Search

Halil Yildiz,1,&ast; Diego Castanares-Zapatero,2,&ast; Guillaume Pierman,1 Lucie Pothen,1 Julien De Greef,1 Frank Aboubakar Nana,3 Hector Rodriguez-Villalobos,4 Leila Belkhir,1 Jean Cyr Yombi1 1Department of Internal Medicine and Infectious Diseases, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain (UCLouvain), Brussels, Belgium; 2Department of Intensive Care Unit, Cliniques Universitaires Saint-Luc, UCLouvain, Brussels, Belgium; 3Department of Pneumology, Cliniques Universitaires Saint-Luc, UCLouvain, Brussels, Belgium; 4Department of Microbiology, Cliniques Universitaires Saint-Luc, UCLouvain, Brussels, Belgium&ast;These authors contributed equally to this workCorrespondence: Halil YildizDepartment of Internal Medicine and Infectious Diseases, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, 10 avenue hippocrate, Brussels, BelgiumTel +3227641902Fax +3227641046Email halil.yildiz@uclouvain.beIntroduction: The neutrophil-to-lymphocyte ratio (NLR) could be a predictive factor of severe COVID-19. However, most relevant studies are retrospective, and the optimal NLR cut-off point has not been determined. The objective of our research was identification and validation of the best NLR cut-off value on admission that could predict high in-hospital mortality in COVID-19 patients.Methods: Medical files of all patients admitted for COVID-19 pneumonia in our dedicated COVID-units between March and April 2020 (derivation cohort) and between October and December 2020 (validation cohort) were reviewed.Results: Two hundred ninety-nine patients were included in the study (198 in the derivation and 101 in the validation cohort, respectively). Youden’s J statistic in the derivation cohort determined the optimal cut-off value for the performance of NLR at admission to predict mortality in hospitalized patients with COVID-19. The NLR cut-off value of 5.94 had a sensitivity of 62% and specificity of 64%. In ROC curve analysis, the AUC was 0.665 [95% CI 0.530– 0.801, p= 0.025]. In the validation cohort, the best predictive cut-off value of NLR was 6.4, which corresponded to a sensitivity of 63% and a specificity of 64% with AUC 0.766 [95% CI 0.651– 0.881, p < 0.001]. When the NLR cut-off value of 5.94 was applied in the validation cohort, there was no significant difference in death and survival in comparison with the derivation NLR cut-off. Net reclassification improvement (NRI) analysis showed no significant classification change in outcome between both NLR cut-off values (NRI:0.012, p=0.31).Conclusion: In prospective analysis, an NLR value of 5.94 predicted high in-hospital mortality upon admission in patients hospitalized for COVID-19 pneumonia.Keywords: neutrophil-to-lymphocyte ratio, coronavirus disease, SARS-CoV-2 infection, COVID-19, risk factors, laboratory markers

Local delivery of mRNA-based immunotherapy offers a promising avenue as it enables the production of specific immunomodulatory proteins that can stimulate the immune system to recognize and eliminate cancer cells while limiting systemic exposure and toxicities. Here, we develop and employ lipid-based nanoparticles (LNPs) to intratumorally deliver an mRNA mixture encoding the cytokines interleukin (IL)-21 and IL-7 and the immunostimulatory molecule 4-1BB ligand (Triplet LNP). IL-21 synergy with IL-7 and 4-1BBL leads to a profound increase in the frequency of tumor-infiltrating CD8 + T cells and their capacity to produce granzyme B and IFN-γ, leading to tumor eradication and the development of long-term immunological memory. Mechanistically, the efficacy of the Triplet LNP depends on tumor-draining lymph nodes to tumor CD8 + T-cell trafficking. Moreover, we highlight the therapeutic potential of the Triplet LNP in multiple tumor models in female mice and its superior therapeutic efficacy to immune checkpoint blockade. Ultimately, the expression of these immunomodulators is associated with better overall survival in patients with cancer., Competing Interests: Competing interests: J.F., E.B., S.D.K., and F.L. are employees of etherna. J.F., E.B., S.D.K., and F.L. have applied for a patent related to the study (Compositions and methods for delivery of agents to immune cells; WO2023118411A1). S.D.K. and B.G.D.G. have applied for a patent related to the ionizable lipids used in this work (Ionizable lipids; WO2022136641A1). All other authors declare no potential conflicts of interest., (© 2024. The Author(s).)

This review discusses the current data on predictive and prognostic biomarkers in oligometastatic NSCLC and discusses whether biomarkers identified in other stages and widespread metastatic disease can be extrapolated to the oligometastatic disease (OMD) setting. Research is underway to explore the prognostic and predictive value of biological attributes of tumor tissue, circulating cells, the tumor microenvironment, and imaging findings as biomarkers of oligometastatic NSCLC. Biomarkers that help define true OMD and predict outcomes are needed for patient selection for oligometastatic treatment, and to avoid futile treatments in patients that will not benefit from locoregional treatment. Nevertheless, these biomarkers are still in the early stages of development and lack prospective validation in clinical trials. Furthermore, the absence of a clear definition of OMD contributes to a heterogeneous study population in which different types of OMD are mixed and treatment strategies are different. Multiple tissue-based, circulating, and imaging features are promising regarding their prognostic and predictive role in NSCLC, but data is still limited and might be biased owing to the inclusion of heterogeneous patient populations. Larger homogeneous and prospective series are needed to assess the prognostic and predictive role of these biomarkers. As obtaining tissue can be difficult and is invasive, the most promising tools for further evaluation are liquid biopsies and imaging-based biomarkers as these can also be used for longitudinal follow-up., Competing Interests: Dr. Hartemink reports outside of this manuscript personal fees as an invited speaker from AstraZeneca, MSD, and Bristol Myers Squibb. Institutional funding as a local principal investigator (PI) from KWF Dutch Cancer Society (ESLUNG study) and the Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital (UPLAN studies). Member guideline committees: Dutch guidelines on ‘SCLC’, ‘NSCLC’, ‘Mediastinal tumors’, and ‘Tobacco smoking cessation’. Board member of Dutch Thoracic Group and Chair scientific committee of Dutch Thoracic Group. Dr. Ruysscher reports outside of this manuscript research grant/support/Advisory Board: Institutional financial interests (no personal financial interests) from AstraZeneca, BMS, Beigene, Philips, Olink and Advisory Board: Institutional financial interests (no personal financial interests) for Eli-Lilly. Dr. Hendriks reports outside of this manuscript personal fees as an invited speaker from AstraZeneca, Bayer, Lilly, MSD, high5oncology, Takeda, Janssen, GSK, Sanofi, Pfizer (Inst), Medtalks, Benecke, VJOncology, Medimix (self); all payments were paid to the institution with the exception of Medtalks, Benecke, VJOncology, Medimix; fees paid to her institution for advisory board membership from Advisory boards: Amgen, Boehringer Ingelheim, Lilly, Novartis, Pfizer, Takeda, Merck, Janssen, MSD, Anheart, Bayer, AZ; institutional research grants from 10.13039/100004337Roche 10.13039/100004328Genentech, 10.13039/100004325AstraZeneca, Boehringer Ingelheim, Takeda, 10.13039/100004334Merck, 10.13039/100004319Pfizer, 10.13039/100004336Novartis, and 10.13039/100005564Gilead; institutional funding as a local principal investigator (PI) from AstraZeneca, GSK, Novartis, Merck, Roche, Takeda, Blueprint, Mirati, Abbvie, Gilead, MSD, Merck, Amgen; Member guideline committees: Dutch guidelines on NSCLC, brain metastases and leptomeningeal metastases (self), ESMO guidelines on metastatic NSCLC and SCLC (non-financial) Other (non-financial): secretary NVALT studies foundation, subchair of EORTC metastatic NSCLC systemic therapy, vice-chair scientific committee Dutch Thoracic Group. The remaining authors declare no conflict of interest., (© 2024 The Authors.)

Introduction: The LIPI, based on pretreatment derived neutrophils/[leukocytes-neutrophils] ratio (dNLR) and LDH, is associated with immune checkpoint inhibitors (ICI) outcomes in advanced non-small-cell lung cancer (NSCLC). We aimed to assess baseline LIPI correlation with durvalumab consolidation outcomes in the locally advanced setting., Material and Methods: Multicentre retrospective study (330 patients) with stage III unresectable NSCLC treated with durvalumab after chemo-radiotherapy between April 2015 and December 2020; 65 patients treated with chemo-radiotherapy only. Baseline LIPI characterized 3 groups: good (dNLR≤3+LDH≤ULN), intermediate (dNLR>3/LDH>ULN) and poor (dNLR>3+LDH>ULN). Primary endpoint was overall survival (OS)., Results: In the durvalumab cohort, median age was 67 years, 95% smokers, 98% with a performance status of 0-1; 60% had nonsquamous histology and 16% a PD-L1 expression <1%. Radiotherapy was delivered concurrently in 81%. LIPI was evaluable in 216 patients: 66% good, 31% intermediate, 3% poor. LIPI significantly correlated with median OS (median follow-up: 19 months): 18.1 months vs. 47.0 months vs. not reached in poor, intermediate and good LIPI groups, respectively (P = .03). A trend between objective response rate and LIPI groups was observed: 0% vs. 41% vs. 45%, respectively (P = .05). The pooled intermediate/poor LIPI group was associated with shorter OS (HR 1.97; P = .03) and higher risk of progressive disease (OR 2.68; P = .047). Survivals and response were not influenced in the control cohort., Conclusion: Baseline LIPI correlated with outcomes in patients with locally advanced NSCLC treated with durvalumab consolidation, but not in those who only received chemo-radiotherapy, providing further evidence of its prognostic and potential predictive role of ICI benefit in NSCLC., Competing Interests: Disclosure VAA: Lectures and educational activities: Bristol-Myers Squibb, AstraZeneca, MSD; Travel, Accommodations, Expenses: Takeda, Sanofi, Janssen; RL: Personal fees: AstraZeneca, Bristol-Myers Squibb. Travel, Accommodations: Roche, Italfarmaco; RLC: Consulting, advisory role or lectures: Amgen, Bristol-Myers Squibb, Pierre-Fabre, Boehringer Ingelheim, Novartis, Roche. Honoraria: AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Pierre-Fabre, MSD, Novartis, Pfizer, Roche, Takeda. Clinical trials research: AstraZeneca, Roche. Travel, Accommodations, Expenses: Roche, Novartis, Takeda, Boehringer Ingelheim; JBB: Reports grants and personal fees from Roche and Pfizer, and personal fees from MSD, BMS, AstraZeneca, Boehringer-Ingelheim, Sanofi, and Novartis, outside the submitted work; SP: Consulting, advisory role or lectures: AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Eli Lilly, Merck, Novartis, Roche, Amgen, Takeda (outside the submitted manuscript); MT: Travel, accommodation, expenses: Roche, Bristol-Myers Squibb, AstraZeneca, Takeda, Eli Lilly. Honoraria as medical writer: Novartis, Amgen, MSD. None related to the current manuscript; MS: Speaker, Advisory Role: Amgen, AstraZeneca, BMS, Boehringer Ingelheim, Janssen, Lilly, Novartis, Pfizer, Roche, Sanofi Avemtis, Siemens Healthineers, Takeda; Research support (institutional): Amgen, BMS, Dracen Pharmaceuticals, Janssen, Novartis, Pfizer, Siemens Healthiness; EN: has participated in lectures and advisory boards from Roche, Bristol Myers Squibb, Merck Sharp & Dohme, Merck Serono, Pfizer, Lilly, Amgen, Boehringer Ingelheim, AstraZeneca, Takeda, Sanofi and Bayer. E. N. has received research funding support from Pfizer, Roche, Merck Serono, Bristol Myers Squibb and Nanostring; GL: Honorary from Boehringer Ingelheim, Blueprint Medicines, AstraZeneca, Merck, Janssen; Consulting and advisory role from Pfizer and AstraZeneca; Research funding from AstraZeneca, Lucence, Xilis, Merck Sharp and Dohme, EMD Serono, Blueprint Medicines, Tesaro, Vavarian Nordic, Novartis, G1 Therapeutics. AdaptImmune, BMS, GSK, Abbvie, Rgenix, Pfizer, Roche, Genentech, Lilly, Janssen; travel, accommodations and expenses from Boehringer Ingelheim, Pfizer, Squibb Sons, Janssen, Seattle Genetics, Celgene, Ibsen, Pharmacyclocs, Merck, AstraZeneca, Seagen; DS: Consulting, advisory role: AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Merck Sharp & Dohme, Sanofi. Honoraria: AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Eli Lilly, Roche, Merck Sharp & Dohme. Principal Investigator in clinical trial sponsored by Bristol-Myers Squibb, Merck Sharp & Dohme, Eli Lilly. Travel, Accommodations: AstraZeneca, Roche, Bristol-Myers Squibb, Merck Sharp & Dohme, Pfizer; RGC: Consulting, advisory role or lectures from AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Takeda, Janseen, MSD, Roche, Pfizer, Eli Lilly, Amgen, Sanofi; honoraria (self) from AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Pfizer, Roche, MSD, Takeda, Eli Lilly, Novartis; clinical trials research from AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Eli Lilly, Merck, Novartis, Pfizer, Roche, Medimmun, Sanofi-Aventis; VB: Consulting, advisory role: AstraZeneca, Bristol-Myers Squibb, MSD, Merck, Novartis, Pfizer, Roche. Clinical trials research: AstraZeneca, MSD, Roche; MC: Advisory or Consultancy role: AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, EUSA Pharma, Lilly, Roche. Honoraria, lectures: Abbot, AstraZeneca, Bristol-Myers Squibb, EUSA Pharma, Ipsen, Merck, Sharp & Dohme, Novartis, Pfizer, Pierre Fabre, Roche, Takeda. Travel expenses: Ipsen, Lilly, Merck, Pfizer, Pierre Fabre. Institutional financial interests: Astra Zeneca, Merck, Pfizer, Roche; BB: Sponsored Research at Gustave Roussy Cancer Center, Abbvie, Amgen, AstraZeneca, Biogen, Blueprint Medicines, BMS, Celgene, Eli Lilly, GSK, Ignyta, IPSEN, Merck KGaA, MSD, Nektar, Onxeo, Pfizer, Pharma Mar, Sanofi, Spectrum Pharmaceuticals, Takeda, Tiziana Pharma; DP: Consulting, advisory role or lectures: AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Daiichi Sankyo, Eli Lilly, Merck, Novartis, Pfizer, prIME Oncology, Peer CME, Roche. Honoraria: AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Merck, Novartis, Pfizer, prIME Oncology, Peer CME, Roche. Clinical trials research: AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Eli Lilly, Merck, Novartis, Pfizer, Roche, Medimmun, Sanofi-Aventis, Taiho Pharma, Novocure, Daiichi Sankyo. Travel, Accommodations, Expenses: AstraZeneca, Roche, Novartis, prIME Oncology, Pfizer; LM: Research grant/Funding (self): Bristol Myers Squibb, Boehringer Ingelheim, Amgen, Stilla, Inivata; Advisory/Consultancy: Roche Diagnostics, Takeda; Honoraria (self): Bristol Myers Squibb, Tecnofarma, Roche; Travel/Accommodation/Expenses: Roche, Boehringer Ingelheim, Takeda, AstraZeneca. The remaining authors declare no conflict of interest., (Copyright © 2023 Elsevier Inc. All rights reserved.)

The presence of human neutrophils in the tumor microenvironment is strongly correlated to poor overall survival. Most previous studies have focused on the immunosuppressive capacities of low-density neutrophils (LDN), also referred to as granulocytic myeloid-derived suppressor cells, which are elevated in number in the blood of many cancer patients. We observed two types of LDN in the blood of lung cancer and ovarian carcinoma patients: CD45 high LDN, which suppressed T-cell proliferation and displayed mature morphology, and CD45 low LDN, which were immature and non-suppressive. We simultaneously evaluated the classical normal-density neutrophils (NDN) and, when available, tumor-associated neutrophils. We observed that NDN from cancer patients suppressed T-cell proliferation, and NDN from healthy donors did not, despite few transcriptomic differences. Hence, the immunosuppression mediated by neutrophils in the blood of cancer patients is not dependent on the cells' density but rather on their maturity., (© 2023 Vanhaver et al.)

Purpose: Compared with people living without HIV (PWOH), people living with HIV (PWH) and cancer have traditionally been excluded from immune checkpoint inhibitor (ICI) trials. Furthermore, there is a paucity of real-world data on the use of ICIs in PWH and cancer., Methods: This retrospective study included PWH treated with anti-PD-1- or anti-PD-L1-based therapies for advanced cancers. Kaplan-Meier method was used to estimate overall survival (OS) and progression-free survival (PFS). Objective response rates (ORRs) were measured per RECIST 1.1 or other tumor-specific criteria, whenever feasible. Restricted mean survival time (RMST) was used to compare OS and PFS between matched PWH and PWOH with metastatic NSCLC (mNSCLC)., Results: Among 390 PWH, median age was 58 years, 85% (n = 331) were males, 36% (n = 138) were Black; 70% (n = 274) received anti-PD-1/anti-PD-L1 monotherapy. Most common cancers were NSCLC (28%, n = 111), hepatocellular carcinoma ([HCC]; 11%, n = 44), and head and neck squamous cell carcinoma (HNSCC; 10%, n = 39). Seventy percent (152/216) had CD4+ T cell counts ≥200 cells/µL, and 94% (179/190) had HIV viral load <400 copies/mL. Twenty percent (79/390) had any grade immune-related adverse events (irAEs) and 7.7% (30/390) had grade ≥3 irAEs. ORRs were 69% (nonmelanoma skin cancer), 31% (NSCLC), 16% (HCC), and 11% (HNSCC). In the matched mNSCLC cohort (61 PWH v 110 PWOH), 20% (12/61) PWH and 22% (24/110) PWOH had irAEs. Adjusted 42-month RMST difference was -0.06 months (95% CI, -5.49 to 5.37; P = .98) for PFS and 2.23 months (95% CI, -4.02 to 8.48; P = .48) for OS., Conclusion: Among PWH, ICIs demonstrated differential activity across cancer types with no excess toxicity. Safety and activity of ICIs were similar between matched cohorts of PWH and PWOH with mNSCLC.

The tumor microenvironment (TME) is composed of a plethora of different cell types, such as cytotoxic immune cells and immunomodulatory cells. Depending on its composition and the interactions between cancer cells and peri-tumoral cells, the TME may affect cancer progression. The characterization of tumors and their complex microenvironment could improve the understanding of cancer diseases and may help scientists and clinicians to discover new biomarkers. We recently developed several multiplex immunofluorescence (mIF) panels based on tyramide signal amplification (TSA) for the characterization of the TME in colorectal cancer, head and neck squamous cell carcinoma, melanoma, and lung cancer. Once the staining and scanning of the corresponding panels are completed, the samples are analyzed on an image analysis software. The spatial position and the staining of each cell are then exported from this quantification software into R. We developed R scripts that allow us not only to analyze the density of each cell type in several tumor compartments (e.g. the center of the tumor, the margin of the tumor, and the stroma) but also to perform distance-based analyses between different cell types. This particular workflow adds a spatial dimension to the classical density analysis already routinely performed for several markers. mIF analysis could allow scientists to have a better understanding of the complex interaction between cancer cells and the TME and to discover new predictive biomarkers of response to treatments, such as immune checkpoint inhibitors, and targeted therapies.

The molecular steps leading to small cell lung cancer (SCLC) development and progression are still poorly understood, resulting in the absence of targeted therapy and an extremely poor prognosis. Activation of Focal Adhesion Kinase (FAK) plays a key role in the invasive behavior of this cancer in vitro. Our hypothesis is that FAK could be a therapeutic target in SCLC. Our work aims to describe a mouse model to study the role of FAK and the antitumoral potential of its inhibition in SCLC in vivo., (Copyright © 2023 SPLF. Published by Elsevier Masson SAS. All rights reserved.)

Introduction: Approximately 10% of EGFR mutations (EGFRmuts) are uncommon (ucEGFRmuts). We aimed to collect real-world data about osimertinib for patients with ucEGFRmuts., Methods: This is a multicenter, retrospective study of ucEGFRmut (exon 20 insertions excluded) metastatic NSCLC treated with osimertinib as first EGFR inhibitor. The Response Evaluation Criteria in Solid Tumors and response assessment in neuro-oncology brain metastases brain objective response rate (ORR) were evaluated by the investigators. Median progression-free survival (mPFS), median overall survival, and median duration of response (mDOR) were calculated from osimertinib initiation. Mutations found at resistance were collected., Results: A total of 60 patients were included (22 centers, nine countries), with median age of 64 years, 75% females, and 83% Caucasian. The largest subgroups were G719X (30%), L861Q (20%), and de novo Thr790Met (T790M) (15%). The ORR was 61%, mPFS 9.5 months, mDOR 17.4 months, and median overall survival 24.5 months. Regarding patients with no concurrent common mutations or T790M (group A, n = 44), ORR was 60%, mPFS 8.6 months, and mDOR 11 months. For G719X, ORR was 47%, mPFS 8.8 months, and mDOR 9.1 months. For L861Q, ORR was 80%, mPFS 16 months, and mDOR 16 months. For de novo T790M, ORR was 44%, mPFS 12.7 months, and mDOR 46.2 months. Compound EGFRmut including common mutations had better outcome compared with only ucEGFRmut. For 13 patients with a response assessment in neuro-oncology brain metastases-evaluable brain metastases, brain ORR was 46%. For 14 patients, rebiopsy results were analyzed: four patients with additional EGFR mutation (C797S, D585Y, E709K), three with new TP53 mutation, one with c-Met amplification, one with PIK3CA mutation, and one with neuroendocrine transformation., Conclusions: Osimertinib was found to have an activity in ucEGFRmut with a high rate of disease control systemically and intracranially. Several resistance mechanisms were identified. This report comprises, to the best of our knowledge, the largest data set of its kind., (Copyright © 2022 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.)

Introduction: Durvalumab is the standard-of-care as consolidation therapy after chemo-radiotherapy in stage III unresectable non-small cell lung cancer (NSCLC); however, its activity across patients with NSCLC harbouring driver genomic alterations (dGA) is poorly characterised., Material and Methods: Multicentre retrospective study including patients with stage III unresectable NSCLC treated with durvalumab after chemo-radiotherapy between April 2015 and October 2020 at 26 centres in Europe and America. Clinical and biological data were collected; dGA included: EGFR/BRAF/KRAS mutations (m) and ALK/ROS1 rearrangements (r). We evaluated progression-free survival (PFS) and overall survival (OS) based on dGA., Results: Out of 323 patients included, 43 patients had one dGA: KRASm (n = 26; 8 G12C), EGFRm (n = 8; 6 del19/ex21), BRAFm (n = 5; 4 V600E) and ALKr (n = 4). The median age was 66 years [39-84], gender ratio 1:1, with 98% performance status (PS) 0-1 and 19% non-smokers; 88% had adenocarcinoma. PD-L1 was positive in 85% (n = 4 missing). In the whole cohort, the median PFS was 17.5 months (mo.) (95% CI, 13.2-24.9) and median OS 47 mo (95%CI, 47-not reached [NR]). No statistically significant differences in terms of the median PFS were observed between patients with dGA vs. non-dGA: 14.9 mo (95% CI, 8.1-NR) vs. 18 mo. (95% CI, 13.4-28.3) (P = 1.0); however, when analysed separately: the median PFS was NR (11.3-NR) in the KRASm G12C vs. 8.1 mo (5.8-NR) in the EGFRm del19/ex21 vs. 7.8 mo (7.7-NR) in the BRAFm V600E/ALKr (P = 0.02)., Conclusions: We observed limited activity of durvalumab consolidation in patients with stage III unresectable NSCLC with EGFR/BRAFm and ALKr but not for those harbouring KRASm. Larger prospective studies are needed to confirm these findings., Competing Interests: Conflict of interest statement MMj: advisory and consultancy honoraria from Roche, Merck, BristolMyers Squibb, AstraZeneca, Amgen, Boehringer, Sanofi and Takeda; speaker honoraria from Roche, Merck, Bristol-Myers Squibb, AstraZeneca, Bayer, Amgen, Pfizer and Boehringer; grants from AstraZeneca and BristolMyers Squib, and travel/accommodation expenses from Roche, Merck and Lilly. RLC: honoraria from Kyowa Kirin, Pierre-Fabre, Takeda, AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Novartis, Roche, Merck Serono, Pfizer; consulting or advisory role from Roche, Astra-Zeneca, Boehringer Ingelheim, Aristo, Novartis; research funding from Roche, Bristol-Myers Squibb, MSD, Boehringer Ingelheim, AstraZeneca. JBB: grants and personal fees from Roche-Genentech, Pfizer, MSD, BMS, Astrazeneca, Novartis, Boehringer-Ingelheim, Vifor, Sanofi, LEO Pharma, outside the submitted work. SP: Consulting, advisory role or lectures from AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Eli Lilly, Merck, Novartis, Roche, Amgen. MT: travel grants from Roche, Bristol-Myers Squibb, AstraZeneca, Takeda; honoraria as medical writer from Novartis, Amgen. GZ: research grants from Roche-France, Bristol-Myers Squibb, and Takeda outside of the submitted work; perceived fees from Bristol-Myers Squibb, AstraZeneca, Pfizer, and Boehringer Ingelheim outside the submitted work; and reimbursement for international meetings assistance from AbbVie, Merck Sharp & Dohme, AstraZeneca, Bristol-Myers Squibb, and Roche-France. XM-R: Research grant funding from Brystol-Myers Squibb; consulting, advisory role or lectures from AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim; honoraria (self) from AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Pfizer, Roche, MSD; clinical trials research from Boehringer Ingelheim, Pfizer, Roche, Abbvie; travel, accommodations and expenses from Roche, Pfizer, Brysto-Myers Squibb. JB: educational grants by AMGEN. MSch: speaker and advisory role honoraria, travel accommodations from AMGEN, AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Janssen, Novartis, Pfizer, Roche, Takeda; personal research support from AMGEN, Dracen Pharmaceuticals, Siemens Healthineers; institutional research support from Boehringer Ingelheim, Bristol-Myers Squibb, MSD, Novartis, Pfizer, Roche. EN: research support from Roche, Merck Serono, Bristol Myers Squibb and Pfizer and participated in advisory boards or lectures from Bristol Myers Squibb, Merck Serono, Merck Sharpe & Dohme, Lilly, Roche, Pfizer, Takeda, Bayer, Boehringer Ingelheim, Amgen and AstraZeneca. DS: Consulting, advisory role, honoraria from AstraZeneca, Merck Sharp & Dohme, Bristol-Myers Squibb, Boehringer Ingelheim, Sanofi, Eli Lilly; travel grants from Roche. RGC: Consulting, advisory role or lectures from AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Takeda, Janseen, MSD, Roche, Pfizer, Eli Lilly, Amgen, Sanofi; honoraria (self) from AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Pfizer, Roche, MSD, Takeda, Eli Lilly, Novartis; clinical trials research from AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Eli Lilly, Merck, Novartis, Pfizer, Roche, Medimmun, Sanofi-Aventis. JMe: Advisory Boards/Honoraria/Speakers’ fee/Consultant for Astra-Zeneca, Boeringher Ingelheim, BMS, Roche, MSD; travel grants from Astra-Zeneca, Boeringher Ingelheim, BMS, Ipsen, Roche, MSD. VB: Clinical trial research from AstraZeneca, Roche, MSD; advisory role/consulting/speaker from Pfizer, MSD, AstraZeneca, Roche, Bristol, Merck, Takeda. MC: Advisory or Consultancy role from AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, EUSA Pharma, Lilly, Roche; honoraria, lectures from Abbot, Bristol-Myers Squibb, EUSA Pharma, Ipsen, Novartis, Pfizer, Pierre Fabre, Roche; travel, expenses from Ipsen, Lilly, Merck, Pfizer, Pierre Fabre; institutional financial interests from Astra Zeneca, Merck, Roche, Pfizer. GR: consulting, advisory role or lectures from AstraZeneca, Bayer, Bristol-Myers Squibb, Janssen, Merck Sharp & Dome, Pfizer, Roche, Takeda; sponsored Research Amgen and Janssen. BB: sponsored research at Gustave Roussy Cancer Centre Abbvie, Amgen, AstraZeneca, Biogen, Blueprint Medicines, BMS, Celgene, Eli Lilly, GSK, Ignyta, IPSEN, Merck KGaA, MSD, Nektar, Onxeo, Pfizer, Pharma Mar, Sanofi, Spectrum Pharmaceuticals, Takeda, Tiziana Pharma. DP: consulting, advisory role or lectures from AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Daiichi Sankyo, Eli Lilly, Merck, Novartis, Pfizer, prIME Oncology, Peer CME, Roche; honoraria from AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Merck, Novartis, Pfizer, prIME Oncology, Peer CME, Roche; clinical trials research from AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Eli Lilly, Merck, Novartis, Pfizer, Roche, Medimmun, Sanofi-Aventis, Taiho Pharma, Novocure, Daiichi Sankyo; travel, accommodations, expenses from AstraZeneca, Roche, Novartis, prIME Oncology, Pfizer. LM: research grant/Funding (self) from Bristol Myers Squibb, Boehringer Ingelheim, Amgen, Stilla, Inivata; advisory/consultancy from Roche, Takeda; honoraria (self) from Bristol Myers Squibb, Roche, Takeda, AstraZeneca; travel/Accommodation/Expenses from Roche, Bristol Myers Squibb, Takeda, AstraZeneca; non-remunerated activity/ies from AstraZeneca. MR, EA, MMo, ND, EE, RL, JMo, FA, SP, AD, MSp, EM, RR, JCB, LL, BD, AdG, CAV and GL declare no conflicts of interest., (Copyright © 2022. Published by Elsevier Ltd.)

Osimertinib has become a standard of care in the first-line treatment of advanced-stage non-small-cell lung cancer (NSCLC) harboring exon 19 and 21 activating mutations in the EGFR gene. Nevertheless, the 18.9-month median progression-free survival emphasizes the fact that resistance to osimertinib therapy is inevitable. Acquired resistance mechanisms to osimertinib in EGFR-driven NSCLC include MET amplification, EGFR C797S mutation, neuroendocrine differentiation, small-cell lung carcinoma histologic transformation, PD-L1 and KRAS amplifications and ESR1-AKAP12 and MKRN1-BRAF translocations, as well as BRAF V600 mutation. This last one represents 3% of the acquired resistance mechanisms to osimertinib. In this review, we discuss the rationale for EGFR/BRAF/MEK co-inhibition in the light of a clinical case of EGFR -mutant NSCLC developing a BRAF V600 mutation as an acquired resistance mechanism to osimertinib and responding to the association of osimertinib plus dabrafenib and trametinib. Additionally, we discuss the acquired resistance mechanisms to osimertinib plus dabrafenib and trametinib combination in that context.

Background: In cystic fibrosis (CF), recurrent infections suggest impaired mucosal immunity but whether production of secretory immunoglobulin A (S-IgA) is impaired remains elusive. S-IgA is generated following polymeric immunoglobulin receptor (pIgR)-mediated transepithelial transport of dimeric (d-)IgA and represents a major defence through neutralisation of inhaled pathogens like Pseudomonas aeruginosa (Pa)., Methods: Human lung tissue (n = 74), human sputum (n = 118), primary human bronchial epithelial cells (HBEC) (cultured in air-liquid interface) (n = 19) and mouse lung tissue and bronchoalveolar lavage were studied for pIgR expression, IgA secretion and regulation., Findings: Increased epithelial pIgR immunostaining was observed in CF lung explants, associated with more IgA-producing plasma cells, sputum and serum IgA, especially Pa-specific IgA. In contrast, pIgR and IgA transport were downregulated in F508del mice, CFTR-inhibited HBEC, and CF HBEC. Moreover, the unfolded protein response (UPR) due to F508del mutation, inhibited IgA transport in Calu-3 cells. Conversely, pIgR expression and IgA secretion were strongly upregulated following Pa lung infection in control and F508del mice, through an inflammatory host response involving interleukin-17., Interpretation: A complex regulation of IgA secretion occurs in the CF lung, UPR induced by CFTR mutation/dysfunction inhibiting d-IgA transcytosis, and Pa infection unexpectedly unleashing this secretory defence mechanism., Funding: This work was supported by the Forton's grant of the King Baudouin's Foundation, Belgium, the Fondazione Ricerca Fibrosi Cistica, Italy, and the Fonds National de la Recherche Scientifique, Belgium., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Despite its beneficial effects, radiotherapy still results in a range of side effects that negatively impact quality of life of patients. Exercise has been shown to counteract the side effects induced by cancer treatment. This narrative review aims to provide an up-to-date review of the effects of an exercise intervention in cancer patients during radiotherapy. A literature search was performed on PubMed to identify original articles that evaluated the effects of an exercise programme to alleviate treatment-related side effects in cancer patients undergoing radiotherapy with or without other cancer treatments. Benefits related to exercise training have been shown in breast, prostate, rectal, lung, head and neck cancer patients undergoing radiotherapy. Therefore, exercise should be considered as a concurrent treatment alongside radiotherapy to alleviate treatment-related side effects and facilitate effective recovery. Due to the onset and progress of treatment-related side effects throughout radiotherapy, a regular clinical evaluation seems strongly advisable in order to continuously adapt the exercise programme depending on symptoms and side effects. An exercise professional is needed to personalize exercise training based on the medical condition and tailor it throughout the intervention according to progress and the patient's medical status. Future studies are needed to confirm the potential benefits of exercises observed on treatment-related side effects. Furthermore, because of the narrative design of this study, a systematic review is required to evaluate the strength of the evidence reported., Competing Interests: Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2020.)

Small-cell lung cancer (SCLC) represents 15% of all lung cancers and it is clinically the most aggressive type, being characterized by a tendency for early metastasis, with two-thirds of the patients diagnosed with an extensive stage (ES) disease and a five-year overall survival (OS) as low as 5%. There are still no effective targeted therapies in SCLC despite improved understanding of the molecular steps leading to SCLC development and progression these last years. After four decades, the only modest improvement in OS of patients suffering from ES-SCLC has recently been shown in a trial combining atezolizumab, an anti-PD-L1 immune checkpoint inhibitor, with carboplatin and etoposide, chemotherapy agents. This highlights the need to pursue research efforts in this field. Focal adhesion kinase (FAK) is a non-receptor protein tyrosine kinase that is overexpressed and activated in several cancers, including SCLC, and contributing to cancer progression and metastasis through its important role in cell proliferation, survival, adhesion, spreading, migration, and invasion. FAK also plays a role in tumor immune evasion, epithelial-mesenchymal transition, DNA damage repair, radioresistance, and regulation of cancer stem cells. FAK is of particular interest in SCLC, being known for its aggressiveness. The inhibition of FAK in SCLC cell lines demonstrated significative decrease in cell proliferation, invasion, and migration, and induced cell cycle arrest and apoptosis. In this review, we will focus on the role of FAK in cancer cells and their microenvironment, and its potential as a therapeutic target in SCLC.

Introduction: Focal adhesion kinase (FAK) plays a crucial role in cancer development and progression. FAK is overexpressed and/or activated and associated with poor prognosis in various malignancies. However, in lung cancer, activated FAK expression and its prognostic value are unknown., Methods: FAK and activated FAK (phospho-FAK Y397) expressions were analyzed by multiplex immunofluorescence staining in formalin-fixed paraffin-embedded tissues from 95 non-small-cell lung cancer (NSCLC) and 105 small-cell lung cancer (SCLC) patients, and 37 healthy donors. The FAK staining score was defined as the percentage (%) of FAK-stained tumor area multiplied by (×) FAK mean intensity and phospho-FAK staining score as the (% of phospho-FAK-stained area of low intensity × 1) + (% of phospho-FAK-stained area of medium intensity × 2) + (% of the phospho-FAK-stained area of high intensity × 3). FAK and phospho-FAK staining scores were compared between normal, NSCLC, and SCLC tissues. They were also tested for correlations with patient characteristics and clinical outcomes., Results: The median follow-up time after the first treatment was 42.5 months and 6.4 months for NSCLC and SCLC patients, respectively. FAK and phospho-FAK staining scores were significantly higher in lung cancer than in normal lung and significantly higher in SCLC compared to NSCLC tissues ( p < 0.01). Moreover, the ratio between phospho-FAK and FAK staining scores was significantly higher in SCLC than in NSCLC tissues ( p < 0.01). However, FAK and activated FAK expression in lung cancer did not correlate with recurrence-free and overall survival in NSCLC and SCLC patients., Conclusions: Total FAK and activated FAK expressions are significantly higher in lung cancer than in normal lung, and significantly higher in SCLC compared to NSCLC, but are not prognostic biomarkers in this study.

Small cell lung cancer (SCLC) has a poor prognosis. Focal adhesion kinase (FAK) is a non-receptor tyrosine kinase regulating cell proliferation, survival, migration, and invasion, which is overexpressed and/or activated in several cancers, including SCLC. We wanted to determine whether FAK contributes to SCLC aggressive behavior. We first evaluated the effect of FAK small-molecule inhibitor PF-573,228 in NCI-H82, NCI-H146, NCI-H196, and NCI-H446 SCLC cell lines. PF-573,228 (0.1-5 μmol/L) inhibited FAK activity by decreasing phospho-FAK (Tyr397), without modifying total FAK expression. PF-573,228 decreased proliferation, decreased DNA synthesis, induced cell-cycle arrest in G 2 -M phases, and increased apoptosis in all cell lines. PF-573,228 also decreased motility in adherent cell lines. To make sure that these effects were not off-target, we then used a genetic method to inhibit FAK in NCI-H82 and NCI-H446, namely stable transduction with FAK shRNA and/or FAK-related nonkinase (FRNK), a splice variant lacking the N-terminal and kinase domains. Although FAK shRNA transduction decreased total and phospho-FAK (Tyr397) expression, it did not affect proliferation, DNA synthesis, or progression through cell cycle. However, restoration of FAK-targeting (FAT) domain (attached to focal adhesion complex where it inhibits pro-proliferative proteins such as Rac-1) by FRNK transduction inhibited proliferation, DNA synthesis, and induced apoptosis. Moreover, although FAK shRNA transduction increased active Rac1 level, FRNK reexpression in cells previously transduced with FAK shRNA decreased it. Therefore, FAK appears important in SCLC biology and targeting its kinase domain may have a therapeutic potential, while targeting its FAT domain should be avoided to prevent Rac1-mediated protumoral activity., (©2018 American Association for Cancer Research.)