncology, MESH: Antibodies, Monoclonal, Humanized, MESH: Trastuzumab, MESH: Female, MESH: Carcinoma, Non-Small-Cell Lung
Abstract: PURPOSE HER2 exon 20 insertions and point mutations are oncogenic drivers found in 1%-2% of patients with non–small-cell lung cancer (NSCLC). No targeted therapy is approved for this subset of patients. We prospectively evaluated the effectiveness of the combination of two antibodies against human epidermal growth factor 2 (HER2 [HER2] trastuzumab and pertuzumab with docetaxel; trastuzumab and pertuzumab) and docetaxel. METHODS The IFCT 1703-R2D2 trial is a multicenter, nonrandomized phase II study. Patients with HER2-mutated, advanced NSCLC who progressed after ≥ 1 platinum-based treatment were enrolled. Patients received pertuzumab at a loading dose of 840 mg and 420 mg thereafter; trastuzumab at an 8 mg/kg loading dose and 6 mg/kg thereafter; and docetaxel at a dose of 75 mg/m2 every 3 weeks. The primary outcome was the objective response rate (ORR). Other end points included the duration of response, progression-free survival, and safety ( NCT03845270 ). RESULTS Forty-five patients were enrolled and treated. The median age was 64.5 years (range, 31-84 years), 35% were smokers, 72% were females, 15% had an Eastern Cooperative Oncology Group performance status of 2, and 30% had brain metastases. The objective response rate was 29% (n = 13), and 58% had stable disease (n = 26). The median progression-free survival was 6.8 months (95% CI, 4.0 to 8.5). The median duration of response in patients with a confirmed response (n = 13) was 11 months (95% CI, 2.9 to 14.9). Grade 3/4 treatment-related adverse events were observed in 64% of the patients. No patient discontinued treatment because of toxicity. The most frequent grade ≥ 3 treatment-related adverse events were neutropenia (33%), diarrhea (13%), and anemia (9%). CONCLUSION Triple therapy with trastuzumab, pertuzumab, and docetaxel is feasible and effective for HER2-mutated pretreated advanced NSCLC. These results highlight the effectiveness of the HER2 antibody-based strategy, which should be considered for these patients.
Published: 2022

41. A prospective behavioral and imaging study exploring the impact on long-term memory of radiotherapy delivered for a brain tumor in childhood and adolescence

Author: Jérémie Pariente, B. Lemesle, Anne Ducassou, Déborah Méligne, Dominique Barbolosi, Helene Gros-Dagnac, Lisa Pollidoro, Eloïse Baudou, Germain Arribarat, Jérémy Danna, Mathilde Cazaux, Patrice Péran, F. Tensaouti, Delphine Larrieu-Ciron, Anne Laprie, Yves Chaix, Anne-Isabelle Bertozzi, Annick Sevely, Marion Gambart, Jean-Pierre Desirat, Xavier Muracciole, Margaux Roques, Jessica Tallet, Toulouse Neuro Imaging Center (ToNIC), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Hôpital Purpan [Toulouse], CHU Toulouse [Toulouse]-CHU Toulouse [Toulouse], Service de Neurologie Pédiatrique [Toulouse], CHU Toulouse [Toulouse], CHU Toulouse, Departement de Neurologie, Département d'Oncologie Médicale [CHU Toulouse] (IUCT Oncopole - Institut Universitaire du Cancer), Centre hospitalier universitaire de Toulouse - CHU Toulouse-Institut Universitaire du Cancer de Toulouse - Oncopole (IUCT Oncopole - UMR 1037), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM), Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Institut Universitaire du Cancer de Toulouse - Oncopole (IUCT Oncopole - UMR 1037), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM), Simulation and Modeling of Adaptive Response for Therapeutics in Cancer (SMARTc), Centre de Recherche en Cancérologie de Marseille (CRCM), Laboratoire de Neurosciences Cognitives [Marseille] (LNC), and Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Pediatrics, resting-state functional magnetic resonance imaging, R895-920, NTCP, Procedural memory, SRTT, Medical physics. Medical radiology. Nuclear medicine, PFT, WISC, 0302 clinical medicine, Posterior fossa brain tumor, IQ, intellectual quotient, NTCP, normal tissue complication probability, normal tissue complication probability, intellectual quotient, serial reaction time task, Wechsler Adult Intelligence Scale, DFA, discriminating factor analysis, Semantic memory, Episodic memory, 3DT1, T1-weighted imaging, RC254-282, Spectroscopy, posterior fossa tumor, Long-term memory, CMS, pseudocontinuous arterial spin labeling, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Cognition, Executive functions, diffusion tensor imaging, 3. Good health, Oncology, DTI, 030220 oncology & carcinogenesis, TCP, rs-fMRI, resting-state functional magnetic resonance imaging, medicine.medical_specialty, WAIS, Wechsler Adult Intelligence Scale, PFT, posterior fossa tumor, Brain tumor, WAIS, pCASL, [SDV.CAN]Life Sciences [q-bio]/Cancer, MEM-III, Article, 03 medical and health sciences, Magnetic resonance imaging, Memory, medicine, Wechsler Memory Scale, Radiology, Nuclear Medicine and imaging, Wechsler Intelligence Scale for Children, Children's Memory Scale, SRTT, serial reaction time task, TCP, tumor control probability, Radiotherapy, Working memory, business.industry, discriminating factor analysis, CMS, Children's Memory Scale, medicine.disease, T1-weighted imaging, tumor control probability, DFA, nervous system, IQ, MEM-III, Wechsler Memory Scale, DTI, diffusion tensor imaging, business, 3DT1, 030217 neurology & neurosurgery, rs-fMRI, pCASL, pseudocontinuous arterial spin labeling, WISC, Wechsler Intelligence Scale for Children
Abstract: Highlights • Common long-term memory defects after pediatric brain tumor affect school achievement • The hippocampi, the cerebellum and cerebellar-cortical networks play a role in several memory systems. • This study will provide long-term neuropsychological data about four different memory systems. • We will investigate the correlations between neuropsychological, neuroimaging and radiotherapy dose data. • Imaging will be structural (3DT1), microstructural (DTI), functional (rs-fMRI), vascular (ASL) and metabolic (spectroscopy)., Background Posterior fossa tumors represent two thirds of brain tumors in children. Although progress in treatment has improved survival rates over the past few years, long-term memory impairments in survivors are frequent and have an impact on academic achievement. The hippocampi, cerebellum and cerebellar-cortical networks play a role in several memory systems. They are affected not only by the location of the tumor itself and its surgical removal, but also by the supratentorial effects of complementary treatments, particularly radiotherapy. The IMPALA study will investigate the impact of irradiation doses on brain structures involved in memory, especially the hippocampi and cerebellum. Methods/design In this single-center prospective behavioral and neuro-imaging study, 90 participants will be enrolled in three groups. The first two groups will include patients who underwent surgery for a posterior fossa brain tumor in childhood, who are considered to be cured, and who completed treatment at least 5 years earlier, either with radiotherapy (aggressive brain tumor; Group 1) or without (low-grade brain tumor; Group 2). Group 3 will include control participants matched with Group 1 for age, sex, and handedness. All participants will perform an extensive battery of neuropsychological tests, including an assessment of the main memory systems, and undergo multimodal 3 T MRI. The irradiation dose to the different brain structures involved in memory will be collected from the initial radiotherapy dosimetry. Discussion This study will provide long-term neuropsychological data about four different memory systems (working memory, episodic memory, semantic memory, and procedural memory) and the cognitive functions (attention, language, executive functions) that can interfere with them, in order to better characterize memory deficits among the survivors of brain tumors. We will investigate the correlations between neuropsychological and neuroimaging data on the structural (3DT1), microstructural (DTI), functional (rs-fMRI), vascular (ASL) and metabolic (spectroscopy) impact of the tumor and irradiation dose. This study will thus inform the setting of dose constraints to spare regions linked to the development of cognitive and memory functions. Trial registration ClinicalTrials.gov: NCT04324450, registered March 27, 2020, updated January 25th, 2021. Retrospectively registered, https://www.clinicaltrials.gov/ct2/show/NCT04324450.
Published: 2022

42. Macro-scale models for fluid flow in tumour tissues: impact of microstructure properties

Author: Cristina Vaghi, Sebastien Benzekry, Clair Poignard, Raphaelle Fanciullino, Modélisation Mathématique pour l'Oncologie (MONC), Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Institut Bergonié [Bordeaux], UNICANCER-UNICANCER-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Simulation and Modeling of Adaptive Response for Therapeutics in Cancer (SMARTc), Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Plan Cancer Numep NUMEP, Plan Cancer QUANTIC, Vaghi, Cristina, Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Institut Bergonié [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Paoli-Calmettes, and Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Aix Marseille Université (AMU)
Subjects: Materials science, [SDV.CAN]Life Sciences [q-bio]/Cancer, Models, Biological, 01 natural sciences, Imaging data, 03 medical and health sciences, Hydraulic conductivity, [SDV.CAN] Life Sciences [q-bio]/Cancer, Neoplasms, Interstitial tissue, Tumor Microenvironment, Fluid dynamics, Fluid flow in tumours, Humans, [MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP], 0101 mathematics, [MATH.MATH-AP] Mathematics [math]/Analysis of PDEs [math.AP], 030304 developmental biology, Interstitial fluid pressure, 0303 health sciences, Tumour microenvironment, Applied Mathematics, Biological Transport, Extracellular Fluid, Mechanics, Fluid transport, Microstructure, Agricultural and Biological Sciences (miscellaneous), Interstitial fluid flow, 010101 applied mathematics, Macroscopic scale, Modeling and Simulation, Two-scale homogenisation
Abstract: Understanding the dynamics underlying fluid transport in tumour tissues is of fundamental importance to assess processes of drug delivery. Here, we analyse the impact of the tumour microscopic properties on the macroscopic dynamics of vascular and interstitial fluid flow by using formal asymptotic techniques.Here, we obtained different macroscopic continuum models that couple vascular and interstitial flows. The homogenization technique allows us to derive two macroscale tissue models of fluid flow that take into account the microscopic structure of the vessels and the interstitial tissue. Different regimes were derived according to the magnitude of the vessel wall permeability and the interstitial hydraulic conductivity. Importantly, we provide an analysis of the properties of the models and show the link between them. Numerical simulations were eventually performed to test the models and to investigate the impact of the microstructure on the fluid transport.Future applications of our models include their calibration with real imaging data to investigate the impact of the tumour microenvironment on drug delivery.
Published: 2022

43. Multimodal phenotyping and new biomarkers for the development of innovating therapeutic strategies related to cardio-pulmonary diseases

Author: Boulate, David, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay, Françoise Le Pimpec-Barthes, and Boulate, David
Subjects: screening, dépistage, [SDV]Life Sciences [q-bio], angiophagy, biomarkers, fréquence cardiaque, [SDV] Life Sciences [q-bio], lung cancer, pulmonary hypertension, hypertension pulmonaire, cancer du poumon, angiophagie, biomarqueurs, hear rate
Published: 2022

44. Impact of pharmacogenetics on variability in exposure to oral vinorelbine among pediatric patients: a model-based population pharmacokinetic analysis

Author: Mourad Hamimed, Pierre Leblond, Aurélie Dumont, Florence Gattacceca, Emmanuelle Tresch-Bruneel, Alicia Probst, Pascal Chastagner, Anne Pagnier, Emilie De Carli, Natacha Entz-Werlé, Jacques Grill, Isabelle Aerts, Didier Frappaz, Anne-Isabelle Bertozzi-Salamon, Caroline Solas, Nicolas André, Joseph Ciccolini, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Simulation and Modeling of Adaptive Response for Therapeutics in Cancer (SMARTc), and Centre de Recherche en Cancérologie de Marseille (CRCM)
Subjects: Pharmacology, Cancer Research, MESH: Humans, MESH: Polymorphism, Single Nucleotide, [SDV]Life Sciences [q-bio], MESH: Models, Biological, MESH: Pharmacogenetics, ABCB1, Vinorelbine, P-glycoprotein, Toxicology, Models, Biological, Polymorphism, Single Nucleotide, Population pharmacokinetic analysis, Oncology, Pediatric drug development, Pharmacogenetics, MESH: Child, Humans, Pharmacology (medical), MESH: Vinorelbine, Neoplasm Recurrence, Local, Child, MESH: Neoplasm Recurrence, Local
Abstract: Better understanding of pharmacokinetics of oral vinorelbine (VNR) in children would help predicting drug exposure and, beyond, clinical outcome. Here, we have characterized the population pharmacokinetics of oral VNR and studied the factors likely to explain the variability observed in VNR exposure among young patients.We collected blood samples from 36 patients (mean age 11.6 years) of the OVIMA multicentric phase II study in children with recurrent/progressive low-grade glioma. Patients received 60 mg/mA three-compartment model, with a delayed double zero-order absorption and a first-order elimination, best described VNR pharmacokinetics in children. Typical population estimates for the apparent central volume of distribution (VBeyond canonical BSA and leukocytes, ABCB1-rs2032582 polymorphism showed a meaningful impact on VNR systemic exposure. Simulations showed that the identified covariates could have an impact on both efficacy and toxicity outcomes. Thus, a personalized dosing strategy, using those covariates, could help to optimize the efficacy/toxicity balance of VNR in children.
Published: 2022

45. Pharmacokinetic analysis and modelling to optimize radiolabeled-dendrimers biodistribution

Author: Ou, Jessica, Louis, Béatrice, Nail, Vincent, Balasse, Laure, Bouhlel, Ahlem, Chabert, Adrien, Roussel, Tom, Peng, Ling, Guillet, Benjamin, Garrigue, Philippe, Gattacceca, Florence, Ou, Jessica, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre recherche en CardioVasculaire et Nutrition = Center for CardioVascular and Nutrition research (C2VN), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre Européen de Recherche en Imagerie médicale (CERIMED), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-École Centrale de Marseille (ECM)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Centre National de la Recherche Scientifique (CNRS), Centre Interdisciplinaire de Nanoscience de Marseille (CINaM), and Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)
Subjects: [SDV] Life Sciences [q-bio], [SDV]Life Sciences [q-bio]
Abstract: International audience; Aim/Introduction: Nanosizing promotes the penetration of substances into solid tumors via the enhanced permeability and retention effect. Hence, CERIMED and CINaM teams designed a supramolecular [68Ga]Ga-radiolabeled self-assembling dendrimer (A) for tumor imaging. Dendrimer A was first optimized through chemical modifications to lower exposure of healthy organs, leading to 4 new dendrimer formulations (B,C,D,E). The best dendrimer was then selected and functionalized with RGD at different ratios, generating 2 other dendrimers (F,G). To understand the impact of structural modifications on the dendrimers biodistribution, a pharmacokinetic (PK) study was performed.Materials and Methods: Two-hour-long microPET/CT and gamma-counting biodistribution data of each radiolabeled dendrimer were collected from Swiss mice (n=6). Non-compartmental analysis (NCA) and population compartmental analysis (PopCA) were achieved respectively with PKanalix and Monolix softwares. NCA was used to describe exposure and main PK parameters in blood and organs for each formulation. PopCA was based on a semi-mechanistic model constituted of 10 compartments and allowed to evaluate the impact of dendrimer type on transfer rate constants between compartments.Results: Functionalization with RGD did not impact pharmacokinetics, and dendrimers F and G behaved similarly to dendrimer E. Dendrimer E displayed the lowest systemic exposure (area under concentration versus time curve (AUC) of 38 %ID/mL.h versus 71-138 %ID/mL.h), and consistently the highest clearance CL (2.66 mL/h versus 0.83-1.48 mL/h) which could be attributed to a more efficient renal elimination as suggested by bladder data. The volume of distribution (Vd) was also higher than for other dendrimers (8.00 mL versus 3.95-5.65 mL), suggesting a wider distribution in the organism, in line with the higher concentrations observed at the earliest time points in the main organs. AUCs in the main organs were contrarily lower for dendrimer E, due to a shorter terminal half-life (HL) in organs. Dendrimer E also displayed a short blood HL (2.21 h versus 1.99-4.36 h). The semi-mechanistic model confirmed that dendrimer E was less long retained in the liver compared to the other dendrimers, with higher liver elimination constants. Renal elimination constant was also higher for dendrimer E, confirming a better renal excretion.Conclusion: PK studies allowed the selection of an optimal dendrimer displaying the lowest exposure of healthy organs and the fastest clearance for future functionalization studies. PopCA provided a mechanistic understanding of the differences in PK behavior, which might be partly ascribed to a switch between renal and hepatic elimination. The semi-mechanistic model is also a first step toward the development of a physiologically-based pharmacokinetic model, which could be a useful tool to predict PK behavior of dendrimers depending on their chemical structure.
Published: 2022

46. Nutritional Factors during and after Cancer: Impacts on Survival and Quality of Life

Author: Sébastien Salas, Vanessa Cottet, Laure Dossus, Philippine Fassier, Julie Ginhac, Paule Latino-Martel, Isabelle Romieu, Stéphane Schneider, Bernard Srour, Marina Touillaud, Mathilde Touvier, Raphaëlle Ancellin, Nguyen Phuong, Linh, Réseau National Alimentation Cancer Recherche (réseau NACRe), Hôpital de la Timone [CHU - APHM] (TIMONE), Laboratoire d'Excellence : Lipoprotéines et Santé : prévention et Traitement des maladies Inflammatoires et du Cancer (LabEx LipSTIC), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut Gustave Roussy (IGR)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon)-Université de Bourgogne (UB)-Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon)-Centre Régional de Lutte contre le cancer Georges-François Leclerc [Dijon] (UNICANCER/CRLCC-CGFL), UNICANCER-UNICANCER-Institut National de la Santé et de la Recherche Médicale (INSERM)-Fédération Francophone de la Cancérologie Digestive, FFCD-Etablissement français du sang [Bourgogne-Franche-Comté] (EFS [Bourgogne-Franche-Comté])-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Dijon, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), Lipides - Nutrition - Cancer [Dijon - U1231] (LNC), Université de Bourgogne (UB)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Agro Dijon, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Centre d'Investigation Clinique 1432 (Dijon) - Epidemiologie Clinique/Essais Cliniques (CIC-EC), Université de Bourgogne (UB)-Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Dijon, Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Centre International de Recherche contre le Cancer - International Agency for Research on Cancer (CIRC - IARC), Organisation Mondiale de la Santé / World Health Organization Office (OMS / WHO), Institut Gustave Roussy (IGR), Equipe 3: EREN- Equipe de Recherche en Epidémiologie Nutritionnelle (CRESS - U1153), Université Sorbonne Paris Nord-Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), CHU Nice [Cimiez], Hôpital Cimiez [Nice] (CHU), Centre Léon Bérard [Lyon], Institut national du cancer [Boulogne] (INCA), Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and CHU Clermont-Ferrand
Subjects: obesity, Nutrition and Dietetics, MESH: Humans, MESH: Cancer, alcohol, Malnutrition, MESH: Quality of Life, [SDV.CAN]Life Sciences [q-bio]/Cancer, MESH: Nutrition Assessment, Kidney Neoplasms, dietary supplements, Nutrition Assessment, nutrition, [SDV.CAN] Life Sciences [q-bio]/Cancer, Neoplasms, Quality of Life, Humans, cancer, MESH: Neoplasms, MESH: Kidney Neoplasms, Colorectal Neoplasms, diet, MESH: Colorectal Neoplasms, MESH: Malnutrition, Food Science
Abstract: International audience; The French National Cancer Institute conducted a collective expertise study with researchers and clinical experts from the French Network for Nutrition And Cancer Research (NACRe Network). The objective was to update the state of knowledge on the impacts of nutritional factors on clinical endpoints during or after cancer. Data from 150 meta-analyses, pooled analyses or intervention trials and 93 cohort studies were examined; they concerned 8 nutritional factors, 6 clinical events and 20 cancer locations. This report shows that some nutritional factors have impacts on mortality and on the risks of recurrence or second primary cancer in cancer patients. Therefore, high-risk nutritional conditions can be encountered for certain cancer sites: from the diagnosis and throughout the health care pathways, weight loss (lung and esophageal cancers), malnutrition (lung, esophageal, colorectal, pancreatic, gastric and liver cancers), weight gain (colorectal, breast and kidney cancers) and alcohol consumption (upper aerodigestive cancers) should be monitored; and after cancer treatments, excess weight should be detected (colorectal, breast and kidney cancers). These situations require nutritional assessments, and even support or management by health care professionals, in the context of tertiary prevention. This report also highlights some limitations regarding the existing literature and some needs for future research.
Published: 2022

47. LC-MS/MS assay of mAbs in plasma: application in oncology

Author: Ciccolini, Joseph, Ciccolini, Joseph, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, and Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
Subjects: [SDV] Life Sciences [q-bio], [SDV]Life Sciences [q-bio]
Abstract: International audience
Published: 2022

48. Stratégies anti-BRAF anti-MEK dans le mélanome: aspects pharmacocinétiques et pharmacodynamiques

Author: Ciccolini, Joseph, Ciccolini, Joseph, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Pierre Fabre
Subjects: [SDV] Life Sciences [q-bio], [SDV.CAN] Life Sciences [q-bio]/Cancer, [SDV]Life Sciences [q-bio], [SDV.CAN]Life Sciences [q-bio]/Cancer
Abstract: National audience
Published: 2022

49. Functional status in older patients with cancer

Author: Dominique Rey, Bérengère Saliba-Serre, Laure Farnault, Anais Courcier, Anne-Laure Couderc, Geoffroy Venton, Fabrice Barlesi, Laurent Greillier, Patrick Villani, Florence Duffaud, Emilie Nouguerède, Robin Arcani, Aurélie Daumas, Pierre Suchon, Régis Costello, Sébastien Salas, Anthropologie bio-culturelle, Droit, Ethique et Santé (ADES), Aix Marseille Université (AMU)-EFS ALPES MEDITERRANEE-Centre National de la Recherche Scientifique (CNRS), Unité de coordination en oncogériatrie (UCOG Paca ouest), Assistance Publique - Hôpitaux de Marseille (APHM), Laboratoire d'hématologie biologique [Hôpital de la Timone - Hôpital Nord - APHM], Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Hôpital de la Timone [CHU - APHM] (TIMONE), Centre recherche en CardioVasculaire et Nutrition = Center for CardioVascular and Nutrition research (C2VN), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité de Coordination en Oncogériatrie [CHU de Dijon] (UCOGB), Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Aix Marseille Université (AMU), Service d’Oncologie Médicale [Hôpital de la Timone - APHM], Assistance Publique - Hôpitaux de Marseille (APHM)-Hôpital de la Timone [CHU - APHM] (TIMONE), Service d'oncologie multidisciplinaire innovations thérapeutiques [Hôpital Nord - APHM], Assistance Publique - Hôpitaux de Marseille (APHM)-Hôpital Nord [CHU - APHM], Institut Gustave Roussy (IGR), Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE), Hôpital de la Timone [CHU - APHM] (TIMONE)-Assistance Publique - Hôpitaux de Marseille (APHM), Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital Nord [CHU - APHM], Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Aix Marseille Université (AMU), and Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE)
Subjects: Male, medicine.medical_specialty, Activities of daily living, [SDV]Life Sciences [q-bio], Population, [SDV.CAN]Life Sciences [q-bio]/Cancer, Cancer management, Logistic regression, [SHS]Humanities and Social Sciences, Cohort Studies, Older patients, Neoplasms, Internal medicine, Activities of Daily Living, medicine, Humans, Stage (cooking), Mortality, Prospective cohort study, education, Geriatric Assessment, ComputingMilieux_MISCELLANEOUS, Aged, Aged, 80 and over, education.field_of_study, business.industry, [SDV.MHEP.GEG]Life Sciences [q-bio]/Human health and pathology/Geriatry and gerontology, Hazard ratio, Cancer, Functional status, medicine.disease, Unplanned hospitalization, Oncology, Geriatrics and Gerontology, business, human activities
Abstract: Background Functional Status (FS) is an important domain in Comprehensive Geriatric Assessment (CGA) and is most often evaluated using the Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL) scales separately. Method and objectives This secondary analysis of a previous prospective cohort study was conducted between September 2015 and May 2018 at Marseille University Hospital, France, on 613 cancer outpatients aged ≥70 years. The first objective of this study was to determine the prevalence of FS impairment in older outpatients with cancer using a combination of the information collected with the ADL and short IADL scales. Our second objective was to describe the potential impact of this combined FS on three-month unplanned hospitalizations and three-month mortality in this population. Results The median age was 81 years and 61.2% were men. The most common types of tumours were lung and thoracic (22.3%). Concerning FS, 255 patients (41.6%) had unimpaired ADL-IADL, 131 patients (21.4%) had IADL impairment, 38 patients (6.2%) had ADL impairment, and 189 patients (30.8%) had impaired ADL-IADL. In the multivariate Cox analysis, metastatic stage (adjusted Hazard Ratio (aHR) = 1.79; 95% CI [1.14–2.80]) and impaired ADL-IADL (aHR = 3.46; 95% CI [1.89–6.33]) were independently associated with three-month mortality. In the logistic regression model, impaired ADL-IADL (adjusted Odd ratio (aOR) = 3.64; 95% CI [1.84–7.20]) was the only factor independently associated with three-month unplanned hospitalizations. Interpretation The combined use of the ADL and IADL scales to evaluate functional status in older patients with cancer is of significant prognostic value regarding the risks of three-month unplanned hospitalizations and mortality.
Published: 2022

50. Quantitative impact of pre-analytical process on plasma uracil when testing for dihydropyrimidine dehydrogenase deficiency

Author: Maillard, Maud, Launay, Manon, Royer, Bernard, Guitton, Jérôme, Gautier-Veyret, Elodie, Broutin, Sophie, Tron, Camille, Le Louedec, Félicien, Ciccolini, Joseph, Richard, Damien, Alarcan, Hugo, Haufroid, Vincent, Tafzi, Naïma, Schmitt, Antonin, Etienne-Grimaldi, Marie-Christine, Narjoz, Céline, Thomas, Fabienne, Groupe de Pharmacologie Clinique Oncologique (GPCO), Centre de Recherches en Cancérologie de Toulouse (CRCT), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E), Interactions hôte-greffon-tumeur, ingénierie cellulaire et génique - UFC (UMR INSERM 1098) (RIGHT), Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang [Bourgogne-Franche-Comté] (EFS BFC)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Centre Hospitalier Lyon Sud [CHU - HCL] (CHLS), Hospices Civils de Lyon (HCL), Centre Hospitalier Universitaire [Grenoble] (CHU), Institut Gustave Roussy (IGR), Institut de recherche en santé, environnement et travail (Irset), Université d'Angers (UA)-Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), CHU Louise Michel [Clermont-Ferrand], CHU Clermont-Ferrand, Centre Hospitalier Régional Universitaire de Tours (CHRU Tours), Université Catholique de Louvain = Catholic University of Louvain (UCL), Ciblage individuel et prévention des risques de traitements immunosupresseurs et de la transplantation (IPPRITT), CHU Limoges-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM), Lipides - Nutrition - Cancer [Dijon - U1231] (LNC), Université de Bourgogne (UB)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Agro Dijon, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Centre de Lutte contre le Cancer Antoine Lacassagne [Nice] (UNICANCER/CAL), UNICANCER-Université Côte d'Azur (UCA), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), UCL - SSS/IREC/LTAP - Louvain Centre for Toxicology and Applied Pharmacology, UCL - (SLuc) Service de biochimie médicale, Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Cancérologie de Marseille (CRCM), and Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut Paoli-Calmettes
Subjects: Pharmacology, Dihydropyrimidine Dehydrogenase Deficiency, [SDV]Life Sciences [q-bio], dihydropyrimidine dehydrogenase, [SDV.CAN]Life Sciences [q-bio]/Cancer, Plasma, Phenotype, intra-individual variability, [SDV.SP.PHARMA]Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, Humans, Pharmacology (medical), uracil, Fluorouracil, pre-analytical practices, [SDV.BBM.BC]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biochemistry [q-bio.BM], dihydrouracil, Dihydrouracil Dehydrogenase (NADP)
Abstract: International audience; AIMS: Determining dihydropyrimidine dehydrogenase (DPD) activity by measuring patient’s uracil (U) plasma concentration is mandatory before fluoropyrimidines (FP) administration in France. In this study, we aimed to refine the pre-analytical recommendations for determining U and dihydrouracil (UH(2) ) concentrations, since they are essential in reliable DPD deficiency testing.METHODS: U and UH(2) concentrations were collected from 14 hospital laboratories. Stability in whole blood and plasma after centrifugation, the type of anticoagulant and long-term plasma storage were evaluated. The variation induced by time and temperature was calculated and compared to an acceptability range of ± 20%. Inter-occasion variability (IOV) of U and UH(2) was assessed in 573 patients double sampled for DPD-deficiency testing. RESULTS: Storage of blood samples before centrifugation at room temperature (RT) should not exceed 1 h, whereas cold (+4°C) storage maintains U stable after 5 hours. For patients correctly double sampled, IOV of U reached 22.4% for U (SD = 17.9%, range = [0-99%]). Notably, 17% of them were assigned with a different phenotype (normal or DPD deficient) based on the analysis of their two samples. For those having at least one non-compliant sample, this percentage increased up to 33.8%. The moment of blood collection did not affect the DPD phenotyping result.CONCLUSION: Caution should be taken when interpreting U concentrations if the time before centrifugation exceeds 1 h at RT, since it rises significantly afterwards. Not respecting the pre-analytical conditions for DPD phenotyping increases the risk of DPD status misclassification.
Published: 2022

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