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14 results on '"Multidisciplinary Oncology and Therapeutic Innovations Unit"'

1. 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
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2. 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

3. 1693P Incidence of NTRK genes fusion in adult brain tumours: A prospective cohort of 140 patients with cerebral gliomas and brain metastases

Author

Métellus, P., Camilla, C., Bialecki, E., Beaufils, N., Vellutini, C., Pellegrino, E., Tomasini, P., Nanni, I., Ouafik, L'Houcine, Institut de neurophysiopathologie (INP), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Department of Neurosurgery Hopital Privé Clairval Marseille, Hôpital Privé Clairval [Marseille], Service d'OncoBiologie, Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital Nord [CHU - APHM], Multidisciplinary Oncology and Therapeutic Innovations Unit, Hôpital Nord [CHU - APHM], 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), and Assistance Publique - Hôpitaux de Marseille (APHM)

Subjects
Oncology, [SDV]Life Sciences [q-bio], [SDV.CAN]Life Sciences [q-bio]/Cancer, Hematology
Abstract

International audience; Background: ImmTAC molecules are TCR-anti-CD3 bispecific fusion proteins that can redirect polyclonal T cell activation against cancer cells. Tebentafusp, a gp100-directed ImmTAC, has demonstrated survival benefit in metastatic uveal melanoma 1. Here, patient-derived tumour organoids (TO) 2 and 3-dimensional multicellular melanospheres were evaluated as tumour models to study ImmTAC activity. Methods: 3D melanospheres were generated by low adherence culture of melanoma cell lines (MEL202, MEL624, 92.1, MP-41, A375, IGR-1, Mewo) and their melanin synthesis genes were quantified by qPCR. The capacity of ImmTAC to redirect T cells against melanospheres was assessed in vitro using IFNg and granzyme B Elispots in the presence or absence of commercially sourced IFNa2 or IFNb. Patient derived TO were generated by Tempus 2 and screened for HLA-A*02:01 and antigen positivity. ImmTAC-mediated killing of relevant TO was assessed by 3D high content imaging. Results: Melanospheres formed from all melanoma cell lines tested, and upregulated melanin synthesis genes including PMEL, MITF, and MLANA. This translated into visible but heterogenous melanin expression. ImmTAC were capable of redirecting T cells against cells from melanospheres to produce IFNg (EC 50 23 pM-4.8 nM) and granzyme B (EC 50 130 pM-1.4 nM). Treatment of 3D cultures with IFNa2 or IFNb for 48 hours augmented ImmTAC-mediated redirection of IFNg secretion by a mean of 4.42-fold. To further assess ImmTAC-mediated T cell redirection against more complex in vitro cultures, TO were derived from patient tumours and co-cultured with PBMC for 96 hours. In these settings, clinically relevant doses of ImmTAC redirected T cells to induce cell lysis of antigen positive TO (EC 50 29.3 pM). Conclusions: 3D melanospheres and TO may provide useful models to study tumour biology, heterogeneity, and ImmTAC activity. ImmTAC were capable of redirecting T cells against these in vitro tumour models, which will allow for better understanding of mechanism of action. 1.

Published
2022
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4. 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
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5. 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
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6. 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
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7. 3MO - Comprehensive biomarkers (BMs) analysis to predict efficacy of PD1/L1 immune checkpoint inhibitors (ICIs) in combination with chemotherapy: a subgroup analysis of the Precision Immuno-Oncology for advanced Non-Small CEll Lung CancER (PIONeeR) trial

Author

Barlesi, Fabrice, Greillier, Laurent, Monville, Florence, Audigier-Valette, C, Martinez, S., Cloarec, N., van Hulst, Sylvie, Odier, L., Vely, Frédéric, Juquel, L., Arnaud, L., Bokobza, S., Hamimed, Mourad, Karlsen, Mélanie, Dufossé, Paul, Pouchin, Amélie, Ghezali, Lamia, Le Ray, Maryannick, Fieschi-Meric, J., Benzekry, Sébastien, Dufossé, Paul, 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), 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, Hôpital Nord [CHU - APHM], Veracyte SAS, Centre Hospitalier Intercommunal Toulon-La Seyne sur Mer - Hôpital Sainte-Musse, CH du Pays d'Aix, Aix-en-Provence, Centre Hospitalier Henri Duffaut (Avignon), Hôpital Universitaire Carémeau [Nîmes] (CHU Nîmes), Centre Hospitalier Universitaire de Nîmes (CHU Nîmes), Hôpital Nord-Ouest de Villefranche-sur-Saône [Gleize] (HNOVS), Centre d'Immunologie de Marseille - Luminy (CIML), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Anatomopathologie [Aix-Marseille], Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE), Hôpital de la Conception [CHU - APHM] (LA CONCEPTION), Innate Pharma, Aix-Marseille Université - Faculté de pharmacie (AMU PHARM), Aix Marseille Université (AMU), Assistance Publique - Hôpitaux de Marseille (APHM), and Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
Oncology, [SDV.CAN] Life Sciences [q-bio]/Cancer, Immunology and Allergy, [SDV.MHEP.PSR] Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, [SDV.CAN]Life Sciences [q-bio]/Cancer, [SDV.MHEP.PSR]Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract
Abstract

International audience

Published
2022

8. Comprehensive Genome Profiling in Patients With Metastatic Non-Small Cell Lung Cancer: The Precision Medicine Phase II Randomized SAFIR02-Lung Trial

Author

Boyault, Sandrine, Attignon, Valery, Soubeyran, Isabelle, Morel, Alain, Tran-Dien, Alicia, Jacquet, Alexandra, Dall'Olio, Filippo Gustavo, Jimenez, Marta, Soria, Jean-Charles, Besse, Benjamin, Barlesi, Fabrice, Tomasini, Pascale, Karimi, Maryam, Michiels, Stefan, Raimbourg, Judith, Daniel, Catherine, Janicot, Henri, Madroszyk, Anne, Audigier-Valette, Clarisse, Quoix, Elisabeth, Mazieres, Julien, Moro-Sibilot, Denis, Dansin, Eric, Molinier, Olivier, Morel, Hugues, Pichon, Eric, Cortot, Alexis, Otto, Josiane, Chomy, Francois, Souquet, Pierre-Jean, Cloarec, Nicolas, Giroux-Leprieur, Etienne, Bieche, Ivan, Lacroix, Ludovic, Fondation Synergie Lyon Cancer [Lyon], Centre Léon Bérard [Lyon], Institut Bergonié [Bordeaux], UNICANCER, Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM), Centre de Recherche en Cancérologie et Immunologie Intégrée Nantes-Angers (CRCI2NA ), Université d'Angers (UA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Nantes Université - UFR de Médecine et des Techniques Médicales (Nantes Univ - UFR MEDECINE), Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), Institut de Cancérologie de l'Ouest [Angers/Nantes] (UNICANCER/ICO), 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, 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), Département de médecine oncologique [Gustave Roussy], Institut Gustave Roussy (IGR), Imagine - Institut des maladies génétiques (IHU) (Imagine - U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), 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), Multidisciplinary Oncology and Therapeutic Innovations Unit, Hôpital Nord [CHU - APHM], Tarbiat Modares University [Tehran], 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, Institut Curie [Paris], Service de Pneumologie [CHU Clermont-Ferrand], Pôle RHEUNNIRS [CHU Clermont-Ferrand], CHU Gabriel Montpied [Clermont-Ferrand], CHU Clermont-Ferrand-CHU Clermont-Ferrand-CHU Gabriel Montpied [Clermont-Ferrand], CHU Clermont-Ferrand-CHU Clermont-Ferrand, Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC), Centre Hospitalier Intercommunal Toulon-La Seyne sur Mer - Hôpital Sainte-Musse, CHU Strasbourg, Service de pneumologie [Toulouse], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), CHU de Grenoble-Alpes, Centre Régional de Lutte contre le Cancer Oscar Lambret [Lille] (UNICANCER/Lille), Université de Lille-UNICANCER, Centre Hospitalier Le Mans (CH Le Mans), Intergroupe Francophone de Cancérologie Thoracique [Paris] (IFCT), Intergroupe Francophone de Cancérologie thoracique, Centre Hospitalier Régional d'Orléans (CHRO), Centre Hospitalier Régional Universitaire de Tours (CHRU Tours), Site de Recherche Intégrée en Cancérologie (SIRIC-ONCOLille), Université de Lille, Sciences et Technologies-Université de Lille, Sciences Humaines et Sociales-Centre Régional de Lutte contre le Cancer Oscar Lambret [Lille] (UNICANCER/Lille), Université de Lille-UNICANCER-Université de Lille-UNICANCER-Cancéropole Nord-Ouest-Université de Lille, Droit et Santé-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Université Côte d'Azur (UCA), Centre de Lutte contre le Cancer Antoine Lacassagne [Nice] (UNICANCER/CAL), UNICANCER-Université Côte d'Azur (UCA), Centre Hospitalier Lyon Sud [CHU - HCL] (CHLS), Hospices Civils de Lyon (HCL), Centre Hospitalier Henri Duffaut (Avignon), Biomarqueurs et essais cliniques en Cancérologie et Onco-Hématologie (BECCOH), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Saclay, and Département de biologie et pathologie médicales [Gustave Roussy]

Subjects
ErbB Receptors, Lung Neoplasms, Carcinoma, Non-Small-Cell Lung, [SDV]Life Sciences [q-bio], Antineoplastic Combined Chemotherapy Protocols, Mutation, Humans, Receptor Protein-Tyrosine Kinases, Precision Medicine, B7-H1 Antigen
Abstract

International audience; Purpose: Targeted therapies (TT) and immune checkpoint blockers (ICB) have revolutionized the approach to non-small cell lung cancer (NSCLC) treatment in the era of precision medicine. Their impact as switch maintenance therapy based on molecular characterization is unknown.Patients and Methods: SAFIR02-Lung was an open-label, randomized, phase II trial, involving 33 centers in France. We investigated eight TT (substudy-1) and one ICB (substudy-2), compared with standard-of-care as a maintenance strategy in patients with advanced EGFR, ALK wild-type (wt) NSCLC without progression after first-line chemotherapy, based on high-throughput genome analysis. The primary outcome was progression-free survival (PFS).Results: Among the 175 patients randomized in substudy-1, 116 received TT (selumetinib, vistusertib, capivasertib, AZD4547, AZD8931, vandetanib, olaparib, savolitinib) and 59 standard-of-care. Median PFS was 2.7 months [95% confidence interval (CI), 1.6-2.9] with TT versus 2.7 months (1.6-4.1) with standard-of-care (HR, 0.97; 95% CI, 0.7-1.36; P = 0.87). There were no significant differences in PFS within any molecular subgroup. In substudy-2, 183 patients were randomized, 121 received durvalumab and 62 standard-of-care. Median PFS was 3.0 months (2.3-4.4) with durvalumab versus 3.0 months (2.0-5.1) with standard-of-care (HR, 0.86; 95% CI, 0.62-1.20; P = 0.38). Preplanned subgroup analysis showed an enhanced benefit with durvalumab in patients with PD-L1 tumor proportion score (TPS) >= 1%, (n = 29; HR, 0.29; 95% CI, 0.11-0.75) as compared with PD-L1 < 1% (n = 31; HR, 0.71; 95% CI, 0.31-1.60; P-interaction = 0.036). Conclusions: Molecular profiling can feasibly be implemented to guide treatment choice for the maintenance strategy in EGFR/ALK wt NSCLC; in this study it did not lead to substantial treatment benefits beyond durvalumab for PD-L1 >= 1 patients.

Published
2022
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9. Machine Learning for Prediction of Immunotherapy Efficacy in Non-Small Cell Lung Cancer from Simple Clinical and Biological Data

Author

Fabrice Barlesi, Laurent Greillier, Melanie Karlsen, Pascale Tomasini, M. Grangeon, S. Chaleat, Sebastien Benzekry, Maria Alexa, Dominique Barbolosi, Isabella Bicalho-Frazeto, 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), Assistance Publique - Hôpitaux de Marseille (APHM), Institut Gustave Roussy (IGR), Aix Marseille Université (AMU), Centre de Recherche en Cancérologie de Marseille (CRCM), Benzekry, Sebastien, 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), Multidisciplinary Oncology and Therapeutic Innovations Unit, and Hôpital Nord [CHU - APHM]

Subjects
Cancer Research, Survival, Immune checkpoint inhibitors, medicine.medical_treatment, [SDV.CAN]Life Sciences [q-bio]/Cancer, Machine learning, computer.software_genre, Blood counts, Article, 03 medical and health sciences, Second line, 0302 clinical medicine, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [SDV.CAN] Life Sciences [q-bio]/Cancer, [STAT.AP] Statistics [stat]/Applications [stat.AP], blood counts, lung cancer, response, survival, prediction, machine learning, Medicine, Progression-free survival, Lung cancer, RC254-282, 030304 developmental biology, Biological data, 0303 health sciences, [STAT.AP]Statistics [stat]/Applications [stat.AP], Performance status, business.industry, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Response, Immunotherapy, medicine.disease, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, 3. Good health, Oncology, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [SDV.SP.PHARMA] Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, 030220 oncology & carcinogenesis, [SDV.SP.PHARMA]Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Artificial intelligence, Non small cell, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, business, Prediction, computer, [PHYS.PHYS.PHYS-DATA-AN] Physics [physics]/Physics [physics]/Data Analysis, Statistics and Probability [physics.data-an], [PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis, Statistics and Probability [physics.data-an]
Abstract

BackgroundImmune checkpoint inhibitors (ICIs) are now a therapeutic standard in advanced non-small cell lung cancer (NSCLC), but strong predictive markers for ICIs efficacy are still lacking. We evaluated machine learning models built on simple clinical and biological data to individually predict response to ICIs.MethodsPatients with metastatic NSCLC who received ICI in second line or later were included. We collected clinical and hematological data and studied the association of this data with disease control rate (DCR), progression free survival (PFS) and overall survival (OS). Multiple machine learning (ML) algorithms were assessed for their ability to predict response.ResultsOverall, 298 patients were enrolled. The overall response rate and DCR were 15.3 % and 53%, respectively. Median PFS and OS were 3.3 and 11.4 months, respectively. In multivariable analysis, DCR was significantly associated with performance status (PS) and hemoglobin level (OR 0.58, pConclusionCombination of simple clinical and biological data could accurately predict disease control rate at the individual level.Highlights-Machine learning applied to a large set of NSCLC patients could predict efficacy of immunotherapy with a 69% accuracy using simple routine data-Hemoglobin levels and performance status were the strongest predictors and significantly associated with DCR, PFS and OS-Neutrophils-to-lymphocyte ratio was also associated with outcome-Benchmark of 8 machine learning models

Published
2021
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10. Cardiovascular monitoring and management in cancer patients: a french national survey

Author

Jovenaux, L., Cautela, J., Thuny, F., Paganelli, F., Barlesi, F., COMBE, Isabelle, Unité de Recherche sur les Maladies Infectieuses et Tropicales Emergentes (URMITE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR48, INSB-INSB-Centre National de la Recherche Scientifique (CNRS), American Public University System (APUS), Assistance Publique - Hôpitaux de Marseille (APHM), Multidisciplinary Oncology and Therapeutic Innovations Unit, Hôpital Nord [CHU - APHM], and Institut des sciences biologiques (INSB-CNRS)-Institut des sciences biologiques (INSB-CNRS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, [SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases, ComputingMilieux_MISCELLANEOUS
Abstract

International audience; no abstract

Published
2017

11. Oncogenic drivers in daily practice improve overall survival in patients ă with lung adenocarcinoma

Author

Fournier, Clarisse, Greillier, L., Fina, F., Secq, V., Nanni-Metellus, I., Loundou, A., Garcia, S., Ouafik, L., Tomasini, P., Barlesi, F., Santé Publique et maladies Chroniques : Qualité de vie Concepts, Usages et Limites, Déterminants (SPMC), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM), Service d'oncologie multidisciplinaire innovations thérapeutiques [Hôpital Nord - APHM], Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital Nord [CHU - APHM], Assistance Publique - Hôpitaux de Marseille (APHM), Multidisciplinary Oncology and Therapeutic Innovations Unit, Hôpital Nord [CHU - APHM], and Assistance Publique - Hôpitaux de Marseille (APHM)-Aix Marseille Université (AMU)

Subjects
quality, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, [SHS.PSY]Humanities and Social Sciences/Psychology, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [SHS.ECO]Humanities and Social Sciences/Economics and Finance
Abstract

International audience; Background. - EGFR tyrosine kinase inhibitors and crizotinib are ă nowadays the optimal treatment for metastatic lung cancer with ă activation of EGFR mutations and ALK rearrangement. In addition, several ă targeted agents are in development for lung cancer with other ă oncodrivers. In France, since 2011, six oncodrivers are routinely tested ă in patients with stage IV. The aim of this study was to assess whether ă systematic detection of oncodrivers and matched targeted therapy improve ă overall survival in patients with advanced lung adenocarcinoma. ă Methods. - This study included all consecutive patients treated in our ă department for advanced lung adenocarcinoma from January 2012 to ă December 2013. We studied the impact in survival according to the ă presence of the driver and the targeted therapy. ă Results. - Among the 261 patients included, oncodrivers alterations were ă found in 43.5% of patients: EML4-ALK fusion genes (2.1%), EGFR ă (10.3%), KRAS (27.7%), BRAF (2.5%), HER2 (0.8%), and PI3KCA (0.8%) ă mutations. Twenty-nine percent of patients (n = 32) with oncodrivers ă received matched targeted therapy. Patient treated by targeted agent ă appropriate to an oncogenic driver had a median survival of 21.1 months ă (95% CI: 14.7-27.5). The patients (n=79) who did not receive targeted ă therapy had a median survival of 6.6 months (95% CI: 4.3-8.9). The ă patients (n = 150) without identified driver had a median survival of ă 9.7 months (95% CI: 6.7-11.7); P < 0.001. ă Conclusion. - An actionable oncodriver was routinely detected in nearly ă half of patients with advanced lung adenocarcinoma. This systematic ă detection may influence treatment outcomes, notably with matched ă targeted therapy. (C) 2016 SPLF. Published by Elsevier Masson SAS. All ă rights reserved.

Published
2016
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12. High Serum Vitamin B12 Levels Associated with C-Reactive Protein in Older Patients with Cancer.

Author

Couderc AL, Puchades E, Villani P, Arcani R, Farnault L, Daumas A, Courcier A, Greillier L, Barlesi F, Duffaud F, Salas S, Costello R, Gentile G, Pradel V, Suchon P, and Venton G

Subjects
Activities of Daily Living, Aged, Aged, 80 and over, Geriatric Assessment, Hospitalization, Humans, Vitamin B 12, C-Reactive Protein, Neoplasms
Abstract

Background: A Comprehensive Geriatric Assessment (CGA) has been proposed to assess prognosis and to adapt oncological care in older patients with cancer. However, few biological markers are incorporated in the CGA., Methods: This comparative study on older patients with cancer was realized before final therapeutic decision and during a CGA that included biological markers. Our objective study was to know if the serum vitamin B12-C-reactive protein index (BCI) can help to estimate early death and unplanned hospitalization. Associations between BCI and unplanned hospitalization or mortality were analyzed using ordered multivariate logistic regression., Findings: We included 621 older cancer adults in outpatient care with a median age of 81 years (range, 70-98 years) from September 2015 to May 2018. In this study, 5.6% of patients died within 3 months, 8.8% had unplanned hospitalization within 1 month, and 11.4% had unplanned hospitalization within 3 months. Hypercobalaminemia was present in 83 patients (13.4%), and 34 patients (5.5%) had BCI >40,000. According to the multivariate analysis, BCI was a prognostic factor of mortality within 3 months and unplanned hospitalizations at 1 and 3 months. Impaired activities of daily living (ADL) and palliative care were also risk factors for mortality within 3 months. Impaired instrumental ADL, low albumin level, and palliative care were risk factors for unplanned hospitalization at 1 month., Interpretation: BCI could be routinely added to the CGA process, as part of a pretreatment workup, in order to assess more precisely the frailties and to adapt oncological care in older patients treated for cancer., Implications for Practice: Aging comes with an increase of frailties and comorbidities. To identify frailties in older patients with cancer, this study used a Comprehensive Geriatric Assessment, which allowed for the adaptation of each treatment plan in accordance with the individual needs of the patients. However, biological characteristics were not included in this assessment. This study showed that hypercobalaminemia and vitamin B12 -C-reactive protein index may be potential markers for cancer with poor prognosis, particularly in the older population. These biological markers can be used in geriatric oncology and general medicine., (© 2020 AlphaMed Press.)

Published
2020
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13. Medication Reconciliation Associated with Comprehensive Geriatric Assessment in Older Patients with Cancer: ChimioAge Study.

Author

Couderc AL, Boisseranc C, Rey D, Nouguerede E, Greillier L, Barlesi F, Duffaud F, Deville JL, Honoré S, Villani P, and Correard F

Subjects
Aged, Aged, 80 and over, Female, Humans, Male, Medical Oncology methods, Patient Care Planning, Prospective Studies, Clinical Decision-Making methods, Geriatric Assessment methods, Medication Reconciliation methods, Neoplasms therapy, Polypharmacy
Abstract

Background: Polymorbidity induces polypharmacy in older patients may lead to potential drug-drug interactions (DDI) which can modify the tolerance and safety of oncological treatments and alter the intended therapeutic effect. The objective of our study was to describe the decision-making process for oncological treatment and related outcomes, in a population of older adults undergoing a comprehensive geriatric assessment (CGA) associated to a comprehensive medication reconciliation (CMR) prior to initiating oncological treatment., Methods: ChimioAge is a prospective observational study conducted between 01/2017 and 07/2018 at Marseille University Hospital and approved by the French National Ethics Committee. It comprised all consecutive patients aged 70 years and over who were referred for a CGA as part of CMR, before initiating systemic treatment., Results: One hundred and seventy-one cancer patients were included. Mean age was 79.2 years, over half had metastatic cancers, 75% had an ECOG performance status zero or one, and two-thirds were independent in daily activities. Two-thirds of the patients had polypharmacy and the CMR identified potential DDI with systemic treatment in 43.3% of patients. Following the CGA, the CMR and the hospital oncologists decision, 30% of the patients received adapted systemic treatment with reduced doses at initiation. They presented fewer toxicities - irrespective of grade and type - than patients who received standard treatment (p<0.001) and had comparable overall survival (Log rank p=0.21)., Conclusion: This is one of the first studies to highlight the value in conducting CMR and a CGA simultaneously before initiating systemic treatment in older patients with cancer. These two evaluations could give oncologists decisive information to personalize cancer treatment of older patients and optimize treatment dose to offer the best efficacy and minimize toxicity., Competing Interests: Laurent Greillier reports personal fees and non-financial support from ABBVIE, ASTRA-ZENECA, BOEHRINGER INGELHEIM, BMS, MSD, and ROCHE and personal fees from TAKEDA, outside the submitted work. The authors report no other potential conflicts of interest for this work., (© 2020 Couderc et al.)

Published
2020
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14. Improving efficacy of the combination between antiangiogenic and chemotherapy: Time for mathematical modeling support.

Author

Ciccolini J, Benzekry S, Lacarelle B, Barbolosi D, and Barlési F

Subjects
Female, Humans, Male, Angiogenesis Inhibitors therapeutic use, Antibodies, Monoclonal, Humanized therapeutic use, Antineoplastic Combined Chemotherapy Protocols therapeutic use, Carcinoma, Non-Small-Cell Lung drug therapy, Lung Neoplasms drug therapy, Neovascularization, Pathologic drug therapy, Vascular Endothelial Growth Factor A antagonists & inhibitors
Published
2015
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