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Background: Perioperative immunotherapy improves short-term outcomes in resectable non-small-cell lung cancer (NSCLC). We now report 5-year survival from the NADIM trial to assess its long-term benefit., Methods: NADIM was a multicentre, single-arm, phase 2 trial conducted across 18 hospitals in Spain. Patients were aged 18 years or older, had an Eastern Cooperative Oncology Group performance status of 0 or 1, and had histologically or cytologically confirmed, treatment-naive, resectable stage IIIA NSCLC (American Joint Committee on Cancer, 7th edition criteria). The neoadjuvant treatment consisted of three cycles of intravenous paclitaxel (200 mg/m 2 ) and carboplatin (area under the curve 6 mg/mL per min) with nivolumab (360 mg). After surgery, 1 year of adjuvant treatment with intravenous nivolumab monotherapy was administered (240 mg every 2 weeks for 4 months, followed by 480 mg every 4 weeks for 8 months). The primary endpoint was 24-month progression-free survival, with 5-year progression-free survival and overall survival as secondary endpoints, assessed in the intention-to-treat population (ie, all patients who received neoadjuvant treatment). Toxicity profile was also assessed as a secondary endpoint. This trial is registered at ClinicalTrials.gov (NCT03081689) and is complete; this is the final report of the trial., Findings: Between April 26, 2017, and Aug 25, 2018, 51 patients were assessed for eligibility, of whom 46 comprised the intention-to-treat population (34 [74%] male and 12 [26%] female, median age 63 years [IQR 58-70]). Follow-up was concluded at 60 months (data cutoff July 11, 2023; median follow-up 60·0 months [IQR 60·0-60·0]). 5-year progression-free survival in the intention-to-treat population was 65·0% (95% CI 49·4-76·9), and overall survival was 69·3% (53·7-80·6). Disease progression occurred in 11 (24%) patients; 14 (30%) patients died, including nine (20%) from disease relapse and five (11%) from non-tumour-related causes. Treatment-related adverse events (TRAEs) of grade 3 or worse occurred in 14 (30%) of 46 patients during neoadjuvant treatment and in seven (19%) of 37 during adjuvant treatment. The most common grade 3 or worse TRAEs were increased lipase and febrile neutropenia (three [7%] each) during neoadjuvant treatment, and elevated serum lipase (four [7%]) and elevated serum amylase (three [8%]) during adjuvant treatment. Serious TRAEs included elevated serum lipase and neutropenia (one [2%] each) during neoadjuvant treatment, and elevated serum lipase (one [3%]) during adjuvant treatment. No treatment-related surgery delays, deaths, or unexpected long-term toxicities were reported., Interpretation: Perioperative chemoimmunotherapy showed a promising long-term benefit with no concerning safety data, reinforcing its use in resectable stage IIIA NSCLC., Funding: Bristol-Myers Squibb, Spanish Ministry of Science, Instituto de Salud Carlos III, European Union., Competing Interests: Declaration of interests MP reports non-financial support (reagents for T-cell receptor sequencing) from ThermoFisher Scientific; grants, consulting fees, and non-financial support from Bristol Myers Squibb, Roche, and AstraZeneca; and consulting fees from MSD and Takeda; outside the submitted work. EN reports grants from Roche, Pfizer, Bristol Myers Squibb, Merck, and Nanostring; consulting fees from Roche, Bristol Myers Squibb, Merck Sharpe & Dohme, Merck-Serono, Sanofi, Pfizer, Lilly, Amgen, Janssen, Daiichi-Sankyo, Boehringer-Ingelheim, AstraZeneca, Takeda, Sanofi, Pierre Fabre, Qiagen, and Bayer; payment of honoraria from Roche, Bristol Myers Squibb, Merck Sharpe & Dohme, Sanofi, Pfizer, Lilly, Amgen, Janssen, Daiichi-Sankyo, Boehringer-Ingelheim, AstraZeneca, Takeda, Sanofi, and Qiagen; support for attending meetings or travel from Takeda, MSD, Janssen, and Roche; and participation on advisory boards for Apollomics, Roche, and Pfizer. AI reports consulting fees from Pfizer, Amgen, and Astra Zeneca; payment for expert testimony from Bristol Myers Squibb, Roche, Pfizer, Astra Zeneca, and Takeda; support for attending meetings or travel from Roche, Takeda, and Pfizer; and participation on advisory boards for Roche and Bristol Myers Squibb. RG-C reports consulting fees from Bristol Myers Squibb, MSD, Roche, Pfizer, and AstraZeneca. MD reports consulting fees from AstraZeneca, Bristol Myers Squibb, MSD Oncology, Pfizer, Roche, and Takeda; and support for attending meetings or travel from AstraZeneca, MSD Oncology, Pfizer, and Takeda. BM reports consulting fees from Astra Zeneca and Amgen; payment or honoraria from Roche, Bristol Myers Squibb, and MSD; and support for attending meetings or travel from MSD and AstraZeneca. MM reports grants from Roche and Astra Zeneca; payment of honoraria from Roche, AstraZeneca, MSD, Pfizer, Helsinn, Cassen, Amgen, Janssen, Sanofi, Pierre Fabre, Bristol Myers Squibb, and Takeda; and support for attending meetings or travel from MSD, Roche, and AstraZeneca. DR-A reports honoraria for lectures from MSD, Roche, Bristol Myers Squibb, Novartis, Takeda, Lilly, and AstaZeneca; support for attending meetings or travel from Roche, MSD, Novartis, and Sanofi; and participation on advisory boards for Merck Sharpe & Dohme, Regeneron, Bristol Myers Squibb, GSK, and Lilly. AM-M reports consulting fees from AstraZeneca/MedImmune, Bristol Myers Squibb, F. Hoffmann La Roche, Merck Sharpe & Dohme, MSD Oncology, Pfizer, and Janssen; payment for expert testimony from AstraZeneca, MedImmune, Bristol Myers Squibb, and F. Hoffmann La Roche; support for attending meetings or travel from AstraZeneca, MedImmune, Bristol-Myers Squibb, F. Hoffmann La Roche, Merck Sharpe & Dohme, MSD Oncology, Pfizer, Janssen, and Lilly; and participation on advisory boards for AstraZeneca, MedImmune, Merck Sharpe & Dohme, F. Hoffmann La Roche, and Bristol-Myers Squibb. JdC reports consulting fees from AstraZeneca, Bristol Myers Squibb, Roche, MSD, Boehringer, Janssen, Lilly, Sanofi, Takeda, Pfizer, and GSK; support for attending meeting or travel from AstraZeneca, MSD, and Roche; participation on advisory boards for AstraZeneca, Bristol Myers Squibb, Roche, MSD, Glaxo, Janssen, and Gilea; and speaker's bureau fees from AstraZeneca/MedImmune, Bristol-Myers Squibb, F. Hoffmann La Roche, Merck Sharpe & Dohme, MSD Oncology, Pfizer, and Janssen. DG reports payment or honoraria from Astra Zeneca and Bristol Myers Squibb. VC reports consulting fees from Roche, AstraZeneca, MSD, Bristol Myers Squibb, Takeda, Sanofi, and Amgen; payment or honoraria from Roche, AstraZeneca, MSD, Bristol Myers Squibb, Takeda, SanofiI, and Amgen; and support for attending meetings or travel from AstraZeneca, Roche, MSD, and Takeda. RP reports payment or honoraria from Guardant Health and Pfizer; and support for attending meetings or travel from Merck Sharpe & Dohme; participation on an advisory board for AstraZeneca. AR reports payment or honoraria from Illumina, Health in Code, and ThermoFisher Scientific; support for attending meetings or travel from ThermoFisher Scientific, Bristol Myers Squibb Foundation, and Takeda; and advisory board participation for Takeda. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Loss of human leukocyte antigen (HLA) class I expression and loss of heterozygosity (LOH) are common events implicated in the primary resistance of non-small cell lung cancer (NSCLC) to immunotherapy. However, there is no data on perioperative chemoimmunotherapy (ChIO) efficacy or response mechanisms in the context of HLA class I defects., Methods: Baseline HLA class I tumor status (HLA-deficient (HLA-DEF) or HLA-proficient (HLA-PRO)) was determined by DNA LOH combined with immunohistochemistry for protein levels in tissue of 24 patients with NSCLC treated with perioperative nivolumab plus chemotherapy from NADIM trial (NCT03081689). We integrated HLA tumor status with molecular data (programmed death-ligand 1 (PD-L1), TMB, TCR repertoire, TILs populations, bulk RNA-seq, and spatial transcriptomics (ST)) and clinical outcomes (pathological response and survival data) to study the activity of perioperative ChIO considering HLA class I defects., Results: HLA-DEF tumors comprised 41.7% of analyzed tumors and showed a desert-like microenvironment at baseline, with lower PD-L1 levels and reduced immune infiltrate. However, perioperative ChIO induced similar complete pathological response (CPR) rates in both HLA-DEF and PRO tumors (50% and 60% respectively, p=0.670), as well as 3-year survival rates: Progression-free survival (PFS) and overall survival (OS) of 70% (95% CI 32.9% to 89.2%) for HLA-DEF, and PFS 71.4% (95% CI 40.6% to 88.2%) and OS 92.9% (95% CI 59.1% to 99.0%) for HLA-PRO (log-rank PFS p=0.909, OS p=0.137). Proof-of-concept ST analysis of a CPR HLA-DEF tumor after ChIO showed a strong immune response with tertiary lymphoid structures (TLS), CD4+T cells with HLA class II colocalization, and activated CD8+T cells., Conclusions: Our findings highlight the activity of perioperative ChIO, and the potential role of TLS and T-cell immune response, in NSCLC HLA-DEF tumors., Competing Interests: Competing interests: VC reports consulting fees from Roche, AstraZeneca, MSD, BMS, Takeda, Sanofi, Agmen; payment or honoraria from Roche, AstraZeneca, MSD, BMS, Takeda, Sanofi, Agmen, Janssen, Regeneron and Pfizer; and support for attending meetings and/or travel from Roche, AstraZeneca, MSD, and Takeda outside the submitted work. EN reports grants from Roche, BMS, Pfizer, and Merck Serono; consulting fees and payment or honoraria form Roche, BMS, MSD, Merck Serono, Sanofi, Pfizer, Lilly, Amgen, Janssen, Daiichi Sankyo, Boehringer Ingelheim, AstraZeneca, Takeda, Sanofi, Pierre Fabre, Qiagen; payment or honoraria from Bayer; and advisory board from MSD, Roche, Apollomics, Daiichi and Transgene outside the submitted work. AM-M reports consulting fees, payment or honoraria and support for attending meetings and/or travel from AstraZeneca/MedImmune, BMS, F Hoffmann-La Roche AG, MSD, MSD Oncology, Pfizer; Steering Committee Member of AstraZeneca/MedImmune; support for attending meetings and/or travel from Lilly; and advisory board from AstraZeneca/MedImmune, MSD, BMS, and F Hoffmann-La Roche AG outside the submitted work. AI reports consulting fees from Pfizer, Amgen, AstraZeneca, and Roche; payment form expert testimony form BMS, Roche, Pfizer, AstraZeneca, and Takeda; support for attending meetings and/or travel from Roche, Takeda, and Pfizer; and advisory abroad from Roche and BMS outside the submitted work. BM reports payment or honoraria from Roche, BMS, MSD, Boehringer Ingelheim, and Pfizer outside the submitted work. SV reports payment or honoraria from Merck GmbH, MSD, BMS, Takeda, AstraZeneca, and Roche; support for attending meetings and/or travel from OSE Immunotherapeutics, Roche, and GMS; and advisory board from Merck GmbH, Puma Biotech, Takeda, Ipsen, AbbVie, Roche, and AstraZeneca outside the submitted work. IBA reports payment or honoraria from AstraZeneca, BMS, Janssen Cilag, Lilly, MSD, Roche, Sanofi, and Takeda; as well as support for attending meetings and/or travel from MSD and AstraZeneca outside the submitted work. JdC reports consulting fees from AstraZeneca, BMS, Roche, MSD, Boehringer Ingelheim, Janssen, Lilly, Sanofi, Takeda, Pfizer, and Glaxo; payment or honoraria from AstraZeneca, BMS, Roche, MSD, Pfizer, Janssen, Takeda, and Sanofi; support for attending meetings and/or travel from AstraZeneca, MSD, and Roche; and advisory Board fees from AstraZeneca, BMS, Roche, MSD, Glaxo, Janssen, and Gilead outside the submitted work. MCo reports consulting fees from Novartis, AstraZeneca, Boehringer Ingelheim, Roche, BMS, Lilly, MSD, Takeda, Pfizer, Kyowa, Sanofi, and Janssen, as well as payment or honoraria from Novartis, AstraZeneca, Boehringer Ingelheim, Roche, BMS, Lilly, MSD, Takeda, Kyowa, Pierre Fabre, Novocure, Sanofi, and Janssen outside the submitted work. JM-L reports payment or honoraria from Roche, BMS, and EUSA Pharma, as well as support for attending meetings and/or travel from Roche outside the submitted work. MP reports consulting fees from BMS, AstraZeneca, MSD, Roche, Takeda. Support for attending meetings and/or travel and payment or honoraria from BMS, AstraZeneca, MSD, Roche, and Takeda outside the submitted work. No disclosures were reported by the other authors., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Advances in the multidisciplinary care of early stage resectable NSCLC (rNSCLC) are emerging at an unprecedented pace. Numerous phase 3 trials produced results that have transformed patient outcomes for the better, yet these findings also require important modifications to the patient treatment journey trajectory and reorganization of care pathways. Perhaps, most notably, the need for multispecialty collaboration for this patient population has never been greater. These rapid advances have inevitably left us with important gaps in knowledge for which definitive answers will only become available in several years. To this end, the International Association for the Study of Lung Cancer commissioned a diverse multidisciplinary international expert panel to evaluate the current landscape and provide diagnostic, staging, and therapeutic recommendations for patients with rNSCLC, with particular emphasis on patients with American Joint Committee on Cancer-Union for International Cancer Control TNM eighth edition stages II and III disease. Using a team-based approach, we generated 19 recommendations, of which all but one achieved greater than 85% consensus among panel members. A public voting process was initiated, which successfully validated and provided qualitative nuance to our recommendations. Highlights include the following: (1) the critical importance of a multidisciplinary approach to the evaluation of patients with rNSCLC driven by shared clinical decision-making of a multispecialty team of expert providers; (2) biomarker testing for rNSCLC; (3) a preference for neoadjuvant chemoimmunotherapy for stage III rNSCLC; (4) equipoise regarding the optimal management of patients with stage II between upfront surgery followed by adjuvant therapy and neoadjuvant or perioperative strategies; and (5) the robust preference for adjuvant targeted therapy for patients with rNSCLC and sensitizing EGFR and ALK tumor alterations. Our primary goals were to provide practical recommendations sensitive to the global differences in biology and resources for patients with rNSCLC and to provide expert consensus guidance tailored to the individualized patient needs, goals, and preferences in their cancer care journey as these are areas where physicians must make daily clinical decisions in the absence of definitive data. These recommendations will continue to evolve as the treatment landscape for rNSCLC expands and more knowledge is acquired on the best therapeutic approach in specific patient and disease subgroups., Competing Interests: Disclosure Dr. Spicer reports receiving grants or contracts from AstraZeneca, Bristol-Myers Squibb, Merck Sharp & Dohme, Amgen, Roche, Regeneron, and Pfizer; consulting fees from AstraZeneca, Bristol-Myers Squibb, Eisai, Daiichi Sankyo, and Merck Sharp & Dohme; honoraria from AstraZeneca, Amgen, Bristol-Myers Squibb, Merck Sharp & Dohme, and Pfizer; meeting support from AstraZeneca, Bristol-Myers Squibb, and Merck Sharp & Dohme; data safety monitoring board for AstraZeneca; and receipt of other services from AstraZeneca, Bristol-Myers Squibb, and Merck Sharp & Dohme, outside the submitted work. Dr. Cascone reports receiving speaker fees and/or honoraria from the American Society for Clinical Oncology Post, AstraZeneca, Bio Ascend, Bristol-Myers Squibb, Clinical Care Options, IDEOlogy Health, Medical Educator Consortium, Medscape, OncLive, PEAK Medical, PeerView, Physicians' Education Resource, Society for Immunotherapy of Cancer, and Targeted Oncology; advisory role/consulting fees from Arrowhead Pharmaceuticals, AstraZeneca, Bristol-Myers Squibb, Mark Foundation for Cancer Research, Merck, oNKo-innate, Pfizer, RAPT Therapeutics, and Regeneron; and institutional research funding from AstraZeneca and Bristol-Myers Squibb, outside the submitted work. Dr.Ahn reports receiving consulting fees from AstraZeneca, Alpha Pharmaceuticals, Genxin, and Pfizer; and honoraria from Takeda, Roche, Merck, Merck Sharp & Dohme, AstraZeneca, Amgen, Boronoi, Arcus, Daiichi Sankyo, Bayer, and Janssen, outside the submitted work. Dr.Dacic reports receiving consulting fees from AstraZeneca, Genentech, and Medscape, outside the submitted work. Dr. Felip reports receiving consulting fees from AbbVie, Amgen, AstraZeneca, Bayer, BeiGene, Boehringer Ingelheim, Bristol-Myers Squibb, Eli Lilly, F. Hoffmann-La Roche, Genmab, GlaxoSmithKline, Janssen, Merck Serono, Merck Sharp & Dohme, Novartis, Peptomyc, Pfizer, Regeneron, Sanofi, Takeda, Turning Point, and Daiichi Sankyo; honoraria from Amgen, AstraZeneca, Bristol-Myers Squibb, Daiichi Sankyo, Eli Lilly, F. Hoffmann-La Roche, Genentech, Janssen, Medical Trends, Medscape, Merck Serono, Merck Sharp & Dohme, PeerVoice, Pfizer, Sanofi, Takeda, and Touch Oncology; travel support from AstraZeneca, Janssen, and Roche; and other from Grifols as an independent member of the board, outside the submitted work. Dr. Forde reports receiving grants or contracts from AstraZeneca, Bristol-Myers Squibb, Novartis, Regeneron, and BioNTech; consulting fees from Ascendis, AstraZeneca, Bristol-Myers Squibb, Curevac, Novartis, Regeneron, G1, Genlux, Genentech, Gritstone, Merck, Janssen, F Star, Sanofi, Amgen, Fosun, Teva, Synthekine, Flame, Iteos, and Tavotek. Dr. Higgins reports receiving grants or contracts from Jazz Pharmaceuticals, RefleXion Medicalx; consulting fees from AstraZeneca and Janssen; positions on the NRG Oncology Board of Directors and RTOG Foundation Board of Directors; and stock or stock options in Picture Health. Dr. Kris reports receiving grant or contracts from BerGenBio, Merus, AstraZeneca, Mirati, Pfizer, Janssen, Sanofi, and Novartis; honoraria from Pfizer and AstraZeneca; and personal fees from AstraZeneca and Roche/Genentech, outside the submitted work. Dr. Mitsudomi reports receiving grants or contracts from Boehringer Ingelheim, AstraZeneca, Chugai, Pfizer, Ono, Daiichi Sankyo, and Eli Lilly; consulting fees from AstraZeneca, Novartis, Chugai, Boehringer Ingelheim, Pfizer, Merck Sharp & Dohme, Thermo Fisher, Roche Diagnostics, Bristol-Myers Squibb, Ono Pharmaceuticals, Taiho, Takeda, Janssen, Daiichi Sankyo, and Regeneron; honoraria from AstraZeneca, Chugai, Boehringer Ingelheim, Pfizer, Taiho, Eli Lilly, Daiichi Sankyo, Thermo Fisher, Merck Sharp & Dohme, Bristol-Myers Squibb, Ono Pharmaceuticals, Invitae, Guardant, Novartis, Amgen, Merck biopharma, and Kyorin; data safety monitoring board for Taiho Pharmaceutical, outside the submitted work. Dr. Provencio reports receiving grants or contracts from Bristol-Myers Squibb, AstraZeneca, Roche, Janssen, and Takeda; consulting fees from Bristol-Myers Squibb, Roche, AstraZeneca, Merck Sharp & Dohme, and Takeda; honoraria from Bristol-Myers Squibb, Takeda, Roche, AstraZeneca, and Merck Sharp & Dohme; and meeting attendance support from Merck Sharp & Dohme, Roche, and Bristol-Myers Squibb, outside the submitted work. Dr. Senan reports receiving grants or contracts from AstraZeneca, Merck Sharp & Dohme, and Bristol-Myers Squibb; consulting fees from AstraZeneca and Bristol-Myers Squibb; honoraria from AstraZeneca; advisory board participation for AstraZeneca and Merck Sharp & Dohme; and membership on ETOP scientific committee, outside the submitted work. Dr. Solomon reports receiving travel support from IASLC to attend meeting related to manuscript; consulting fees from AstraZeneca, Bristol-Myers Squibb, Eli Lily, Merck Sharp & Dohme, Pfizer, Roche, GlaxoSmithKline, Janssen, and Amgen; honoraria from AstraZeneca, Bristol-Myers Squibb, Merck Sharp & Dohme, Pfizer, Roche, and GlaxoSmithKline; unpaid leadership roles at the IASLC, Thoracic Oncology Group of Australasia, and Cancer Council of Victoria. Dr. Tsao reports receiving travel support from IASLC to attend meeting related to manuscript; grants or contracts from AstraZeneca, Bayer, and Lily; consulting fees from AstraZeneca, Bayer, Amgen, AbbVie, Regeneron, Sanofi, Daiichi Sankyo, and Lily; honoraria from AbbVie and Sanofi; and board of directors for IASLC. Dr. Tsuboi reports receiving grant from AstraZeneca KK, Ono Pharmaceutical Co., Ltd., Bristol-Myers Squibb KK, Novartis Japan, BMG KK, MiRXES, and Johnson & Johnson Japan; honoraria from Amgen KK, Johnson & Johnson Japan, AstraZeneca KK, Eli Lilly Japan, Chugai Pharmaceutical Co., Ltd., Taiho Pharma, Medtronic Japan, Ono Pharmaceutical Co., Ltd., Merck Sharp & Dohme KK, Bristol-Myers Squibb KK, Daiichi Sanko KK, and Novalis; advisory committee participation for Chugai Pharmaceutical Co., Ltd., and AstraZeneca KK; and Board of Directors for Japan Lung Cancer Society (JLCS), Bronchology Committee Chair for JLCS, and Educational Committee working group chair for IASLC, outside the submitted work. Dr. Wakelee reports receiving grants or contracts from ACEA Biosciences, Arrys Therapeutics, AstraZeneca, Bristol-Myers Squibb, Clovis Oncology, Genentech/Roche, Merck, Novartis, SeaGen, Xcovery, and Helsinn; advisory board participation for AstraZeneca, Blueprint, Mirati, Merck, and Genentech/Roche; and leadership positions on the IASLC Board of Directors and ECOG-ACRIN executive committee. Dr. Wu reports receiving grants and contracts form AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Henqrui, and Roche; honoraria from AstraZeneca, Beigene, Boehringer Ingelheim, Bristol-Myers Squibb, Eli Lilly, Merck Sharp & Dohme, Pfizer, Roche, and Sanofi; and unpaid leadership role for Chinese Thoracic Oncology Group. Dr. Yang reports receiving personal fees and other from Amgen, Bayer Boehringer Ingelheim, Bristol-Myers Squibb, Daiichi Sankyo, Merck KGaA, Merck Sharp & Dohme, Novartis, Roche/Genentech, Takeda Oncology, and Yuhan Pharmaceuticals; grants, personal fees, and other from AstraZeneca; other from Eli Lilly; personal fees from Ono Pharmaceuticals and Pfizer; and other from JNJ, Puma Technology, Gilead, and GlaxoSmithKline, outside the submitted work. Dr. Zhou reports receiving consulting fees from Innovent Biologics, Hengrui, Qila, and TopAlliance Biosciences; honoraria from Lily China, Sanofi, Boehringer Ingelheim, Roche, Merck Sharp & Dohme, Qilu, Hengrui, Innovent Biologics, Alice, C-Stone, LUYE Pharma, TopAlliance Biosciences, Amoy Diagnostics, and AnHeart. Dr. Kelly reports receiving grants from AstraZeneca, during the conduct of the study; grants and personal fees from Genentech and Bristol-Myers Squibb; and personal fees from AstraZeneca, outside the submitted work. The remaining authors declare no conflict of interest., (Copyright © 2024 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.)

Background: Early detection is crucial to improve lung cancer survival rates. Delays in diagnosis might negatively impact the prognosis of the disease. This study aims to analyze the diagnostic delay in lung cancer patients and describe if there is an association between delay and survival., Methods: The data source used was the Thoracic Tumor Registry of the Spanish Lung Cancer Group. This analysis was restricted to lung cancer cases with information on the first date of consultation by symptoms and date of diagnosis. The delay was calculated as the number of days between the two dates. A descriptive analysis was performed, and ordinal logistic regressions were fitted with delay as the dependent variable. Kaplan-Meier survival analysis and Cox regression were performed., Results: 22,755 lung cancer cases were included. Never smokers were 1.16 (95%CI: 1.06-1.27) times more likely to register longer delay than smokers. Stage 0-I-II cases had a 3.09 (95%CI: 2.88-3.32) higher risk of longer delay compared to III-IV stages. Overall, 5-year survival rate after diagnosis was 23.64% (95%CI: 22.88-24.41). In those categorized as having the shortest delay 5-year survival was 17.67% (95%CI: 16.31-19.07) and in the extreme delay it was 32.98% (95%CI: 31.28-34.69) (p<0.001). Adjusted mortality risk was higher in those with the shortest delay (HR 1.36, CI95%: 1.30-1.43) in comparison with the extreme delay., Conclusions: Diagnostic delay is short among Spanish lung cancer patients, indicating a relatively quick diagnostic process. Extreme delays appear to be associated with higher survival rates, possibly attributed to slow-growing tumors, earlier stage at diagnosis or basically the natural history of this disease., (Copyright © 2024 The Author(s). Published by Elsevier España, S.L.U. All rights reserved.)

Objectives: Lung Cancer (LC) is a multifactorial disease for which the role of genetic susceptibility has become increasingly relevant. Our aim was to use artificial intelligence (AI) to analyze differences between patients with LC based on family history of cancer (FHC)., Materials and Methods: From August 2016 to June 2020 clinical information was obtained from Thoracic Tumors Registry (TTR), a nationwide database sponsored by the Spanish Lung Cancer Group. In addition to descriptive statistical analysis, an AI-assisted analysis was performed. The German Technical Information Library supported the merging of data from the electronic medical records and database of the TTR. The results of the AI-assisted analysis were reported using Knowledge Graph, Unified Schema and descriptive and predictive analyses., Results: Analyses were performed in two phases: first, conventional statistical analysis including 11,684 patients of those 5,806 had FHC. Median overall survival (OS) for the global population was 23 months (CI 95 %: 21.39-24.61) in patients with FHC versus 21 months (CI 95 %: 19.53-22.48) in patients without FHC (NFHC), p < 0.001. The second AI-assisted analysis included 5,788 patients of those 939 had FHC. 58.48 % of women with FHC had LC. 9.53 % of patients had an EGFR or HER2 mutation or ALK translocation and at least one relative with cancer. A family history of LC was associated with an increased risk of smoking-related LC. Non-smokers with a family history of LC were more likely to have an EGFR mutation in NSCLC. In Bayesian network analysis, 55 % of patients with a family history of LC and never-smokers had an EGFR mutation., Conclusion: In our population, the incidence of LC in patients with a FHC is higher in women and younger patients. FHC is a risk factor and predictor of LC development, especially in people ≤ 50 years. These results were confirmed by conventional statistics and AI-assisted analysis., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. Calvo reported receiving personal fees from Roche, Bristol Myers Squibb, Merck Sharp & Dohme, AstraZeneca, Takeda, Pfizer, Sanofi and AMGEN outside the submitted work; being a consultant or advisor and speakerś bureau for Roche, Bristol Myers Squibb/Celgene, Merck Sharp & Dohme, AstraZeneca, Takeda Sanofi and AMGEN and receiving travel, accommodations, and expenses from Takeda, Roche, Bristol Myers Squibb and Merck Sharp & Dohme. Dr. Carcereny reported receiving consulting fees from AstraZeneca, Novartis, Boehringer Ingelheim, Roche, Bristol Myers Squibb, Merck Sharp & Dohme; payment or honoraria from AstraZeneca, Roche, Boehringer Ingelheim, Bristol Myers Squibb, Pfizer and receiving travel, accommodations, and expenses from Roche, Merck Sharp & Dohme, Takeda, Bristol Myers Squibb and Pfizer. Dr. Cobo reported receiving consulting fees from Novartis, AstraZeneca, Boehringer-Ingelheim, Roche, Bristol Myers Squibb, Merck Sharp & Dohme, Lilly, Takeda, Pfizer, Kyowa, Sanofi, Jansen; payment or honoraria from Novartis, AstraZeneca, Boehringer-Ingelheim, Roche, Bristol Myers Squibb, Merck Sharp & Dohme, Lilly, Takeda, Kyowa, Pierre-Fabre, Novocure, Sanofi, Jansen and receiving travel, accommodations, and expenses from AstraZeneca, Boehringer-Ingelheim, Roche, Bristol Myers Squibb, Merck Sharp & Dohme, Lilly, Pierre-Fabre and being advisor for Gilead. Dr. López-Castro reported receiving consulting fees from Takeda, Roche, Pfizer, Novartis, Pierre-Fabre, Bristol Myers Squibb; payment or honoraria from Pfizer, Pierre-Fabre, Takeda, Roche, Novartis Jansen and receiving travel, accommodations, and expenses from Roche, Takeda, Novartis and Merck Sharp & Dohme. Dr. Bernabé reported receiving grant from Roche; payment or honoraria from Roche, Merck Sharp & Dohme, Pfizer, AMGEN, Takeda, Astrazeneca and receiving travel, accommodations, and expenses from Roche, Bristol Myers Squibb and being advisor for Takeda, Roche, Bristol Myers Squibb and Astrazeneca. Dr. Garcia-Campelo reported receiving consulting fees from AMGEN, AstraZeneca, Bayer, Bristol Myers Squibb, Boehringer Ingelheim, Roche, Janssen, Lilly, Merck Sharp & Dohme, Pfizer, Sanofi, Takeda, Pfizer; payment or honoraria from AMGEN, AstraZeneca, Bayer, Bristol Myers Squibb, Boehringer Ingelheim, Roche, Janssen, Lilly, Merck Sharp & Dohme, Pfizer, Sanofi, Takeda and receiving travel, accommodations, and expenses from AstraZeneca, Roche, Pfizer and being advisor for AstraZeneca. Dr. del Barco reported receiving travel, accommodations and expenses from Merck Sharp & Dohme. Dr. Bosch-Barrera reported receiving grants from Pfizer and Roche outside the submitted work; payment or honoraria from Astrazeneca, Pfizer, Merck Sharp & Dohme, Bristol Myers Squibb, Roche, Sanofi and receiving travel, accommodations, and expenses from Merck Sharp & Dohme, Roche and Takeda. Dr. Provencio reported receiving grants from Bristol Myers Squibb, Takeda, Roche, Pfizer, and Merck Sharp & Dohme outside the submitted work; being a consultant or advisor for Bristol Myers Squibb, Roche, Merck Sharp & Dohme, AstraZeneca, and Takeda; being on the speakers’ bureau for Bristol Myers Squibb, Roche, AstraZeneca, and Merck Sharp & Dohme; receiving research funds from Pierre Fabre, Roche, Boehringer Ingelheim, and Bristol Myers Squibb; and receiving travel, accommodations, and expenses from Roche, Bristol Myers Squibb, and AstraZeneca. The remaining authors declare no conflict of interest., (Copyright © 2024. Published by Elsevier B.V.)

Background: Immunotherapy-based treatments have demonstrated high efficacy in patients with advanced and locally advanced non-small-cell lung cancer (NSCLC). BRAF mutations affect a small but significant fraction of NSCLC. The efficacy of these therapies in this subgroup of patients is unknown., Materials and Methods: Plasma and tissue samples from 116 resectable stage IIIA/B NSCLC patients, included in NADIM and NADIM II clinical trials (NADIM cohort), and from a prospective academic cohort with 84 stage IV NSCLC patients (BLI-O cohort), were analyzed by next-generation sequencing., Results: The p.G464E, p.G466R, p.G466V, p.G469V, p.L597Q, p.T599I, p.V600E (n = 2) BRAF mutations, were identified in four (3.45 %) samples from the NADIM cohort, all of which were cases treated with neoadjuvant chemoimmunotherapy (CH-IO), and four (4.76 %) samples from the BLI-O cohort, corresponding to cases treated with first-line immunotherapy (n = 2) or CH-IO (n = 2). All these patients were alive and had no evidence of disease at data cut-off. Conversely, patients with BRAF wild-type (wt) tumors in the BLI-O cohort had a median progression-free survival (PFS) of 5.49 months and a median overall survival (OS) of 12.00 months (P-LogRank = 0.013 and 0.046, respectively). Likewise, PFS and OS probabilities at 36 months were 60.5 % and 76.1 % for patients with BRAF-wt tumors in the NADIM cohort. The pathological complete response (pCR) rate after neoadjuvant CH-IO in patients with BRAF-positive tumors (n = 4) was 100 %, whereas the pCR rate in the BRAF-wt population was 44.3 % (RR: 2.26; 95 % CI: 1.78-2.85; P < 0.001)., Conclusion: BRAF mutations may be a good prognostic factor for advanced and locally advanced NSCLC patients undergoing immunotherapy-based treatments., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: M. Provencio declares consulting fees, payment for lectures, presentations or speakers bureaus and support for attending meetings and/or travel from BRISTOL-MYERS SQUIBB, Astra Zeneca, MSD, Roche, Takeda. This author has also declared that he have a pending patent (n° EP 22 382 701.5). R. Serna-Blasco declares to be in possession of a pending patent (n° EP 22 382 701.5). E. Nadal declares Grants or contracts from Roche, Pfizer, Bristol-Myers Squibb and Merck Serono; consulting fees from Roche, Bristol Myers Squibb, Merck Sharp Dohme, Merck-Serono, Sanofi, Pfizer, Lilly, Janssen, AMGEN, Daiichi-Sankyo, Boehringer-Ingelheim, AstraZeneca, Takeda, Sanofi, Pierre Fabre, Qiagen, and Bayer; payment for lectures, presentations or speakers bureaus from Roche, Bristol Myers Squibb, Merck Sharp Dohme, Merck-Serono, Sanofi, Pfizer, Lilly, Janssen, Amgen, Boehringer-Ingelheim, AstraZeneca, Takeda, Sanofi, Pierre Fabre and Qiagen; support for attending meetings and/or travel from Roche, Takeda and Pfizer; and Participation on data safety Monitoring board or advisory board from Roche, Apollomics and MSD. M.P. Diz Taín declares Payment or honoraria for lectures, presentations or speakers bureaus from BRISTOL-MYERS SQUIBB, Astra-Zeneca, Roche, MSD, Takeda, Pfizer and Amgen; support for attending meetings and/or travel from BRISTOL-MYERS SQUIBB, Roche, MSD and Takeda; Participation on a Data Safety Monitoring Board or Advisory Board from BRISTOL-MYERS SQUIBB, Astra-Zeneca, and Boehringer Ingelheim; and other financial or non-financial interests from Astra-Zeneca, Roche, Mirati, and Pfizer. B. Massuti declares consulting fees and support for attending meetings and/or travel from Bristol-Myers Squibb, Takeda, Merck Sharpe and Dohme. J.L. González Larriba declares consulting fees from MSD, Janssen Cilag, Bristol Myers Squibb, Boehringer Ingelheim, and AMGEN; Payment or honoraria for lectures, presentations or speakers bureaus from MSD, Astra Zeneca, Roche, Pfizer, Janssen-Cilag, Novartis, Astella Pharma, and Bristol-Myers Squibb; Support for attending meetings and/or travel from MSD, Takeda, Bristol-Myers Squibb, Roche, Pfizer, and Janssen-Cilag. A. Insa declares Payment or honoraria for lectures, presentations or speakers bureaus from AMGEN, Bristol-Myers Squibb, Roche, and Takeda; Support for attending meetings and/or travel from Roche, Pfizer, and MSD; Participation on a Data Safety Monitoring Board or Advisory Board from Astra Zeneca, Sanofi, and Pfizer. A. Sánchez-Hernández declares Payment or honoraria for lectures, presentations or speakers bureaus from Roche, Lilly, MSD, Sanofi, Astra Zeneca, Janssen, Takeda, Merck, Novartis, Pfizer, and Bristol-Myers Squibb; Support for attending meetings and/or travel from Roche, Sanofi, MSD Takeda, Janssen, Pfizer, and Bristol-Myers Squibb. R. García-Campelo declares Grants or contracts from Bristol-Myers Squibb, Astra Zeneca, and MSC; consulting fees from Roche, Bristol-Myers Squibb, MSD, Sanofi, Takeda, Pfizer, Regeneron, AMGEN, and Astra Zeneca. J. Rogado declares Payment or honoraria for lectures, presentations or speakers bureaus from Roche, Astra Zeneca, MSD, MERCK, Ferrer, Persan Farma, Fresenius Kabi, and Sanofi; Support for attending meetings and/or travel from Roche, MSD, Bristol-Myers Squibb, Astra Zeneca, and Lilly; Participation on a Data Safety Monitoring Board or Advisory Board from Fresenius Kabi, MSD, Sanofi. A. Martínez-Martí declares consulting fees from AstraZeneca/MedImmune, Bristol-Myers Squibb, F. Hoffmann La Roche AG, MSD, and Pfizer; Payment or honoraria for lectures, presentations, speakers bureaus from AstraZeneca/MedImmune, Bristol-Myers Squibb, F. Hoffmann La Roche AG, MSD, MSD, and Pfizer; Payment for expert testimony from AstraZeneca/MedImmune; Support for attending meetings and/or travel from AstraZeneca/MedImmune, Bristol-Myers Squibb, F. Hoffmann La Roche AG, MSD, Pfizer, and Lilly; Participation on a Data Safety Monitoring Board or Advisory Board from AstraZeneca/MedImmune, MSD, F. Hoffmann La Roche, Bristol-Myers Squibb. J. Bosch-Barrera declares consulting fees from Sanofi and Roche; Payment or honoraria for lectures, presentations or speakers bureaus from Roche, Bristol-Myers Squibb, Astra Zeneca, and Pfizer; Support for attending meetings and/or travel from Takeda and MSD. R. Bernabé-Caro declares an investigational grant Roche; Payment or honoraria for lectures, presentations, speakers bureaus from Roche, Bristol-Myers Squibb, Pfizer, MSD, Amgen, Takeda, and Astra Zeneca; Participation on a Data Safety Monitoring Board or Advisory Board from Takeda, Roche, Bristol-Myers Squibb, and Astra Zeneca. J. de Castro Carpeño declares consulting from fees Astra Zeneca, Bristol Myers Squibb, Hoffmann- La Roche, MSD, Boehringer Ingelheim, Janssen, Lilly, Sanofi, Takeda, Pfizer, and Glaxo; Payment or honoraria for lectures, presentations, speakers bureaus from Astra Zeneca, Bristol Myers Squibb, Hoffmann- La Roche, MSD, Pfizer, Janssen, Takeda, and Sanofi; Support for attending meetings and/or travel from Astra Zaneca, MSD, and Hoffmann- La Roche; Participation on a Data Safety Monitoring Board or Advisory Board from Astra Zeneca, Bristol Myers Squibb, Hoffmann- La Roche, MSD, Glaxo, Janssen, Gilead, and Sanofi. N. Reguart declares Payment or honoraria for lectures, presentations or speakers bureaus from MSD, Bristol Myers Squibb, Roche, Boehringer Ingelheim, Guardant Health, Bayer, Merck, Pfizer, Takeda, Novartis, Astra-Zeneca, Janssen Oncology, Sanofi, Eli Lilly, and Amgen; Support for attending meetings and/or travel from Roche, Takeda, and MSD. M. Dómine declares consulting fees and Payment or honoraria for lectures, presentations or speakers bureaus from Astra Zeneca, Bristol-Myers Squibb, MSD, Pfizer, Roche, and Takeda; Support for attending meetings and/or travel from Astra Zeneca, MSD, Pfizer, and Takeda. M. Majem declares Grants or contracts from Roche and Astra Zeneca; Payment or honoraria for lectures, presentations or speakers bureaus from Roche, Astra Zeneca, MSD, Pfizer, Helsinn, Cassen, AMGEN, Janssen, Sanofi, Pierre Fabre, Bristol-Myers Squibb, and Takeda; Support for attending meetings and/or travel from Astra Zeneca, MSD, and Roche. A. Estival declares Payment or honoraria for lectures, presentations or speakers bureaus from MSD, Pharmamar, Astra Zeneca, Takeda, Roche, and GSK; Support for attending meetings and/or travel from MSD, Boehringer Ingelheim, and Pharmamar; Participation on a Data Safety Monitoring Board or Advisory Board from Roche and MSD. A. López Martín declares Payment or honoraria for lectures, presentations, speakers bureaus from GSK, Bristol-Myers Squibb, and Astra Zeneca; Support for attending meetings and/or travel from Pfizer and Takeda. M. A. Sala González declares Payment or honoraria for lectures, presentations or speakers bureaus from Takeda and Roche; Support for attending meetings and/or travel from Roche and PharmaMar. M. Cobo declares consulting fees from Novartis, Roche, Astra Zeneca, Bristol-Myers Squibb, Boehringer-Ingelheim, MSD, Lilly, Takeda, Pfizer, Kyowa, Sanofi, and Jansen. Payment or honoraria for lectures, presentations or speakers bureaus from Novartis, Astra Zeneca Boehringer-Ingelheim, Bristol-Myers Squibb, Roche, Lilly, MSD, Takeda, Kyowa, Pierre-Fabre, Novocure, Sanofi, and Jansen. I. Barneto declares Payment or honoraria for lectures, presentations or speakers bureaus from Bristol-Myers Squibb, Astra Zeneca, MSD, Takeda, AMGEN, and Novartis; Support for attending meetings and/or travel from MSD and Astra Zeneca; Participation on a Data Safety Monitoring Board or Advisory Board from Sanofi. V. Calvo declares consulting fees from Roche, Astra Zeneca, MSD, Bristol-Myers Squibb, Takeda, Sanofi, and AMGEN; Payment or honoraria for lectures, presentations or speakers bureaus from Roche, Astra Zeneca, MSD, Bristol-Myers Squibb, Takeda, Pfizer, and Janssen; Support for attending meetings and/or travel from Astra Zeneca, Roche, and Takeda. A. Collazo declares Payment or honoraria for lectures, presentations or speakers bureaus from Astra Zeneca and Janssen; Support for attending meetings and/or travel from MSD and Takeda. A. Romero declares consulting fees from Takeda; Payment or honoraria for lectures, presentations or speakers bureaus from Illumina, Health in code, and Thermofisher. Support for attending meetings and/or travel from Thermofisher Scientific. Bristol Myers Squibb Foundation, and Takeda; the author also declares a pending patent (n° EP 22 382 701.5). The rest of the authors declare no potential conflicts of interest., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Occupation is an important risk factor for lung cancer. This knowledge is mainly based on studies conducted on men, with the results being generalized to women., Aims: We aimed to identify the relationship between different occupations and lung cancer in women., Methods: Pooling study in which data were pooled from six case-control studies conducted at 13 Spanish hospitals and 1 hospital in Portugal. Each woman's longest held job was coded as per the ISCO-08. Results were adjusted for age, smoking, and exposure to residential radon., Results: The study population comprised 1262 women: 618 cases and 644 controls. The reference group were white-collar workers. The adjusted multivariate analysis showed a higher risk of developing lung cancer among teaching professionals (odds ratio [OR]: 4.36; 95% confidence interval [CI] 1.73-11.02), cooks (OR: 3.59; 95% CI 1.52-8.48), domestic cleaners and helpers (OR: 2.98; 95% CI 1.54-5.78), homemakers (OR: 2.30; 95% CI 1.26-4.21) and crop farmers, livestock farmers and gardeners (OR: 2.06, 95% CI: 1.11-3.81). For adenocarcinoma, the highest risk was observed in teaching professionals, and for small-cell carcinoma, the highest risk was observed in cooks. Higher risks were observed for small-cell carcinoma compared to other histological types., Conclusions: Some occupations may be associated with an increased risk of lung cancer in women and this risk could vary by histologic subtype; however, further research is needed to confirm these associations. In any case, protection measures must be implemented in the workplace aimed at reducing the risk of lung cancer among women workers, and more studies exclusively focused on women are warranted., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Purpose: Transcriptomic subtyping holds promise for personalized therapy in extensive-stage small cell lung cancer (ES-SCLC). In this study, we aimed to assess intratumoral transcriptomic subtype diversity and to identify biomarkers of long-term chemoimmunotherapy benefit in human ES-SCLC., Experimental Design: We analyzed tumor samples from 58 patients with ES-SCLC enrolled in two multicenter single-arm phase IIIb studies evaluating frontline chemoimmunotherapy in Spain: n = 32 from the IMfirst trial and n = 26 from the CANTABRICO trial. We used the GeoMx Digital Spatial Profiler system to perform multi-region transcriptomic analysis. For subtype classification, we performed hierarchical clustering using the relative expression of ASCL1 (SCLC-A), NEUROD1 (SCLC-N), POU2F3 (SCLC-P), and YAP1 (SCLC-Y)., Results: Subtype distribution was found to be similar between bothcohorts, except for SCLC-P, which was not identified in the CANTABRICO&#95;DSP cohort. A total of 44% of the patients in both cohorts had tumors with multiple coexisting transcriptional subtypes. Transcriptional subtypes or subtype heterogeneity was not associated with outcomes. Most potential targets did not show subtype-specific expression. Consistently in both cohorts, tumors from patients with long-term benefit (time to progression ≥12 months) contained an IFNγ-dominated mRNA profile, including enhanced capacity for antigen presentation. Hypoxia and glycolytic pathways were associated with resistance to chemoimmunotherapy., Conclusions: This work suggests that intratumoral heterogeneity, inconsistent association with outcome, and unclear subtype-specific target expression might be significant challenges for subtype-based precision oncology in SCLC. Preexisting IFNγ-driven immunity and mitochondrial metabolism seem to be correlates of long-term efficacy in this study, although the absence of a chemotherapy control arm precludes concluding that these are predictive features specific for immunotherapy., (©2024 American Association for Cancer Research.)

Introduction: Recent advances in the treatment of locally advanced NSCLC have led to changes in the standard of care for this disease. For the selection of the best approach strategy for each patient, it is necessary the homogenization of diagnostic and therapeutic interventions, as well as the promotion of the evaluation of patients by a multidisciplinary oncology team., Objective: Development of an expert consensus document with suggestions for the approach and treatment of locally advanced NSCLC leaded by Spanish Lung Cancer Group GECP., Methods: Between March and July 2023, a panel of 28 experts was formed. Using a mixed technique (Delphi/nominal group) under the guidance of a coordinating group, consensus was reached in 4 phases: 1. Literature review and definition of discussion topics 2. First round of voting 3. Communicating the results and second round of voting 4. Definition of conclusions in nominal group meeting. Responses were consolidated using medians and interquartile ranges. The threshold for agreement was defined as 85% of the votes., Results: New and controversial situations regarding the diagnosis and management of locally advanced NSCLC were analyzed and reconciled based on evidence and clinical experience. Discussion issues included: molecular diagnosis and biomarkers, radiologic and surgical diagnosis, mediastinal staging, role of the multidisciplinary thoracic committee, neoadjuvant treatment indications, evaluation of response to neoadjuvant treatment, postoperative evaluation, and follow-up., Conclusions: Consensus clinical suggestions were generated on the most relevant scenarios such as diagnosis, staging and treatment of locally advanced lung cancer, which will serve to support decision-making in daily practice., (© 2024. The Author(s).)

Purpose of Review: Early-stage nonsmall cell lung cancer (NSCLC) accounts for 30% of the total NSCLC, being the stage III a heterogeneous disease that represents a challenge in the management of these patients. Multidisciplinary approach is essential for an adequate treatment strategy, with surgery being the only curative treatment. Neoadjuvant or adjuvant chemotherapy has been the standard of care for a long period, with modest results., Recent Findings: Combination of chemotherapy and immunotherapy has revolutionized the neoadjuvant setting of resectable NSCLC, improving pathologic complete responses and survival outcomes in this scenario. Furthermore, perioperative treatment with immunotherapy has also recently shown promising results in several phase III trials., Summary: The landscape of early-stage resectable NSCLC has evolved in recent years, with an improvement in the survival of these patients since the incorporation of immunotherapy in this scenario., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Introduction: Lung cancer is one of the most prevalent cancers and the leading cause of cancer death. Advanced non-small cell lung cancer (aNSCLC) patients frequently harbor mutations that impact their survival outcomes. There are limited data regarding the prognostic and predictive significance of these mutations on survival outcomes in the real-world setting., Methods: This observational retrospective study analyzed de-identified electronic medical records from the Flatiron Health Clinico-Genomic and FoundationCore® databases to identify patients with aNSCLC who initiated first-line immune checkpoint inhibitors (ICI; alone or in combination) or chemotherapy under routine care between 2016 and 2021. The primary objectives were to assess the prevalence of non-actionable mutations and to determine their association with overall survival (OS). Real-world progression-free survival (rwPFS) and real-world response (rwR) were investigated as secondary exploratory outcomes., Results: Based on an assessment of 185 non-actionable mutations in 2999 patients, the most prevalent mutations were TP53 (70%), KRAS (42%), CDKN2A/B (31%), and STK11 (21%). STK11, KEAP1, and CDKN2A/B mutations were significantly associated with lower rwR, shorter rwPFS and OS. KRAS mutations were clinically associated with shorter rwPFS in CIT-treated patients. Subgroup analysis revealed that fast progressors were significantly more likely to harbor STK11, KEAP1, and CDKN2A/B mutations. Accordingly, long-term survivors (LTS) showed a significantly lower prevalence of these mutations., Conclusion: Our results provide evidence on the prognostic value of STK11, KEAP1, and CDKN2A/B mutations in patients with aNSCLC. Further research is required to better understand the implications of these findings on patient management and future trial design and treatment selection., (© 2023. The Author(s).)

The recurrence of low-stage lung cancer poses a challenge due to its unpredictable nature and diverse patient responses to treatments. Personalized care and patient outcomes heavily rely on early relapse identification, yet current predictive models, despite their potential, lack comprehensive genetic data. This inadequacy fuels our research focus-integrating specific genetic information, such as pathway scores, into clinical data. Our aim is to refine machine learning models for more precise relapse prediction in early-stage non-small cell lung cancer. To address the scarcity of genetic data, we employ imputation techniques, leveraging publicly available datasets such as The Cancer Genome Atlas (TCGA), integrating pathway scores into our patient cohort from the Cancer Long Survivor Artificial Intelligence Follow-up (CLARIFY) project. Through the integration of imputed pathway scores from the TCGA dataset with clinical data, our approach achieves notable strides in predicting relapse among a held-out test set of 200 patients. By training machine learning models on enriched knowledge graph data, inclusive of triples derived from pathway score imputation, we achieve a promising precision of 82% and specificity of 91%. These outcomes highlight the potential of our models as supplementary tools within tumour, node, and metastasis (TNM) classification systems, offering improved prognostic capabilities for lung cancer patients. In summary, our research underscores the significance of refining machine learning models for relapse prediction in early-stage non-small cell lung cancer. Our approach, centered on imputing pathway scores and integrating them with clinical data, not only enhances predictive performance but also demonstrates the promising role of machine learning in anticipating relapse and ultimately elevating patient outcomes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Sexual dysfunction (SD) associated with oncological treatment is a common and understudied disorder. Our aim was to characterize SD in a cohort of Spanish patients., Methods: Analytic observational study in patients included in the CLARIFY H2020 project at the Hospital Universitario Puerta de Hierro. Clinical variables and validated measures of sexual function were collected from October 2020 to May 2022. Frequency and quality of sexual activity were assessed. Descriptive, trend associations, and logistic regression analyses were performed., Results: A total of 383 patients were included: breast cancer 68.14% (261), lung cancer 26.37% (101), and lymphoma 5.50% (21). Mean age was 56.5 years (range 33-88). 19.58% (75) were men and 80.42% (308) were women. 69% and 31% of men and women, respectively, reported being sexually active. The absolute frequency of overall sexual dissatisfaction was 76% in women and 24% in men. Women with breast cancer were most likely to have severe sexual dysfunction. Those with early disease had resolved complaints after 5 years. In multinomial logistic regression, significant associations were found in women with metastatic breast cancer and severe disorders of arousal (p 0.000), lubrication (p 0.002), orgasm (p 0.000), as well as dissatisfaction with sexual performance (p 0.000) and global sexual dissatisfaction (p 0.000). Women with lung cancer have severe arousal dysfunction (p 0.016) and global sexual dissatisfaction (p 0.044)., Conclusions: Our population has a high prevalence of SD, which supports the need to increase awareness of this disorder among the medical oncology team and the importance of including sexual health assessment in oncological patient follow-up., (© 2023. The Author(s), under exclusive licence to Federación de Sociedades Españolas de Oncología (FESEO).)

Importance: To date, no meta-analyses have comprehensively assessed the association of neoadjuvant chemoimmunotherapy with clinical outcomes in non-small cell lung cancer (NSCLC) in randomized and nonrandomized settings. In addition, there exists controversy concerning the efficacy of neoadjuvant chemoimmunotherapy for patients with NSCLC with programmed cell death 1 ligand 1 (PD-L1) levels less than 1%., Objective: To compare neoadjuvant chemoimmunotherapy with chemotherapy by adverse events and surgical, pathological, and efficacy outcomes using recently published randomized clinical trials and nonrandomized trials., Data Sources: MEDLINE and Embase were systematically searched from January 1, 2013, to October 25, 2023, for all clinical trials of neoadjuvant chemoimmunotherapy and chemotherapy that included at least 10 patients., Study Selection: Observational studies and trials reporting the use of neoadjuvant radiotherapy, including chemoradiotherapy, molecular targeted therapy, or immunotherapy monotherapy, were excluded., Main Outcomes and Measures: Surgical, pathological, and efficacy end points and adverse events were pooled using a random-effects meta-analysis., Results: Among 43 eligible trials comprising 5431 patients (4020 males [74.0%]; median age range, 55-70 years), there were 8 randomized clinical trials with 3387 patients. For randomized clinical trials, pooled overall survival (hazard ratio, 0.65; 95% CI, 0.54-0.79; I2 = 0%), event-free survival (hazard ratio, 0.59; 95% CI, 0.52-0.67; I2 = 14.9%), major pathological response (risk ratio, 3.42; 95% CI, 2.83-4.15; I2 = 31.2%), and complete pathological response (risk ratio, 5.52; 95% CI, 4.25-7.15; I2 = 27.4%) favored neoadjuvant chemoimmunotherapy over neoadjuvant chemotherapy. For patients with baseline tumor PD-L1 levels less than 1%, there was a significant benefit in event-free survival for neoadjuvant chemoimmunotherapy compared with chemotherapy (hazard ratio, 0.74; 95% CI, 0.62-0.89; I2 = 0%)., Conclusion and Relevance: This study found that neoadjuvant chemoimmunotherapy was superior to neoadjuvant chemotherapy across surgical, pathological, and efficacy outcomes. These findings suggest that patients with resectable NSCLC with tumor PD-L1 levels less than 1% may have an event-free survival benefit with neoadjuvant chemoimmunotherapy.

Background: First-line pembrolizumab plus chemotherapy has shown clinical benefit in patients with metastatic non-small cell lung cancer (NSCLC) regardless of tissue tumor mutational burden (tTMB) status. Blood tumor mutational burden (bTMB), assessed using plasma-derived circulating tumor DNA (ctDNA), may be a surrogate for tTMB. The KEYNOTE-782 study evaluated the correlation of bTMB with the efficacy of first-line pembrolizumab plus chemotherapy in NSCLC., Methods: Previously untreated patients with stage IV nonsquamous NSCLC received pembrolizumab 200 mg plus pemetrexed 500 mg/m 2 and investigator's choice of carboplatin area under the curve 5 mg/mL/min or cisplatin 75 mg/m 2 for 4 cycles, then pembrolizumab plus pemetrexed for ≤31 additional cycles every 3 weeks. Study objectives were to evaluate the association of baseline bTMB with objective response rate (ORR) (RECIST v1.1 by investigator assessment; primary), progression-free survival (PFS; RECIST v1.1 by investigator assessment), overall survival (OS), and adverse events (AEs; all secondary). A next-generation sequencing assay (GRAIL LLC) with a ctDNA panel that included lung cancer-associated and immune gene targets was used to measure bTMB., Results: 117 patients were enrolled; median time from first dose to data cutoff was 19.3 months (range, 1.0-35.5). ORR was 40.2 % (95 % CI 31.2-49.6 %), median PFS was 7.2 months (95 % CI 5.6-9.8) and median OS was 18.1 months (95 % CI 13.5-25.6). Treatment-related AEs occurred in 113 patients (96.6 %; grade 3-5, n = 56 [47.9 %]). Of patients with evaluable bTMB (n = 101), the area under the receiver operating characteristics curve for continuous bTMB to discriminate response was 0.47 (95 % CI 0.36-0.59). Baseline bTMB was not associated with PFS or OS (posterior probabilities of positive association: 16.8 % and 7.8 %, respectively)., Conclusions: AEs were consistent with the established safety profile of first-line pembrolizumab plus chemotherapy in NSCLC. Baseline bTMB did not show evidence of an association with efficacy., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: J.B. reports advisory roles with AbbVie, AstraZeneca, Bayer, BMS, Causalis, Merck Serono, MSD, Novartis, Roche, and Takeda and receiving research funding from Immunai, OncoHost, MSD, and AstraZeneca. D.R.A. reports personal fees/honoraria for consultancy or advisory roles and lectures from Roche, Genentech, AstraZeneca, Bristol Myers Squibb, Boehringer Ingleheim, MSD, Merck Serono, Eli Lilly, Gilead, Sanofi, Regeneron, Incyte, Pfizer, Takeda, and Novartis; and travel expenses from Roche, Bristol Myers Squibb, MSD, Sanofi, Regeneron, and Novartis. E.F. reports personal fees or honoraria for advisory roles from Abbvie, Amgen, AstraZeneca, Bayer, Bergen Bio, Bristol-Myers Squibb, Daiichi Sankyo, Eli Lilly, F. Hoffman-La Roche, GSK, Janssen, Merck Serono, MSD, Novartis, Peptomyc, Pfizer, Regeneron, Sanofi, Takeda, and Turning Point; speaker’s bureau fees from Amgen, AstraZeneca, Bristol Myers Squibb, Eli Lilly and Company, F. Hoffman-La Roche, Janssen, Medical Trends, Medscape, Merck Serono, MSD, Peervoice, Pfizer, Sanofi, Takeda, and Touch Oncology; and independent board membership with Grifols. M.P. reports lecture fees, honoraria, or other fees from Bristol Myers Squibb, Roche, MSD, AstraZeneca, Takeda, Eli Lilly and Company, F. Hoffman-La Roche, Janssen, and Pfizer; and research funds from MSD, AstraZeneca, Roche, Boehringer Ingleheim, and Bristol Myers Squibb. D.R.C. reports lecture fees, honoraria or other fees from Roche and AstraZeneca. S.M.T, J.K., and E.J.D. report employment with MSD. M.A. reports employment and stock ownership with MSD. N.H. reports advisory or consultancy roles and stock ownership with Curve Biosciences. R.Mc. and B.J. report employment with Grail LLC. R.Ma reports employment with Grail LLC and stock ownership with Illumina. D.B. reports employment with GRAIL LLC and stock ownership with Illumina. E.E., S.P.A., M.G., A.R., A.F., S.B.R., G.S., T.C. have no conflicts of interest to disclose., (Copyright © 2024 Merck Sharp & Dohme LLC., a subsidiary of Merck & Co., Inc., Rahway, NJ, USA, The Author(s). Published by Elsevier B.V. All rights reserved.)

Objectives: Cancer is a disease of old age; however, most studies usually included minority of patients fit elderly. The purpose is to investigate the clinical characteristics and genetic information of patients with thoracic tumors who are 80 years old or older compared to those under 80 years old., Study Design and Methods: The Thoracic Tumor Registry (TTR) is a Spanish observational, prospective cohort study that included patients diagnosed with thoracic tumors. Data were collected from medical records related to sociodemographic, epidemiological, clinical, molecular/genetic, and treatment outcome variables., Results: The total number of patients, recruited from August 2016 to April 2023, was 26.193 (93,1 % were younger than 80 years and 6,9 % were 80 years or older). In the group of older patients: the male ratio increased (72,9 % vs. 80 %); the number of elderly people who had never smoked or were ex-smokers increased (9,9 % vs. 21,1 % and 44,8 % vs. 61,3 %, respectively) and the number of current smokers decreased (43,3 % vs. 17,5 %); had higher ECOG performance status at diagnosis (for ECOG ≥ 2, 15 % vs. 32,9 %), and there were more patients with previous cancer (17,3 % vs. 28 %). The proportion of men is higher than that of women (73 % vs. 27 % in <80 years and 80 % vs. 20 % in ≥80 years). For all biomarkers, the proportion of patients who had a molecular determination was lower in older patients. There were no differences in terms of alterations in the biomarkers tested; except for EGFR, for which the positivity rate was higher in patients aged 80 years and older (25 % vs. 15,3 %)., Conclusion: The proportion of older patients with targeted mutations is higher. So, at least at diagnosis, it should be proceeded in a standard way. Then, when it comes to treatment, comorbidities and patient's baseline situation should be considered., Clinical Trial Registration: NCT02941458., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: Spanish Lung Cancer Group (SLCG) conducted a review to analyze the barriers to access to innovative targeted therapies for non-small cell lung cancer (NSCLC) in clinical practice in Spain., Methods: Review all relevant content published on websites of European Commission, European Medicines Agency, and Spanish Agency of Medicines and Medical Products regarding the authorization and access to oncology treatments., Results: More than 20 targeted therapies are available to treat different molecular alterations in patients with NSCLC. European Commission has approved treatments for genomic alterations involving the following genes: ALK, RET, ROS1, EGFR, BRAF, NTRK, KRAS, MET. However, the availability of these therapies in Spain is not complete, as innovative treatments are not reimbursed or funded late, with only five of these alterations currently covered by National Health System., Conclusion: SLCG considers imperative to improve the access in Spain to innovative treatments for NSCLC to reduce inequity across European countries., (© 2023. The Author(s).)

Introduction: The aim of this study was to analyze the clinical and genetic characteristics of young lung cancer cases, and to compare them with those of older cases., Methods: We used the Thoracic Tumors Registry (TTR) as a data source representative of lung cancer cases diagnosed in Spain, and included all cases registered until 9/01/2023 which had information on age at diagnosis or the data needed to calculate it. We performed a descriptive statistical analysis and fitted logistic regressions to analyze how different characteristics influenced being a younger lung cancer patient., Results: A total of 26,336 subjects were included. Lung cancer cases <50 years old had a higher probability of being women (OR: 1.38; 95% CI: 1.21-1.57), being in stage III or IV (OR: 1.32; 95% CI: 1.08-1.62), not having comorbidities (OR: 5.21; 95% CI: 4.59-5.91), presenting with symptoms at diagnosis (OR: 1.53; 95% CI: 1.29-1.81), and having ALK translocation (OR: 7.61; 95% CI: 1.25-46.32) and HER2 mutation (OR: 5.71; 95% CI: 1.34-24.33), compared with subjects ≥50 years. Among subjects <35 years old (n=61), our study observed a higher proportion of women (59.0% vs. 26.6%; p<0.001), never smokers (45.8% vs. 10.3%; p<0.001), no comorbidities (21.3% vs. 74.0%; p<0.001); ALK translocation (33.3% vs. 4.4%; p<0.001) and ROS1 mutation (14.3% vs. 2.3%; p=0.01), compared with subjects ≥35 years., Conclusions: Lung cancer displays differences by age at diagnosis which may have important implications for its clinical management., (Copyright © 2023 The Author(s). Published by Elsevier España, S.L.U. All rights reserved.)

Background: Platinum-sensitivity is a phenotypic biomarker of Poly (ADP-ribose) polymerase inhibitors (PARPi) sensitivity in histotypes where PARPi are approved. Approximately one-third of non-small cell lung cancers (NSCLC) are platinum-sensitive. The double-blind, randomized phase II PIPSeN (NCT02679963) study evaluated olaparib, a PARPi, as maintenance therapy for patients with platinum-sensitive advanced NSCLC., Methods: Chemonaïve patients with ECOG performance status of 0-1, platinum-sensitive, EGFR- and ALK-wild-type, stage IIIB-IV NSCLC were randomized (R) to receive either olaparib (O) maintenance or a placebo (P). The primary objective was progression-free survival (PFS) from R. Secondary objectives included overall survival (OS) and safety. With an anticipated hazard ratio of 0.65, 144 patients were required to be randomized, and approximately 500 patients enrolled., Results: The trial was prematurely terminated because anti-PD(L)1 therapy was approved during the trial recruitment. A total of 182 patients were enrolled, with 60 patients randomized: 33 and 27 in the O and P arms, respectively. Patient and tumor characteristics were well-balanced between arms, except for alcohol intake (33% vs 11% in the O and P arms, respectively, p = 0.043). The median PFS was 2.9 and 2.0 months in the O and P arms, respectively (logrank p = 0.99). The median OS was 9.4 and 9.5 months in the O and P arms, respectively (p = 0.28). Grade ≥3 toxicities occurred in 15 and 8 patients in O and P arms, with no new safety concerns., Conclusion: PIPSeN was terminated early after enrollment of only 50% of the pre-planned population, thus being statistically underpowered. Olaparib maintenance did neither improve median PFS nor OS in this patient population., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Background: In 2019, we reported the first efficacy and safety analysis of EUCROSS, a phase II trial investigating crizotinib in ROS1 fusion-positive lung cancer. At that time, overall survival (OS) was immature and the effect of crizotinib on intracranial disease control remained unclear. Here, we present the final analysis of OS, systemic and intracranial activity, and the impact of co-occurring aberrations., Materials and Methods: EUCROSS was a prospective, single-arm, phase II trial. The primary endpoint was best overall response rate (ORR) using RECIST 1.1. Secondary and exploratory endpoints were progression-free survival (PFS), OS, and efficacy in pre-defined subgroups., Results: Median OS of the intention-to-treat population (N = 34) was 54.8 months [95% confidence interval (CI) 20.3 months-not reached (NR); median follow-up 81.4 months] and median all-cause PFS of the response-evaluable population (N = 30) was 19.4 months (95% CI 10.1-32.2 months). Time on treatment was significantly correlated with OS (R = 0.82; P < 0.0001). Patients with co-occurring TP53 aberrations (28%) had a significantly shorter OS [hazard ratio (HR) 11; 95% CI 2.0-56.0; P = 0.006] and all-cause PFS (HR 4.2; 95% CI 1.2-15; P = 0.025). Patients with central nervous system (CNS) involvement at baseline (N = 6; 20%) had a numerically shorter median OS and all-cause PFS. Median intracranial PFS was 32.2 months (95% CI 23.7 months-NR) and the rate of isolated CNS progression was 24%., Conclusions: Our final analysis proves the efficacy of crizotinib in ROS1-positive lung cancer, but also highlights the devastating impact of TP53 mutations on survival and treatment efficacy. Additionally, our data show that CNS disease control is durable and the risk of CNS progression while on crizotinib treatment is low., Competing Interests: Disclosures SM reports research grants from Novartis and Pfizer, personal fees from Eli Lilly, Janssen, and AstraZeneca as well as support for attending meetings and/or travel from Eli Lilly and Janssen. JS reports personal fees from Pfizer, Janssen, Merck Sharp Dohme, Lilly, Boehringer-Ingelheim, AstraZeneca, Roche, Bristol-Myers Squibb, Amgen, LEO Pharma, Novartis, Takeda, and Sanofi as well as support for meetings and/or travels from AstraZeneca, Janssen, and Lilly. EF reports personal fees from AbbVie, Amgen, AstraZeneca, Bayer, Beigene, Bristol-Myers Squibb, Daichi Sankyo, Eli Lilly, F. Hoffmann-La Roche, Gilead, GlaxoSmithKline, Janssen, Medical Trends, Medscape, Merck-Serono, Merck Sharp & Dohme, Novartis, Peervoice, Peptomyc, Pfizer, Regeneron, Sanofi, Takeda, Turning Point Pharmaceuticals, and Touch Oncology as well as support for attending meetings and/or travel from AstraZeneca, Janssen, and Roche. CG reports personal fees from Roche, Sanofi, Boehringer-Ingelheim, Merck Sharp & Dohme, Bristol-Myers Squibb, Celgene, Lilly, Takeda, Novartis, AstraZeneca, and Pfizer. JC reports grants from Pfizer, Roche, and Bristol-Myers Squibb, personal fees from Amgen, AstraZeneca, Roche, Eli Lilly, Merck, Merck Sharp & Dohme, Takeda, Janssen, Sanofi, and Pfizer, as well as support for attending meetings and/or travel from Merck Sharp Dohme. JF reports personal fees from AstraZeneca. EC i C reports personal fees from Pfizer. RNF reports a research grant from Bristol-Myers Squibb and personal fees from Janssen. AI reports personal fees from Amgen, AstraZeneca, Bristol-Myers Squibb, Boehringer-Ingelheim, Merck Sharp & Dohme, Sanofi, Pfizer, Roche, and Takeda as well as support for attending meetings and/or travel from Roche and Pfizer. LN reports research grants from Novartis, Pfizer, Janssen, Bristol-Myers Squibb, Amgen, Siemens, and Dracen as well as personal fees from Pfizer, Janssen, AstraZeneca, and Roche. MR reports personal fees as well as support for attending meetings and/or travel from AstraZeneca, Amgen, Beigene, Bristol-Myers Squibb, Boehringer-Ingelheim, Daiichi Sankyo, Merck, Merck Sharp & Dohme, Mirati, Biontech, Novartis, GlaxoSmithKline, Pfizer, Roche, and Samsung Biopis. RR reports personal fees from Novartis and Janssen. DS reports personal fees from Bristol-Myers Squibb, Boehringer-Ingelheim, Merck Sharp & Dohme, Novartis, Roche, Healthcare Consulting Cologne, and AbbVie as well as support for attending meetings and/or travel from AstraZeneca, Bristol-Myers Squibb, Boehringer-Ingelheim, Merck Sharp & Dohme, Novartis, Roche, and AbbVie. MS reports research grants from Amgen, Dracen Pharmaceuticals, Novartis, Siemens Healthineers, and Takeda, personal fees from Amgen, AstraZeneca, Boehringer-Ingelheim, Bristol-Myers Squibb, Janssen, Novartis, Roche, Sanofi-Aventis, Siemens Healthineers, and Takeda as well as support for attending meetings and/or travel from Janssen and Pfizer. MP reports research grants from Pfizer, Roche, and Bristol-Myers Squibb, personal fees from Bristol-Myers Squibb, Amgen, AstraZeneca, Takeda, Pfizer, Merck, Merck Sharp & Dohme, Roche, and Sanofi as well as support for attending meetings and/or travel from Merck Sharp & Dohme. SM-B reports personal fees from Amgen, AstraZeneca, Bayer, Bristol-Myers Squibb, GlaxoSmithKline, Janssen, Merck, Merck Sharp & Dohme, Molecular Health, Novartis, Pfizer, Qiagen, QuIP, and DLS. MS reports a research grant from AstraZeneca, personal fees from Roche, Astra Zeneca, Pfizer, BioNTech, Boehringer-Ingelheim, Lilly, Bristol-Myers Squibb, CureVac, Daiichi Sankyo, GlaxoSmithKline, Merck, Merck Sharp & Dohme, Novartis, Takeda, Janssen, and Amgen as well as support for attending meetings and/or travel from Pfizer and Bristol-Myers Squibb. RB reports personal fees from AbbVie, Amgen, AstraZeneca, Bayer, BMS, Boehringer-Ingelheim, Illumina, Janssen, Lilly, Merck-Serono, Merck Sharp & Dohme, Novartis, Qiagen, Pfizer, Roche, Sanofi, and Targos MP Inc. RB is a co-owner and shareholder of Gnothis Inc. (Stockholm) and TimerTherapeutix (Germany). JW reports research grants from Bristol-Myers Squibb, Janssen, Novartis, and Pfizer, personal fees and support for attending meetings and/or travel from Amgen, AstraZeneca, Bayer, Blueprint, Bristol-Myers Squibb, Boehringer-Ingelheim, Chugai, Daichi Sankyo, Janssen, Lilly, Loxo, Merck, Merck Sharp & Dohme, Novartis, Nuvalent, Pfizer, Roche, Seattle Genetics, Takeda, and Turning Point Pharmaceuticals. All other authors have declared no conflicts of interest., (Copyright © 2024. Published by Elsevier Ltd.)

Neoadjuvant immunotherapy plus chemotherapy improves event-free survival (EFS) and pathologic complete response (0% residual viable tumor (RVT) in primary tumor (PT) and lymph nodes (LNs)), and is approved for treatment of resectable lung cancer. Pathologic response assessment after neoadjuvant therapy is the potential analog to radiographic response for advanced disease. However, %RVT thresholds beyond pathologic complete response and major pathologic response (≤10% RVT) have not been explored. Pathologic response was prospectively assessed in the randomized, phase 3 CheckMate 816 trial (NCT02998528), which evaluated neoadjuvant nivolumab (anti-programmed death protein 1) plus chemotherapy in patients with resectable lung cancer. RVT, regression and necrosis were quantified (0-100%) in PT and LNs using a pan-tumor scoring system and tested for association with EFS in a prespecified exploratory analysis. Regardless of LN involvement, EFS improved with 0% versus >0% RVT-PT (hazard ratio = 0.18). RVT-PT predicted EFS for nivolumab plus chemotherapy (area under the curve = 0.74); 2-year EFS rates were 90%, 60%, 57% and 39% for patients with 0-5%, >5-30%, >30-80% and >80% RVT, respectively. Each 1% RVT associated with a 0.017 hazard ratio increase for EFS. Combining pathologic response from PT and LNs helped differentiate outcomes. When compared with radiographic response and circulating tumor DNA clearance, %RVT best approximated EFS. These findings support pathologic response as an emerging survival surrogate. Further assessment of the full spectrum of %RVT in lung cancer and other tumor types is warranted. ClinicalTrials.gov registration: NCT02998528 ., (© 2023. The Author(s).)

What Is This Summary About?: This is a summary of the results of a study called PHAROS. This study looked at combination treatment with encorafenib (BRAFTOVI ® ) and binimetinib (MEKTOVI ® ). This combination of medicines was studied in people with metastatic non-small-cell lung cancer (NSCLC). NSCLC is the most common type of lung cancer. Metastatic means that the cancer has spread to other parts of the body. All people in this study had a type of NSCLC that has a change in a gene called BRAF termed a BRAF V600E mutation. A gene is a part of the DNA that has instructions for making things that your body needs to work, and the BRAF V600E mutation contributes to the growth of the lung cancer., What Were the Results?: In this study, 98 people with BRAF V600E-mutant metastatic NSCLC were treated with the combination of encorafenib and binimetinib (called encorafenib plus binimetinib in this summary). Before starting the study, 59 people had not received any treatment for their metastatic NSCLC, and 39 people had received previous anticancer treatment. At the time of this analysis, 44 (75%) out of 59 people who did not receive any treatment before taking encorafenib plus binimetinib had their tumors shrink or disappear. Eighteen (46%) out of 39 people who had received treatment before starting encorafenib plus binimetinib also had their tumors shrink or disappear. The most common side effects of encorafenib plus binimetinib were nausea, diarrhea, fatigue, and vomiting., What Do the Results Mean?: These results support the use of encorafenib plus binimetinib combination treatment as a new treatment option in people with BRAF V600E-mutant metastatic NSCLC. The side effects of encorafenib plus binimetinib in this study were similar to the side effects seen with encorafenib plus binimetinib in people with a type of skin cancer called metastatic melanoma.

Introduction: Small cell lung cancer (SCLC) comprises 10-15% of all lung cancer cases and is the most aggressive histological type. Survival is poor and the molecular landscape of this disease is extraordinarily complex. The objective of this paper was to perform a Genome-Wide Association Study (GWAS) of this disease using a case-control study specifically designed for small cell lung cancer (SCLC)., Methods: Incident cases were consecutively recruited from 8 hospitals from different regions of Spain. Controls were recruited from the same hospitals using a frequency sampling based on age and sex distribution of cases. Biological samples were obtained along with detailed information on cases and controls lifestyle, including tobacco and radon exposure., Results: We included 271 SCLC cases and 557 controls. We found evidence (p-values<10 -5 ) of an association in the complete dataset for several loci, while MAP4 showed a significant association in the gene-based analysis. Pathway analysis suggested that ATR, ATRIP, MCM4, MCM5, ORC4, RPA3 and CDC25A genes have a role on the onset of SCLC., Conclusion: This study provides biological evidence for pathways related to SCLC, offering novel loci for further research., (Copyright © 2023 The Author(s). Published by Elsevier España, S.L.U. All rights reserved.)

Objective: Patients with lung cancer are at increased risk of SARS-CoV-2 infection and severe complications from COVID-19, but information on the efficacy of anti-SARS-CoV-2 vaccine in these patients is scarce. We aimed at evaluating the safety and immunogenicity of COVID-19 vaccines in this population., Patients and Methods: The prospective, nationwide SOLID substudy, enrolled adults with lung cancer who were fully vaccinated against COVID-19. Serum anti-SARS-CoV-2 IgG antibody levels were quantitatively assessed two weeks and six months after receipt of the last dose using a chemiluminescent microparticle immunoassay. Multivariate odds ratios for the association between demographic and clinical factors and seronegativity after vaccination were estimated., Results: 1973 lung cancer patients were enrolled. Most patients had stage IV disease (66%) and were receiving active cancer treatment (82.7%). No significant differences were found in the probability of being seronegative for anti-SARS-CoV-2 IgG antibodies after full vaccination between patients who were receiving active cancer treatment and those who were not (p = 0.396). The administration of immunotherapy or oral targeted therapy and immunization with mRNA-1273 COVID-19 vaccine were factors independently associated with increased odds of being seropositive after vaccination. From all patients, 1405 received the second dose of vaccine and high levels of antibody titers were observed in 93.6% of patients two weeks after second dose. At six months, multivariate logistic regression analysis showed that performance status ≥ 2 was independently associated with a higher probability of being seronegative after full vaccination with an OR 4.15. On the other hand, received chemotherapy or oral target therapy and vaccination with mRNA-1273 were a factor independently associated with lower odds of being seronegative after full vaccination with an OR 0.52, 0.37 and 0.34, respectively., Conclusions: Lung cancer patients can safely achieve a strong immune response against SARS-CoV-2 after full vaccination, regardless of the cancer treatment received., Trial Registration: NCT04407143., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Introduction: Pathologic response has been proposed as an early clinical trial end point of survival after neoadjuvant treatment in clinical trials of NSCLC. The International Association for the Study of Lung Cancer (IASLC) published recommendations for pathologic evaluation of resected lung cancers after neoadjuvant therapy. The aim of this study was to assess pathologic response interobserver reproducibility using IASLC criteria., Methods: An international panel of 11 pulmonary pathologists reviewed hematoxylin and eosin-stained slides from the lung tumors of resected NSCLC from 84 patients who received neoadjuvant immune checkpoint inhibitors in six clinical trials. Pathologic response was assessed for percent viable tumor, necrosis, and stroma. For each slide, tumor bed area was measured microscopically, and pre-embedded formulas calculated unweighted and weighted major pathologic response (MPR) averages to reflect variable tumor bed proportion., Results: Unanimous agreement among pathologists for MPR was observed in 68 patients (81%), and inter-rater agreement (IRA) was 0.84 (95% confidence interval [CI]: 0.76-0.92) and 0.86 (95% CI: 0.79-0.93) for unweighted and weighted averages, respectively. Overall, unweighted and weighted methods did not reveal significant differences in the classification of MPR. The highest concordance by both methods was observed for cases with more than 95% viable tumor (IRA = 0.98, 95% CI: 0.96-1) and 0% viable tumor (IRA = 0.94, 95% CI: 0.89-0.98). The most common reasons for discrepancies included interpretations of tumor bed, presence of prominent stromal inflammation, distinction between reactive and neoplastic pneumocytes, and assessment of invasive mucinous adenocarcinoma., Conclusions: Our study revealed excellent reliability in cases with no residual viable tumor and good reliability for MPR with the IASLC recommended less than or equal to 10% cutoff for viable tumor after neoadjuvant therapy., (Copyright © 2023. Published by Elsevier Inc.)

ALK, ROS1, and RET fusions and MET∆ex14 variant associate with response to targeted therapies in non-small-cell lung cancer (NSCLC). Technologies for fusion testing in tissue must be adapted to liquid biopsies, which are often the only material available. In this study, circulating-free RNA (cfRNA) and extracellular vesicle RNA (EV-RNA) were purified from liquid biopsies. Fusion and MET∆ex14 transcripts were analyzed by nCounter (Nanostring) and digital PCR (dPCR) using the QuantStudio ® System (Applied Biosystems). We found that nCounter detected ALK, ROS1, RET, or MET∆ex14 aberrant transcripts in 28/40 cfRNA samples from positive patients and 0/16 of control individuals (70% sensitivity). Regarding dPCR, aberrant transcripts were detected in the cfRNA of 25/40 positive patients. Concordance between the two techniques was 58%. Inferior results were obtained when analyzing EV-RNA, where nCounter often failed due to a low amount of input RNA. Finally, results of dPCR testing in serial liquid biopsies of five patients correlated with response to targeted therapy. We conclude that nCounter can be used for multiplex detection of fusion and MET∆ex14 transcripts in liquid biopsies, showing a performance comparable with next-generation sequencing platforms. dPCR could be employed for disease follow-up in patients with a known alteration. cfRNA should be preferred over EV-RNA for these analyses., (© 2023 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Background: Approximately 20% of patients with non-small-cell lung cancer (NSCLC) receive a diagnosis of stage III disease. There is no current consensus regarding the most appropriate treatment for these patients., Methods: In this open-label, phase 2 trial, we randomly assigned patients with resectable stage IIIA or IIIB NSCLC to receive neoadjuvant nivolumab plus platinum-based chemotherapy (experimental group) or chemotherapy alone (control group), followed by surgery. Patients in the experimental group who had R0 resections received adjuvant treatment with nivolumab for 6 months. The primary end point was a pathological complete response (0% viable tumor in resected lung and lymph nodes). Secondary end points included progression-free survival and overall survival at 24 months and safety., Results: A total of 86 patients underwent randomization; 57 were assigned to the experimental group and 29 were assigned to the control group. A pathological complete response occurred in 37% of the patients in the experimental group and in 7% in the control group (relative risk, 5.34; 95% confidence interval [CI], 1.34 to 21.23; P = 0.02). Surgery was performed in 93% of the patients in the experimental group and in 69% in the control group (relative risk, 1.35; 95% CI, 1.05 to 1.74). Kaplan-Meier estimates of progression-free survival at 24 months were 67.2% in the experimental group and 40.9% in the control group (hazard ratio for disease progression, disease recurrence, or death, 0.47; 95% CI, 0.25 to 0.88). Kaplan-Meier estimates of overall survival at 24 months were 85.0% in the experimental group and 63.6% in the control group (hazard ratio for death, 0.43; 95% CI, 0.19 to 0.98). Grade 3 or 4 adverse events occurred in 11 patients in the experimental group (19%; some patients had events of both grades) and 3 patients in the control group (10%)., Conclusions: In patients with resectable stage IIIA or IIIB NSCLC, perioperative treatment with nivolumab plus chemotherapy resulted in a higher percentage of patients with a pathological complete response and longer survival than chemotherapy alone. (Funded by Bristol Myers Squibb and others; NADIM II ClinicalTrials.gov number, NCT03838159; EudraCT number, 2018-004515-45.)., (Copyright © 2023 Massachusetts Medical Society.)

Objective: Lung cancer exhibits unpredictable recurrence in low-stage tumors and variable responses to different therapeutic interventions. Predicting relapse in early-stage lung cancer can facilitate precision medicine and improve patient survivability. While existing machine learning models rely on clinical data, incorporating genomic information could enhance their efficiency. This study aims to impute and integrate specific types of genomic data with clinical data to improve the accuracy of machine learning models for predicting relapse in early-stage, non-small cell lung cancer patients., Methods: The study utilized a publicly available TCGA lung cancer cohort and imputed genetic pathway scores into the Spanish Lung Cancer Group (SLCG) data, specifically in 1348 early-stage patients. Initially, tumor recurrence was predicted without imputed pathway scores. Subsequently, the SLCG data were augmented with pathway scores imputed from TCGA. The integrative approach aimed to enhance relapse risk prediction performance., Results: The integrative approach achieved improved relapse risk prediction with the following evaluation metrics: an area under the precision-recall curve (PR-AUC) score of 0.75, an area under the ROC (ROC-AUC) score of 0.80, an F1 score of 0.61, and a Precision of 0.80. The prediction explanation model SHAP (SHapley Additive exPlanations) was employed to explain the machine learning model's predictions., Conclusion: We conclude that our explainable predictive model is a promising tool for oncologists that addresses an unmet clinical need of post-treatment patient stratification based on the relapse risk while also improving the predictive power by incorporating proxy genomic data not available for specific patients., Competing Interests: Declaration of Competing Interest We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Purpose: The combination of encorafenib (BRAF inhibitor) plus binimetinib (MEK inhibitor) has demonstrated clinical efficacy with an acceptable safety profile in patients with BRAF V600E/K -mutant metastatic melanoma. We evaluated the efficacy and safety of encorafenib plus binimetinib in patients with BRAF V600E -mutant metastatic non-small-cell lung cancer (NSCLC)., Methods: In this ongoing, open-label, single-arm, phase II study, patients with BRAF V600E -mutant metastatic NSCLC received oral encorafenib 450 mg once daily plus binimetinib 45 mg twice daily in 28-day cycles. The primary end point was confirmed objective response rate (ORR) by independent radiology review (IRR). Secondary end points included duration of response (DOR), disease control rate (DCR), progression-free survival (PFS), overall survival, time to response, and safety., Results: At data cutoff, 98 patients (59 treatment-naïve and 39 previously treated) with BRAF V600E -mutant metastatic NSCLC received encorafenib plus binimetinib. Median duration of treatment was 9.2 months with encorafenib and 8.4 months with binimetinib. ORR by IRR was 75% (95% CI, 62 to 85) in treatment-naïve and 46% (95% CI, 30 to 63) in previously treated patients; median DOR was not estimable (NE; 95% CI, 23.1 to NE) and 16.7 months (95% CI, 7.4 to NE), respectively. DCR after 24 weeks was 64% in treatment-naïve and 41% in previously treated patients. Median PFS was NE (95% CI, 15.7 to NE) in treatment-naïve and 9.3 months (95% CI, 6.2 to NE) in previously treated patients. The most frequent treatment-related adverse events (TRAEs) were nausea (50%), diarrhea (43%), and fatigue (32%). TRAEs led to dose reductions in 24 (24%) and permanent discontinuation of encorafenib plus binimetinib in 15 (15%) patients. One grade 5 TRAE of intracranial hemorrhage was reported. Interactive visualization of the data presented in this article is available at the PHAROS dashboard (https://clinical-trials.dimensions.ai/pharos/)., Conclusion: For patients with treatment-naïve and previously treated BRAF V600E -mutant metastatic NSCLC, encorafenib plus binimetinib showed a meaningful clinical benefit with a safety profile consistent with that observed in the approved indication in melanoma.

Purpose: Stratifying patients with cancer according to risk of relapse can personalize their care. In this work, we provide an answer to the following research question: How to use machine learning to estimate probability of relapse in patients with early-stage non-small-cell lung cancer (NSCLC)?, Materials and Methods: For predicting relapse in 1,387 patients with early-stage (I-II) NSCLC from the Spanish Lung Cancer Group data (average age 65.7 years, female 24.8%, male 75.2%), we train tabular and graph machine learning models. We generate automatic explanations for the predictions of such models. For models trained on tabular data, we adopt SHapley Additive exPlanations local explanations to gauge how each patient feature contributes to the predicted outcome. We explain graph machine learning predictions with an example-based method that highlights influential past patients., Results: Machine learning models trained on tabular data exhibit a 76% accuracy for the random forest model at predicting relapse evaluated with a 10-fold cross-validation (the model was trained 10 times with different independent sets of patients in test, train, and validation sets, and the reported metrics are averaged over these 10 test sets). Graph machine learning reaches 68% accuracy over a held-out test set of 200 patients, calibrated on a held-out set of 100 patients., Conclusion: Our results show that machine learning models trained on tabular and graph data can enable objective, personalized, and reproducible prediction of relapse and, therefore, disease outcome in patients with early-stage NSCLC. With further prospective and multisite validation, and additional radiological and molecular data, this prognostic model could potentially serve as a predictive decision support tool for deciding the use of adjuvant treatments in early-stage lung cancer.

Introduction and Objectives: Exposure to environmental tobacco smoke (ETS) is associated with increased mortality and morbidity. The objective of this study was to estimate the impact of ETS exposure in Spain on mortality in 2020 in the population aged 35 years and over., Methods: A method of estimating attributable mortality (AM) based on the prevalence of ETS exposure was applied. Prevalence data were obtained from a representative study conducted in Spain and the relative risks were derived from a meta-analysis. AM point estimates are presented along with 95% confidence intervals (95% CI), calculated using a bootstrap naive procedure. AM, both overall and by smoking habit, was estimated for each combination of sex, age group, and cause of death (lung cancer and ischemic heart disease). A sensitivity analysis was performed., Results: A total of 747 (95% CI 676-825) deaths were attributable to ETS exposure, of which 279 (95% CI 256-306) were caused by lung cancer, and 468 (95% CI 417-523) by ischemic heart disease. Three-quarters (75.1%) of AM occurred in men and 60.9% in non-smokers. When chronic obstructive pulmonary disease and cerebrovascular disease are included, the burden of AM is estimated at 2242 deaths., Conclusions: ETS exposure is associated with 1.5% of all deaths from lung cancer and ischemic heart disease in the population aged 35 and over. These data underline the need for health authorities to focus on reducing exposure to ETS in all settings and environments., (Copyright © 2023 The Author(s). Published by Elsevier España, S.L.U. All rights reserved.)

Early-stage lung cancer is crucial clinically due to its insidious nature and rapid progression. Most of the prediction models designed to predict tumour recurrence in the early stage of lung cancer rely on the clinical or medical history of the patient. However, their performance could likely be improved if the input patient data contained genomic information. Unfortunately, such data is not always collected. This is the main motivation of our work, in which we have imputed and integrated specific type of genomic data with clinical data to increase the accuracy of machine learning models for prediction of relapse in early-stage, non-small cell lung cancer patients. Using a publicly available TCGA lung adenocarcinoma cohort of 501 patients, their aneuploidy scores were imputed into similar records in the Spanish Lung Cancer Group (SLCG) data, more specifically a cohort of 1348 early-stage patients. First, the tumor recurrence in those patients was predicted without the imputed aneuploidy scores. Then, the SLCG data were enriched with the aneuploidy scores imputed from TCGA. This integrative approach improved the prediction of the relapse risk, achieving area under the precision-recall curve (PR-AUC) score of 0.74, and area under the ROC (ROC-AUC) score of 0.79. Using the prediction explanation model SHAP (SHapley Additive exPlanations), we further explained the predictions performed by the machine learning model. We conclude that our explainable predictive model is a promising tool for oncologists that addresses an unmet clinical need of post-treatment patient stratification based on the relapse risk, while also improving the predictive power by incorporating proxy genomic data not available for the actual specific patients., (©2022 AMIA - All rights reserved.)

Small cell lung cancer (SCLC) comprises approximately 10% of all lung cancer cases. Tobacco is its main risk factor; however, occupation might play a role in this specific lung cancer subtype. The effect of occupation on SCLC risk has been hardly studied and therefore we aim to assess the role of occupation on the risk of SCLC. To do this, we designed a multicentric, hospital-based, case-control study. Cases consisted exclusively in SCLC patients and controls were recruited from patients having minor surgery at the participating hospitals. Face to face interviews emphasizing occupation and tobacco consumption were held and residential radon was also measured. Logistic regression models were adjusted with odds ratios with 95%CI as estimations of the effect. 423 cases and 905 controls were included. Smoking prevalence was higher in cases compared to controls. Those who worked in known-risk occupations for lung cancer showed an OR of 2.17 (95%CI 1.33; 3.52), with a similar risk when men were analysed separately. The results were adjusted by age, sex, smoking and indoor radon exposure. Those who worked in known-risk occupations and were moderate or heavy smokers had a SCLC risk of 12.19 (95%CI 5.68-26.38) compared with never or moderate smokers who had not worked in such occupations. Occupation is a relevant risk factor of SCLC, and it seems that its effect is boosted when tobacco smoking is present., (© 2023. The Author(s).)

Importance: Antiangiogenic drug combinations with anti-programmed cell death 1 protein and anti-programmed cell death 1 ligand 1 (PD-L1) agents are a novel treatment option for lung cancer. However, survival remains limited, and the activity of these combinations for tumors with high tumor mutation burden (TMB) is unknown., Objective: To assess the clinical benefits and safety of atezolizumab plus bevacizumab for patients with high-TMB advanced nonsquamous non-small cell lung cancer (NSCLC)., Design, Setting, and Participants: This multicenter, single-arm, open-label, phase 2 nonrandomized controlled trial (Atezolizumab Plus Bevacizumab in First-Line NSCLC Patients [TELMA]) included treatment-naive patients aged 18 years or older with confirmed stage IIIB-IV nonsquamous NSCLC with TMB of 10 or more mutations/megabase and no EGFR, ALK, STK11, MDM2, or ROS1 alterations. From May 2019 through January 2021, patients were assessed at 13 sites in Spain, with follow-up until February 28, 2022., Interventions: Participants were given atezolizumab, 1200 mg, plus bevacizumab, 15 mg/kg, on day 1 of each 21-day cycle. Treatment was continued until documented disease progression, unacceptable toxic effects, patient withdrawal, investigator decision, or death., Main Outcomes and Measures: The primary end point was 12-month progression-free survival (PFS) rate (according to Response Evaluation Criteria in Solid Tumours, version 1.1 criteria); PFS was defined as the time from enrollment to disease progression or death. Adverse events were monitored according to the National Cancer Institute Common Terminology Criteria for Adverse Events, version 4.0., Results: A total of 307 patients were assessed for trial eligibility, of whom 266 were ineligible for enrollment. Of the 41 patients enrolled, 3 did not fulfill all inclusion criteria and were excluded. The remaining 38 patients (28 [73.7%] male; mean [SD] age, 63.7 [8.3] years) constituted the per-protocol population. The 12-month PFS rate was 51.3% (95% CI, 34.2%-66.0%), which met the primary end point. The 12-month overall survival (OS) rate was 72.0% (95% CI, 54.1%-83.9%). The median PFS was 13.0 months (95% CI, 7.9-18.0 months), and the median OS was not reached. Of the 38 patients, 16 (42.1%) achieved an objective response and 30 (78.9%) achieved disease control. The median time to response was 2.8 months (IQR, 2.8-3.58 months), with a median duration of response of 11.7 months (range, 3.57-22.4 months; the response was ongoing at cutoff). Of 16 responses, 8 (50.0%) were ongoing. Most adverse events were grade 1 or 2. For atezolizumab, the most common adverse events were fatigue (6 [15.8%]) and pruritus (6 [15.8%]). For bevacizumab, they were hypertension (10 [26.3%]) and proteinuria (4 [10.5%]). Drug discontinuation occurred in 2 patients receiving atezolizumab (5.3%) and 3 patients receiving bevacizumab (7.9%). PD-L1 levels were not associated with response, PFS, or OS., Conclusions and Relevance: These findings suggest that atezolizumab with bevacizumab is a potential treatment for high-TMB nonsquamous NSCLC., Trial Registration: ClinicalTrials.gov Identifier: NCT03836066.

Introduction: We characterized the safety of first-line nivolumab plus ipilimumab (NIVO+IPI) in a large patient population with metastatic NSCLC and efficacy outcomes after NIVO+IPI discontinuation owing to treatment-related adverse events (TRAEs)., Methods: We pooled data from three first-line NIVO+IPI studies (NIVO, 3 mg/kg or 240 mg every 2 wk; IPI, 1 mg/kg every 6 wk) in metastatic NSCLC (CheckMate 227 part 1, CheckMate 817 cohort A, CheckMate 568 part 1). Safety end points included TRAEs and immune-mediated adverse events (IMAEs) in the pooled population and patients aged 75 years or older., Results: In the pooled population (N = 1255), any-grade TRAEs occurred in 78% of the patients, grade 3 or 4 TRAEs in 34%, and discontinuation of any regimen component owing to TRAEs in 21%. The most frequent TRAE and IMAE were diarrhea (20%; grade 3 or 4, 2%) and rash (17%; grade 3 or 4, 3%), respectively. The most common grade 3 or 4 IMAEs were hepatitis (5%) and diarrhea/colitis and pneumonitis (4% each). Pneumonitis was the most common cause of treatment-related death (5 of 16). Safety in patients aged 75 years or older (n = 174) was generally similar to the overall population, but discontinuation of any regimen component owing to TRAEs was more common (29%). In patients discontinuing NIVO+IPI owing to TRAEs (n = 225), 3-year overall survival was 50% (95% confidence interval: 42.6-56.0), and 42% (31.2-52.4) of 130 responders remained in response 2 years after discontinuation., Conclusions: First-line NIVO+IPI was well tolerated in this large population with metastatic NSCLC and in patients aged 75 years or older. Discontinuation owing to TRAEs did not reduce long-term survival., (Copyright © 2022. Published by Elsevier Inc.)

Aim: Report the final analysis from ASTRIS, the largest real-world study of second-/later-line osimertinib in advanced/metastatic EGFR T790M non-small-cell lung cancer (NSCLC). Methods: Patients with advanced/metastatic EGFR T790M NSCLC and prior EGFR-TKI treatment, received once-daily osimertinib 80 mg. Primary end point: overall survival (OS); secondary end points: progression-free survival (PFS), time-to-treatment discontinuation (TTD) and response rate. Safety was also recorded. Results: In 3014 patients, median OS: 22.8 months (21.6-23.8), median PFS: 11.1 months (11.0-12.0), median TTD: 13.5 months (12.6-13.9), and response rate: 57.3% (55.5-59.2). All end points reported with 95% CIs. Numerically longer median OS was observed in patients with baseline WHO performance status <2 versus 2 (24.0 vs 11.1 months) and those without versus with brain/leptomeningeal metastases (25.4 vs 18.0 months). No new safety signals were identified. Conclusion: Second-/later-line osimertinib demonstrated real-world clinical benefit and safety in advanced/metastatic EGFR T790M NSCLC. Clinical Trial Registration: NCT02474355 (ClinicalTrials.gov).

Objective: In Spain, due to the lack of data at national level a lung cancer registry, the Thoracic Tumour Registry (TTR), was created. Such registry should demonstrate comparability with population-based data to ensure representativeness at population level. The aim is to compare the socio-demographic characteristics of the TTR with incidence data from the Red de Registros de Cáncer (REDECAN) and mortality data from the Instituto Nacional de Estadística (INE)., Method: Lung cancer data sources available to date, REDECAN and INE, were used. Lung cancer cases overall and disaggregated by sex and age groups were collected from each source of information and data were compared for the period 2017-2020. Sex and age group proportions of TTR were calculated for both databases (which collect incidence and mortality data), for the entire study period and broken down by year., Results: A total of 17,109 incident lung cancer cases from the TTR, 58,668 estimated incident cases from REDECAN and 88,083 deaths registered from INE between 2017 and 2020 were included. In terms of sex, the proportions are very similar between the three sources and the differences do not exceed 4%. In terms of age, the differences are not large, being larger for mortality data in the older age group from the INE versus the TTR., Conclusions: The TTR seems to be representative of lung cancer cases diagnosed in Spain between 2019 and 2020, both by sex and age. This allows us to accurately characterise the status of this disease, which is the leading cause of cancer death in Spain, and that the analysis of results obtained from the RTT can be applied to cases of lung cancer diagnosed in our country., (Copyright © 2022 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.)

Background: Alectinib, a highly selective next generation ALK-inhibitor, has exhibited potent anti-tumour activity in RET-rearranged NSCLC in the preclinical stage., Methods: ALERT-lung is a single-arm, phase II trial evaluating the activity of alectinib for the treatment of pretreated RET-rearranged advanced NSCLC. Alectinib was administered orally, 600 mg, twice per day until progression, refusal or unacceptable toxicity (treatment could continue beyond progression, if patient was deriving clinical benefit). Patient recruitment closed prematurely due to discouraging results for alectinib in a phase I/II study in the same indication., Results: All 14 patients who enrolled until the premature accrual closure, received at lease one dose of alectinib. Among them, median age was 61 years, majority (71 %) was female, never smokers, of ECOG PS 1. No objective response (complete or partial response) was recorded. Of the 13 evaluable patients, three (23 %) achieved and maintained disease stabilisation for 24 weeks. Up to 31 March 2021 (median follow-up 15.9 months), 12 PFS-events (92 %) were observed, with median PFS of 3.7 months (95 % C.I.: 1.8 - 7.3 months). Overall, three deaths (23 %) were reported. Seven patients (50 %) experienced grade ≥ 3 adverse events, while three discontinued treatment due to erythema multiforme of grade 3, related to alectinib. No treatment-related serious adverse event was reported., Conclusions: Accrual into our trial was terminated early in response to other reports of limited activity of alectinib in patients with RET-fusion NSCLC and the emergence of more potent selective RET-inhibitors. Also in our trial, alectinib did not show the expected potential for anti-tumour activity in NSCLC., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Enriqueta Felip reports grants for oncology innovation (GOI) from Merck Healthcare KGAa and Fundación Merck Salud, consulting fees from Amgen, Astra Zeneca, Bristol Myers Squibb, Daichii Sankyo, Eli Lilly, F. Hoffmann-La Roche, Glaxo Smith Kline, Janssen, Merck Serono, Merck Sharp & Dohme, Novartis, Peptomyc, Pfizer, Sanofi, and Takeda, payments or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Amgen, Astra Zeneca, Bristol Myers Squibb, Eli Lilly, F. Hoffmann-La Roche, Janssen, Medical Trends, Medscape, Merck Serono, Merck Sharp & Dohme, Peervoice, Pfizer, Sanofi, Takeda, and Touch Oncology, she also reports to be an independent board member of GRÍFOLS. Urania Dafni reports a honorarium as Member of the Tumor Agnostic Evidence Generation working Group of Roche. Thierry Berghmans reports consulting fees from Inhatarget and reported participation on a Data Safety Monitoring Board or Advisory Board for BMS, Bayer, Merck, Janssen, and Roche. Francesco Passiglia reports consulting fees from Merck Sharp and Dohme, Astrazeneca, Janssen, Amgen, and Beigene, payments or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Janssen, Amgen, Pfizer, and ThermoFisher Scientific, support for attending meetings and/or travel from Roche and Amgen, he also reports participation on a Data Safety Monitoring Board or Advisory Board for Amgen and Janssen. Anne-Marie C. Dingemans reports grants or contracts from Amgen, Dutch Cancer Society, and HANART, consulting fees from Amgen, Bayer, Boehringer Ingelheim, Sanofi, and Roche, payments or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Janssen, Pfizer, AstraZeneca, Lilly, and Takeda, reports participation on a Data Safety Monitoring Board or Advisory Board for Takeda and Roche, leadership or fiduciary role in other board, society, committee or advocacy group, paid or unpaid as chair of EORTC LCG (unapaid). Santiago Viteri reports payments or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from MSD, BMS, TAKEDA, CURIO, and ROCHE, payments for expert testimony from REDDY PHARMA IBERIA, support for attending meetings and/or travel from OSE IMMUNOTHERAPEUTHICS, MSD, TAKEDA, and MERCK, reports participation on a data safety monitoring board or advisory board for MERCK, JANSSEN, PUMA, ASTRA ZENECA, BMS, TAKEDA, and ROCHE. Christian Britschgi reports consulting fees from Astra Zeneca, Pfizer, Roche, Takeda, Janssen-Cilag, Boehringer-Ingelheim, support for attending meetings and/or travel from AstraZeneca and Takeda. Sinead Cuffe reports support for attending meetings and/or travel from MSD, BMS, and Pfizer. Mariano Provencio reports grants or contracts from BMS, MSD, Lilly, AZ, and Takeda, consulting fees from BMS, MSD, Lilly, AZ, and Takeda, payments or honoraria for lectures from BMS, MSD, AZ, and Takeda, support for attending meetings from MSD and AZ. Sabine Merkelbach-Bruse reports payments or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from AstraZeneca, QuIP, Targos, Roche, Novartis, GSK, Molecular Health, Janssen, BMS, and MSD, support for attending meetings and/or travel from BMS, reports participation on a Data Safety Monitoring Board or Advisory Board for AstraZeneca, Roche, Novartis, GSK, Molecular Health, Janssen, Merck, Amgen, and Onkowissen. Solange Peters reports grants/research support from Amgen, AstraZeneca, Beigene, Bristol-Myers Squibb, GSK,Merck Sharp and Dohme, and Roche/Genentech, consulting fees from AbbVie, Amgen, Arcus, AstraZeneca, Bayer, Beigene, Biocartis, BioInvent, Blueprint Medicines, Boehringer Ingelheim, Bristol-Myers Squibb, Clovis, Daiichi Sankyo, Debiopharm, ecancer, Eli Lilly, Elsevier, F-Star, Fishawack, Foundation Medicine, Genzyme, Gilead, GSK, Illumina, Imedex, IQVIA, Incyte, iTeos, Janssen,Medscape, Merck Sharp and Dohme, Merck Serono, Merrimack, Novartis, Novocure, OncologyEducation, Pharma Mar, Phosplatin Therapeutics, PER, Pfizer, PRIME, Regeneron, RMEI, Roche/Genentech, RTP, Sanofi, Seattle Genetics, Takeda, and Vaccibody, payments or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, ecancer, Eli Lilly, Foundation Medicine, Illumina, Imedex, Medscape, Merck Sharp and Dohme, Mirati, Novartis, PER, Pfizer, Prime, Roche/Genentech, RTP, Sanofi, and Takeda. Jürgen Wolf reports participation on advisory boards for Amgen, AstraZeneca, Bayer, Blueprint, BMS, Boehringer-Ingelheim, Chugai, Daiichi Sankyo, Ignyta, Janssen, Lilly, Loxo, MSD, Novartis, Pfizer, Roche, Seattle Genetics, and Takeda, reports lecture fees from Amgen, AstraZeneca, Bayer, Blueprint, BMS, Boehringer-Ingelheim, Chugai, Daiichi Sankyo, Ignyta, Janssen, Lilly, Loxo, MSD, Novartis, Pfizer, Roche, Seattle Genetics, and Takeda, reports research support to institution from BMS, Janssen Pharmaceutica, Novartis, Pfizer. Rolf A. Stahel reports grants or contracts from AstraZeneca, BMS, Daiichi Sankyo, Celgene, Ipsen, Janssen, Mirati, MSD, Novartis, Pfizer, Pierre Fabre, and Roche. Consulting fees from AstraZeneca, BMS, Boehringer Ingelheim, Janssen, Merck, MSD, Novartis, Novocure, Pfizer, and Roche, payments or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Amgen, AstraZeneca, Blueprint, Boehringer Ingelheim, GSK, MSD, Roche, and Sandoz, he also reports participation on a data safety monitoring board or advisory board for Genentech/Roche, MSD, and Takeda. All other authors declare no conflicts of interest., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Purpose: Neoadjuvant chemotherapy plus nivolumab has been shown to be effective in resectable non-small-cell lung cancer (NSCLC) in the NADIM trial (ClinicalTrials.gov identifier: NCT03081689). The 3-year overall survival (OS) and circulating tumor DNA (ctDNA) analysis have not been reported., Methods: This was an open-label, multicenter, single-arm, phase II trial in which patients with stage IIIA NSCLC, who were deemed to be surgically resectable, were treated with neoadjuvant paclitaxel (200 mg/m 2 once a day) and carboplatin (area under curve 6) plus nivolumab (360 mg) once on day 1 of each 21-day cycle, for three cycles, followed by adjuvant nivolumab monotherapy for 1 year (240 mg once every 2 weeks for 4 months, followed by 480 mg once every 4 weeks for 8 months). The 3-year OS and ctDNA analysis were secondary objectives of the trial., Results: OS at 36 months was 81.9% (95% CI, 66.8 to 90.6) in the intention-to-treat population, rising to 91.0% (95% CI, 74.2 to 97.0) in the per-protocol population. Neither tumor mutation burden nor programmed cell death ligand-1 staining was predictive of survival. Conversely, low pretreatment levels of ctDNA were significantly associated with improved progression-free survival and OS (hazard ratio [HR], 0.20; 95% CI, 0.06 to 0.63, and HR, 0.07; 95% CI, 0.01 to 0.39, respectively). Clinical responses according to RECIST v1.1 criteria did not predict survival outcomes. However, undetectable ctDNA levels after neoadjuvant treatment were significantly associated with progression-free survival and OS (HR, 0.26; 95% CI, 0.07 to 0.93, and HR, 0.04; 95% CI, 0.00 to 0.55, respectively). The C-index to predict OS for ctDNA levels after neoadjuvant treatment (0.82) was superior to that of RECIST criteria (0.72)., Conclusion: The efficacy of neoadjuvant chemotherapy plus nivolumab in resectable NSCLC is supported by 3-year OS. ctDNA levels were significantly associated with OS and outperformed radiologic assessments in the prediction of survival.

Background: Neoadjuvant chemoimmunotherapy for non-small cell lung cancer (NSCLC) has improved pathological responses and survival rates compared with chemotherapy alone, leading to Food and Drug Administration (FDA) approval of nivolumab plus chemotherapy for resectable stage IB-IIIA NSCLC (AJCC 7th edition) without ALK or EGFR alterations. Unfortunately, a considerable percentage of tumors do not completely respond to therapy, which has been associated with early disease progression. So far, it is impossible to predict these events due to lack of knowledge. In this study, we characterized the gene expression profile of tumor samples to identify new biomarkers and mechanisms behind tumor responses to neoadjuvant chemoimmunotherapy and disease recurrence after surgery., Methods: Tumor bulk RNA sequencing was performed in 16 pretreatment and 36 post-treatment tissue samples from 41 patients with resectable stage IIIA NSCLC treated with neoadjuvant chemoimmunotherapy from NADIM trial. A panel targeting 395 genes related to immunological processes was used. Tumors were classified as complete pathological response (CPR) and non-CPR, based on the total absence of viable tumor cells in tumor bed and lymph nodes tested at surgery. Differential-expressed genes between groups and pathway enrichment analysis were assessed using DESeq2 and gene set enrichment analysis. CIBERSORTx was used to estimate the proportions of immune cell subtypes., Results: CPR tumors had a stronger pre-established immune infiltrate at baseline than non-CPR, characterized by higher levels of IFNG, GZMB, NKG7 , and M1 macrophages, all with a significant area under the receiver operating characteristic curve (ROC) >0.9 for CPR prediction. A greater effect of neoadjuvant therapy was also seen in CPR tumors with a reduction of tumor markers and IFNγ signaling after treatment. Additionally, the higher expression of several genes, including AKT1, BST2, OAS3, or CD8B ; or higher dendritic cells and neutrophils proportions in post-treatment non-CPR samples, were associated with relapse after surgery. Also, high pretreatment PD-L1 and tumor mutational burden levels influenced the post-treatment immune landscape with the downregulation of proliferation markers and type I interferon signaling molecules in surgery samples., Conclusions: Our results reinforce the differences between CPR and non-CPR responses, describing possible response and relapse immune mechanisms, opening the possibility of therapy personalization of immunotherapy-based regimens in the neoadjuvant setting of NSCLC., Competing Interests: Competing interests: MP reports non-financial support (reagents for TCR sequencing) from ThermoFisher; grants, personal fees and non-financial support from BMS; grants, personal fees and non-financial support from ROCHE; grants, personal fees and non-financial support from ASTRAZENECA; personal fees from MSD; personal fees from TAKEDA; outside the submitted work. EN grants or contracts: Roche, Pfizer, Merck-Serono, BMS, and Nanostring. Consulting fees: Roche, BMS, MSD, Merck-Serono, Pfizer, Lilly, Amgen, Boehringer, AstraZeneca, Takeda, Bayer, and Sanofi. Payment honoraria: Roche, BMs, MSD, Merck-Serono, Pfizer, Lilly, Amgen, Boehringer, Astrazeneca, Takeda, Bayer, and Sanofi. Support For attending meetings and travel: MSD, Roche, and BMS. AI consulting fees: Pfizer, Amgen, and AstraZeneca. Payment for expert testimony: Bristol, Pfizer, Takeda, Roche, and AstraZeneca. Support for attending meetings or travels: Roche and Bristol. MRG-C reports personal fees from BMS, personal fees from MSD, personal fees from Roche, personal fees from Pfizer, personal fees from AstraZeneca, outside the submitted work; ML-Q: payment for honoraria: BMS, MSD, Ipsen, Astella, AstraZeneca, and Pfizer. Support for attendings meetings/travels: MSD, Takeda, Janssen, Pfizer, and BMS. MD reports personal fees from Astra-Zeneca, personal fees from BMS, personal fees from Boehringer Ingelheim, personal fees from MSD, personal fees from Pfizer, personal fees from Roche, outside the submitted work; MM reports grants and personal fees from BMS, personal fees and non-financial support from MSD, personal fees and non-financial support from Boehringer Ingelheim; personal fees, non-financial support, and other from AstraZeneca; personal fees, non-financial support, and other from Roche; personal fees from Kyowa Kyrin; personal fees from Pierre Fabre, outside the submitted work; DR-A: consulting fees: Roche, AstraZeneca, BMS, MSD, Lilly, Pfizer, and Novartis. Payment for honoraria: Roche, Astrazeneca, BMS, MSD, Lilly, Pfizer, and Novartis. Support for attending meetings/travels: Roche, MSD, and Novartis; AM-M: advisory board: AstraZeneca, BMS, Roche, MSD, and Pfizer. Speaker's bureau: AstraZeneca, BMS, Roche, MSD, and Pfizer. Support for attending meetings or travel: AstraZeneca, BMS, Roche, MSD, Pfizer, and Lilly. Payment for expert testimony: AstraZeneca. Steering committee member: AstraZeneca. JDCC reports personal fees from Astra Zeneca, personal fees from Boehringer Ingelheim, personal fees from Merck Sharp and Dohme, personal fees from Hoffmann-la Roche, personal fees from Bristol-Myers Squibb, personal fees from Takeda, personal fees from Pfizer, personal fees from Novartis, outside the submitted work; IBA reports consulting or advisory board for Bristol Myers, Takeda, Roche, AstraZeneca, and Behringer Inngelheim; BM reports grants and personal fees from Roche, personal fees and other from BMS, personal fees from Takeda, other from MSD, personal fees from Boehringer, other from Takeda, outside the submitted work; AR: consulting fees: AstraZeneca. Payment or honoraria: Vivo diagnóstico. Advisory board: Takeda. VC: payment or honoraria: Roche, BMS, MSD, AstraZeneca, and Boehringer., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: The survival of patients with lung cancer has substantially increased in the last decade by about 15%. This increase is, basically, due to targeted therapies available for advanced stages and the emergence of immunotherapy itself. This work aims to study the situation of biomarker testing in Spain., Patients and Methods: The Thoracic Tumours Registry (TTR) is an observational, prospective, registry-based study that included patients diagnosed with lung cancer and other thoracic tumours, from September 2016 to 2020. This TTR study was sponsored by the Spanish Lung Cancer Group (GECP) Foundation, an independent, scientific, multidisciplinary oncology society that coordinates more than 550 experts and 182 hospitals across the Spanish territory., Results: Nine thousand two hundred thirty-nine patients diagnosed with stage IV non-small cell lung cancer (NSCLC) between 2106 and 2020 were analysed. 7,467 (80.8%) were non-squamous and 1,772 (19.2%) were squamous. Tumour marker testing was performed in 85.0% of patients with non-squamous tumours vs 56.3% in those with squamous tumours (p-value < 0.001). The global testing of EGFR, ALK, and ROS1 was 78.9, 64.7, 35.6% respectively, in non-squamous histology. PDL1 was determined globally in the same period (46.9%), although if we focus on the last 3 years it exceeds 85%. There has been a significant increase in the last few years of all determinations and there are even close to 10% of molecular determinations that do not yet have targeted drug approval but will have it in the near future. 4,115 cases had a positive result (44.5%) for either EGFR, ALK, KRAS, BRAF, ROS1, or high PDL1., Conclusions: Despite the lack of a national project and standard protocol in Spain that regulates the determination of biomarkers, the situation is similar to other European countries. Given the growing number of different determinations and their high positivity, national strategies are urgently needed to implement next-generation sequencing (NGS) in an integrated and cost-effective way in lung cancer., (© 2022. The Author(s).)

Introduction: Residential radon is considered the second cause of lung cancer and the first in never smokers. Nevertheless, there is little information regarding the association between elevated radon levels and small cell lung cancer (SCLC). We aimed to assess the effect of residential radon exposure on the risk of SCLC in general population through a multicentric case-control study., Methods: A multicentric hospital-based case-control study was designed including 9 hospitals from Spain and Portugal, mostly including radon-prone areas. Indoor radon was measured using Solid State Nuclear Track Detectors at the Galician Radon Laboratory., Results: A total of 375 cases and 902 controls were included, with 24.5% of cases being women. The median number of years living in the measured dwelling was higher than 25 years for both cases and controls. There was a statistically significant association for those exposed to concentrations higher than the EPA action level of 148Bq/m 3 , with an Odds Ratio of 2.08 (95%CI: 1.03-4.39) compared to those exposed to concentrations lower than 50Bq/m 3 . When using a dose-response model with 100Bq/m 3 as a reference, it can be observed a linear effect for small cell lung cancer risk. Smokers exposed to higher radon concentrations pose a much higher risk of SCLC compared to smokers exposed to lower indoor radon concentrations., Conclusions: Radon exposure seems to increase the risk of small cell lung cancer with a linear dose-response pattern. Tobacco consumption may also produce an important effect modification for radon exposure., (Copyright © 2021 SEPAR. Published by Elsevier España, S.L.U. All rights reserved.)

Background: The ETOP 10-16 BOOSTER trial failed to demonstrate a progression-free survival (PFS) benefit for adding bevacizumab to osimertinib in second line. An exploratory subgroup analysis, however, suggested a PFS benefit of the combination in patients with a smoking history and prompted us to do this study., Methods: A systematic review and meta-analysis to evaluate the differential effect of smoking status on the benefit of adding an angiogenesis inhibitor to epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor therapy was carried out. All relevant randomized controlled trials appearing in main oncology congresses or in PubMed as of 1 November 2021 were used according to the Preferred Reporting Items for Systematic Review and Meta-Analyses statement. Primarily PFS according to smoking status, and secondarily overall survival (OS) were of interest. Pooled and interaction hazard ratios (HRs) were estimated by fixed or random effects models, depending on the detected degree of heterogeneity. Bias was assessed using the revised Cochrane tool for randomized controlled trials (RoB 2)., Results: Information by smoking was available for 1291 patients for PFS (seven studies) and 678 patients for OS (four studies). The risk of bias was low for all studies. Combination treatment significantly prolonged PFS for smokers [n = 502, HR = 0.55, 95% confidence interval (CI): 0.44-0.69] but not for nonsmokers (n = 789, HR = 0.92, 95% CI: 0.66-1.27; treatment-by-smoking interaction P = 0.02). Similarly, a significant OS benefit was found for smokers (n = 271, HR = 0.66, 95% CI: 0.47-0.93) but not for nonsmokers (n = 407, HR = 1.07, 95% CI: 0.82-1.42; treatment-by-smoking interaction P = 0.03)., Conclusion: In advanced EGFR-non-small-cell lung cancer patients, the addition of an angiogenesis inhibitor to EGFR-tyrosine kinase inhibitor therapy provides a statistically significant PFS and OS benefit in smokers, but not in non-smokers. The biological basis for this observation should be pursued and could determine whether this might be due to a specific co-mutational pattern produced by tobacco exposure., Competing Interests: Disclosure UD reports honorarium as Member of the Tumor Agnostic Evidence Generation working Group of Roche, outside the submitted work. RASo reports advisory role for Amgen, AstraZeneca, Bayer, Bristol Myers Squibb (BMS), Boehringer Ingelheim, Lily, Merck, Novartis, Pfizer, Roche, Taiho, Takeda, and Yuhan and grants from AstraZeneca, Boehringer Ingelheim, outside the submitted work. SP reports grants from Amgen, AstraZeneca, Boehringer Ingelheim, BMS, Clovis, F. Hoffman-La Roche, Illumina, Novartis, Pfizer, Merck Sharp & Dohme (MSD), personal fees from Amgen, AbbVie, AstraZeneca, Bayer, Biocartis, Boehringer Ingelheim, BMS, Clovis, Daiichi Sankyo, Debiopharm, Eli Lilly, F. Hoffman-La Roche, Foundations Medicine, Illumina, Janssen, Novartis, PharmaMar, Pfizer, Regeneron, Sanofi, Seattle Genetics, Takeda, MSD, Merck Serono, Merrimack, Medscape, Phosphoplatin Therapeutics, Beigene, Imedex, outside the submitted work. JDC reports grants and personal fees from AstraZeneca, BMS, MSD, and Hoffmann-La Roche, personal fees from Bayer, Boehringer Ingelheim, GlaxoSmithKline (GSK), Jansen-Cilag, Lilly, Novartis, Pfizer, and Takeda, outside the submitted work. LC reports advisory role for AstraZeneca, Roche, and Daichi, outside the submitted work. MF reports grants from AstraZeneca and BMS and other support AstraZeneca, BMS, Boehringer Ingelheim, Janssen, MSD, Pfizer, Roche, and Takeda, outside the submitted work. EN reports grants, personal fees, and non-financial support from Roche, personal fees and non-financial support from AstraZeneca, grants, personal fees and non-financial support from BMS, personal fees and non-financial support from MSD, grants and personal fees from Merck Serono, personal fees from Takeda, grants, personal fees, and non-financial support from Pfizer, personal fees from Lilly, personal fees from Bayer, personal fees from Amgen, personal fees from Boehringer Ingelheim, outside the submitted work. EC reports personal fees from AstraZeneca, Amgen, BMS, MSD, and Roche, outside the submitted work. MAS reports advisory role for Roche and Boehringer Ingelheim, speaker role for Pierre Fabre, and travel grants from Roche and PharmaMar, outside the submitted work. RB reports payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Roche, AstraZeneca, BMS, Amgen, and MSD, participation on Data Safety Monitoring Board or Advisory Board for AstraZeneca, BMS, and Roche, outside the submitted work. MP reports grants, personal fees, and non-financial support from AstraZeneca, BMS, and Roche, personal fees from MSD and Takeda, outside the submitted work. SC reports non-financial support from Pfizer, Roche, MSD, BMS, outside the submitted work. RASt reports consultant or advisory role for AstraZeneca, BMS, Boehringer Ingelheim, GSK, MSD, Pfizer, Roche, Sandoz, Seattle Genetics, Takeda, speaker honoraria from Amgen, AstraZeneca, Blueprint, BMS, Boehringer Ingelheim, GSK, MSD, Novartis, Roche, Data Monitoring Committee (DMC) role from Genentech/Roche and Takeda, and financial support for ETOP and IBCSG trials (where he is president), from AstraZeneca, BMS, Daiichi Sankyo, Celgene, Ipsen, Janssen, Mirati, MSD, Novartis, Pfizer, Pierre Fabre, Roche. All other authors have declared no conflicts of interest., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: Our understanding of the immunopathology of resectable non-small cell lung cancer (NSCLC) is still limited. Here, we explore immune programs that inform of tumor immunity and response to neoadjuvant chemotherapy and chemoimmunotherapy in localized NSCLC., Experimental Design: Targeted immune gene sequencing using the HTG Precision Immuno-Oncology panel was performed in localized NSCLCs from three cohorts based on treatment: naïve (n = 190), neoadjuvant chemotherapy (n = 38), and neoadjuvant chemoimmunotherapy (n = 21). Tumor immune microenvironment (TIME) phenotypes were based on the location of CD8+ T cells (inflamed, cold, excluded), tumoral PD-L1 expression (<1% and ≥1%), and tumor-infiltrating lymphocytes (TIL). Immune programs and signatures were statistically analyzed on the basis of tumoral PD-L1 expression, immune phenotypes, and pathologic response and were cross-compared across the three cohorts., Results: PD-L1-positive tumors exhibited increased signature scores for various lymphoid and myeloid cell subsets (P < 0.05). TIME phenotypes exhibited disparate frequencies by stage, PD-L1 expression, and mutational burden. Inflamed and PD-L1+/TILs+ NSCLCs displayed overall significantly heightened levels of immune signatures, with the excluded group representing an intermediate state. A cytotoxic T-cell signature was associated with favorable survival in neoadjuvant chemotherapy-treated NSCLCs (P < 0.05). Pathologic response to chemoimmunotherapy was positively associated with higher expression of genes involved in immune activation, chemotaxis, as well as T and natural killer cells (P < 0.05 for all). Among the three cohorts, chemoimmunotherapy-treated NSCLCs exhibited the highest scores for various immune cell subsets including T effector and B cells (P < 0.05)., Conclusions: Our findings highlight immune gene programs that may underlie host tumor immunity and response to neoadjuvant chemotherapy and chemoimmunotherapy in resectable NSCLC., (©2022 American Association for Cancer Research.)