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Background: The efficacy of checkpoint inhibitors for non-small cell lung cancer (NSCLC) with MET exon 14 skipping (METΔ14ex) remains controversial., Materials and Methods: 110 consecutive METΔ14ex NSCLC patients receiving first-line chemotherapy (CHT) and/or immunotherapy (IO) in 10 German centers between 2016-2022 were analyzed., Results: Combined CHT-IO was given to 35/110 (32%) patients, IO alone to 43/110 (39%), and CHT to 32/110 (29%) upfront. Compared to CHT, CHT-IO showed longer progression-free survival (median PFS 6 vs. 2.5 months, p = 0.004), more objective responses (ORR 49% vs. 28%, p = 0.086) and numerically longer overall survival (OS 16 vs. 10 months, p = 0.240). For IO monotherapy, OS (14 vs. 16 months) and duration of response (26 vs. 22 months) were comparable to those of CHT-IO. Primary progressive disease (PD) was more frequent with IO compared to CHT-IO (13/43 vs. 3/35, p = 0.018), particularly for never-smokers (p = 0.041). Higher PD-L1 TPS were not associated with better IO outcomes, but TP53 mutated tumors showed numerically improved ORR (56% vs. 32%, p = 0.088) and PFS (6 vs. 3 months, p = 0.160), as well as longer OS in multivariable analysis (HR=0.54, p = 0.034) compared to their wild-type counterparts. Any second-line treatment was administered to 35/75 (47%) patients, with longer survival for capmatinib or tepotinib compared to crizotinib (PFS 10 vs. 3 months, p = 0.013; OS 16 vs. 13 months, p = 0.270)., Conclusion: CHT-IO is superior to CHT, and IO alone also effective for METΔ14ex NSCLC, especially in the presence of TP53 mutations and independent of PD-L1 expression, but never-smokers are at higher risk of primary PD., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: JK: speaker’s honoraria from BMS, AstraZeneca and Pfizer, travel grants from Takeda, advisory board honoraria from Takeda, Roche and AstraZeneca. DM: advisory board/lecture fees from AstraZeneca, BMS, Boehringer Ingelheim, Lilly, MSD, Novartis, Roche, Sanofi and Takeda. DiKa: advisory boards/speaker´s honoraria from BMS, Boehringer-Ingelheim, MSD, Roche, Janssen, Pfizer, AstraZeneca; support for attending meetings from Novartis, Boehringer-Ingelheim. MH: advisory board, speaker’s honoraria and travel grants from Boehringer-Ingelheim. BH: advisory board/lecture fees from AstraZeneca, Boehringer Ingelheim, BMS, MSD, Roche, Pfizer. MF: grants from AstraZeneca, BMS, MSD, and Roche; consulting fees from AstraZeneca, MSD, Roche, BMS; speaker´s honoraria from AstraZeneca, MSD, Roche, BMS. MK: speaker’s honoraria and travel grants from Veracyte Inc. AV: speaker’s honoraria from AstraZeneca. MA: speaker’s honoraria from Boehringer Ingelheim. CG: advisory board/lecture fees from Amgen, AstraZeneca, BMS, Boehringer Ingelheim, Eli Lilly, Takeda, MSD, Novartis, Pfizer, Roche, AbbVie, Tesaro/GSK and Blueprints Medicines. AT: consulting fees from Boehringer Ingelheim, Daiichi, Astra Zeneca, Roche, Pfizer, BMS, MSD, Sanofi, Lilly, Novartis; speaker’s honoraria from Boehringer Ingelheim, Daiichi, Astra Zeneca, Roche, Pfizer, BMS, MSD, Sanofi, Lilly, Novartis; travel grants from Sanofi, Janssen, Daiichi; BMS, MSD, AstraZeneca. MR: advisory board/lecture fees from Amgen, AstraZeneca, BMS, Boehringer, Lilly, Merck, MSD, Novartis, Pfizer, Roche, Samsung. NF: grants from Roche, consulting fees from AbbVie, Amgen, AstraZeneca, BeiGene, Berlinchemie, Boehringer Ingelheim, Bristol Myers&Squibb, Lilly, Merck Sharp&Dohme, Merck, Novartis, Pfizer, Roche, Sanofi, Takeda; support for attending meetings from Amgen, AstraZeneca, BMS, Janssen, Lilly, Takeda. AS: advisory board honoraria from BMS, AstraZeneca, ThermoFisher, Novartis, speaker’s honoraria from BMS, Illumina, AstraZeneca, Novartis, ThermoFisher, MSD, Roche, and research funding from Chugai and BMS. MT: research funding from AstraZeneca, BMS, Merck, Roche, Takeda; speaker’s honoraria from AstraZeneca, Beigene, Novartis, Eli Lilly, BMS, MSD, Roche, Celgene, Takeda, AbbVie, Boehringer Ingelheim, Pfizer, Eli Lilly, MSD, Takeda, Pfizer, Chugai, Daiichi Sankyo, GlaxoSmithKline, Janssen Oncology, Merck, Sanofi and travel grants from AstraZeneca, BMS, MSD, Novartis, Daiichi Sankyo, Janssen Oncology, Lilly, Merck, Pfizer, Roche, Sanofi, Takeda, Boehringer Ingelheim. PC: research funding from AstraZeneca, Amgen, Boehringer Ingelheim, Novartis, Roche, and Takeda, speaker’s honoraria from AstraZeneca, Janssen, Novartis, Roche, Pfizer, Thermo Fisher, Takeda, support for attending meetings from AstraZeneca, Eli Lilly, Daiichi Sankyo, Gilead, Novartis, Pfizer, Takeda, and personal fees for participating to advisory boards from AstraZeneca, Boehringer Ingelheim, Chugai, Pfizer, Novartis, MSD, Takeda and Roche, all outside the submitted work. All other authors have no conflicts of interest to declare., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: EGFR exon20 insertions (ex20ins) are targeted by novel compounds in non-small-cell lung cancer (NSCLC). However, data about outcome under conventional therapies and the influence of molecular features are scarce., Patients and Methods: We retrospectively analysed 118 patients with evaluation of radiologic response based on RECIST v1.1. TP53 status was available for 88 cases., Results: Platinum doublets and chemoimmunotherapy showed similar response rates (20-25%), disease control rates (80%) and median progression-free survival (mPFS, ≈7 months), which were longer compared to monochemotherapy (9%, 59%, 4.1 months), EGFR inhibitors (0%, 46%, 3.0) and PD-(L)1 inhibitors (0%, 30%, 2.1; p < 0.05). Overall survival (OS) was not dependent on the choice of first-line treatment, but related to more lines of systemic therapy (p < 0.05). TP53 mutations and brain metastases were associated with shorter PFS under platinum doublets and EGFR inhibitors (HR 3.3-6.1, p < 0.01), and shorter OS for patients receiving both treatments (p < 0.05). More tumour CD8 + and less Th1 cells were associated with longer OS independent of brain and TP53 status (p < 0.01). No difference in outcome was noted according to the ex20ins site and use of pemetrexed (vs. other cytotoxics) or bevacizumab. Long-lasting responses (>1 year) occasionally occurred under EGFR inhibitors for both 'near-' and 'far-loop' variants., Conclusions: Platinum doublets and chemoimmunotherapy have the highest activity with ORR of 20-25% and mPFS of approximately 7 months, regardless of the cytotoxic partner, while PD-(L)1 inhibitors show limited efficacy. TP53 mutations, brain metastases and a lower tumour CD8/Th1-cell ratio are independently associated with shorter survival., Competing Interests: Conflict of interest statement PC: research funding from Amgen, AstraZeneca, Boehringer Ingelheim, Novartis, Roche, Takeda, and advisory board/lecture fees from AstraZeneca, Boehringer Ingelheim, Chugai, Daiichi Sankyo, Gilead, Novartis, Pfizer, Roche, Takeda. JR: lecture fees from AstraZeneca, Boehringer Ingelheim. FCS: research funding from Roche; non-financial support from Lilly; personal fees from Takeda, and Pfizer, outside the submitted work. BH: advisory board/lecture fees from AstraZeneca, Boehringer Ingelheim, BMS, MSD, Roche, Pfizer. JK: research funding from AstraZeneca and Celgene. MJ: speaker's honoraria from Roche, Boehringer, and travel grants from Daiichi Sankyo. DK: advisory boards/speakers honoraria from AstraZeneca, BMS, Boehringer Ingelheim, GSK, MSD, Novartis, Pfizer, Roche, Takeda. FE: speaker's honoraria from Roche. FB: research funding from AstraZeneca, BMS and Roche, and travel grants from BMS and MSD. RS: research funding from BMS, and speaker's honoraria from AstraZeneca and Roche. AT: research funding from BMS. MW: research funding from Roche; Personal fees from Roche, AstraZeneca, Boehringer, Kite, Novartis, Merck, BMS, Heidelberg Pharma; Non-financial support from AstraZeneca, BMS, Glenmark; outside the submitted work. SL: advisory board, speaker's honoraria and travel support from BerGenBio, Novartis, Lilly, BMS, MSD, Roche, Celgene, Takeda, AstraZeneca, Sanofi, as well as research funding from Roche, BMS, BerGenBio. WB: consulting fees from AstraZeneca, Boehringer Ingelheim, BMS, Lilly, MSD, Pfizer, Roche, Sanofi, honoraria for lectures from AstraZeneca, Boehringer Ingelheim, BMS, Lilly, MSD, Pfizer, Roche, Sanofi. Travel grants from AstraZeneca, Boehringer Ingelheim, MSD, Roche. CS: advisory board honoraria from AstraZeneca, Boehringer Ingelheim, BMS, MSD, Novartis, Roche, Pfizer, Takeda. Speaker's honoraria from AstraZeneca, Boehringer, Lilly, Roche, MSD, Takeda. DM: advisory board/lecture fees from AstraZeneca, BMS, Boehringer Ingelheim, Lilly, MSD, Novartis, Roche, Sanofi and Takeda (no personal honoraria) NF: advisory board/lecture fees from AbbVie, AstraZeneca, BMS, Boehringer Ingelheim, Pfizer, Roche, MSD, Takeda. JK: advisory board member without receiving any personal fees for Roche Pharma, Boehringer Ingelheim, BMS, MSD, Amgen, Lilly and Takeda. MR: advisory board/lecture fees from Amgen, AstraZeneca, BMS, Boehringer, Lilly, Merck, MSD, Novartis, Pfizer, Roche, Samsung. FG: grants and personal fees from AstraZeneca, Boehringer Ingelheim, BMS, Eli Lilly, MSD, Novartis, Pfizer, Roche, Takeda, as well as personal fees from AbbVie, Tesaro/GSK, Blueprint Medicines, Amgen. CG: advisory board/lecture fees from Amgen, AstraZeneca, BMS, Boehringer Ingelheim, Eli Lilly, Takeda, MSD, Novartis, Pfizer, Roche, AbbVie, Tesaro/GSK and Blueprints Medicines. AS: advisory board honoraria from BMS, AstraZeneca, ThermoFisher, Novartis, speaker's honoraria from BMS, Illumina, AstraZeneca, Novartis, ThermoFisher, MSD, Roche, and research funding from Chugai and BMS. MT: advisory board honoraria from Novartis, Eli Lilly, BMS, MSD, Roche, Celgene, Takeda, AbbVie, Boehringer Ingelheim, Pfizer, speaker's honoraria from Eli Lilly, MSD, Takeda, Pfizer, research funding from AstraZeneca, BMS, Celgene, Novartis, Roche, Takeda, and travel grants from BMS, MSD, Novartis, Boehringer. All remaining authors have declared no conflicts of interest., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Objective: Current predictive biomarkers for PD-1 (programmed cell death protein 1)/PD-L1 (programmed death-ligand 1)-directed immunotherapy in non-small cell lung cancer (NSCLC) mostly focus on features of tumour cells. However, the tumour microenvironment and immune context are expected to play major roles in governing therapy response. Against this background, we set out to apply context-sensitive feature selection and machine learning approaches on expression profiles of immune-related genes in diagnostic biopsies of patients with stage IV NSCLC., Methods: RNA expression levels were determined using the NanoString nCounter platform in formalin-fixed paraffin-embedded tumour biopsies obtained during the diagnostic workup of stage IV NSCLC from two thoracic oncology centres. A 770-gene panel covering immune-related genes and control genes was used. We applied supervised machine learning methods for feature selection and generation of predictive models., Results: Feature selection and model creation were based on a training cohort of 55 patients with recurrent NSCLC treated with PD-1/PD-L1 antibody therapy. Resulting models identified patients with superior outcomes to immunotherapy, as validated in two subsequently recruited, separate patient cohorts (n = 67, hazard ratio = 0.46, p = 0.035). The predictive information obtained from these models was orthogonal to PD-L1 expression as per immunohistochemistry: Selecting by PD-L1 positivity at immunohistochemistry plus model prediction identified patients with highly favourable outcomes. Independence of PD-L1 positivity and model predictions were confirmed in multivariate analysis. Visualisation of the models revealed the predictive superiority of the entire 7-gene context over any single gene., Conclusion: Using context-sensitive assays and bioinformatics capturing the tumour immune context allows precise prediction of response to PD-1/PD-L1-directed immunotherapy in NSCLC., Competing Interests: Conflict of interest statement M.W. reports honoraria from Boehringer Ingelheim, Novartis, Roche and Takeda and research funding from Bristol Myers Squibb and Takeda. F.M. reports research funding from Bristol Myers Squibb. Henning Reis reports a consulting and advisory role for Bristol Myers Squibb; honoraria from Roche and Bristol Myers Squibb; travel support from Philips, Roche and Bristol Myers Squibb; research funding from Bristol Myers Squibb and share ownership from Bayer. M.G. reports travel support from MSD Sharp & Dohme. J.K. reports a consulting and advisory role without personal honoraria for Roche, Boehringer Ingelheim, Bristol Myers Squibb, MSD and Takeda. T.H. reports honoraria from Bristol Myers Squibb, Chugai, MSD Sharp & Dohme and Roche and a consulting and advisory role for Bristol Myers Squibb and Chugai. M.M. reports honoraria from Roche and Boehringer Ingelheim. W.E.E.E. reports honoraria from Eli Lilly, Boehringer Ingelheim, Pfizer, Novartis, Roche, Merck, Bristol Myers Squibb, Amgen, GlaxoSmithKline, Astellas, Bayer, Teva, Merck Serono, Daiichi Sankyo and Hexal; a consulting or advisory role for Eli Lilly, Boehringer Ingelheim, Novartis, Pfizer, Roche, Merck, Bristol Myers Squibb, Astellas, Bayer, Teva and Daiichi Sankyo and research funding from Eli Lilly (institutional). C.A. reports research funding from Bristol Myers Squibb. K.D. reports a consultancy/advisory role for Boehringer Ingelheim and Novartis and honoraria from Boehringer Ingelheim. M.S. reports consultancy for AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen (IQWiG), Lilly and Novartis; honoraria for CME presentations from Alexion, Boehringer Ingelheim, Celgene, GlaxoSmithKline, Lilly and Novartis; research funding to the institution from Boehringer Ingelheim, Bristol Myers Squibb and Novartis and other support from Universität Duisburg-Essen (patents). All the remaining authors declared no conflicts of interest., (Copyright © 2020 Elsevier Ltd. All rights reserved.)