BACKGROUND: Tobacco is the main risk factor for developing lung cancer. Yet, while some heavy smokers develop lung cancer at a young age, other heavy smokers never develop it, even at an advanced age, suggesting a remarkable variability in the individual susceptibility to the carcinogenic effects of tobacco. We characterized the germline profile of subjects presenting these extreme phenotypes with Whole Exome Sequencing (WES) and Machine Learning (ML). METHODS: We sequenced germline DNA from heavy smokers who either developed lung adenocarcinoma at an early age (extreme cases) or who did not develop lung cancer at an advanced age (extreme controls), selected from databases including over 6600 subjects. We selected individual coding genetic variants and variant-rich genes showing a significantly different distribution between extreme cases and controls. We validated the results from our discovery cohort, in which we analysed by WES extreme cases and controls presenting similar phenotypes. We developed ML models using both cohorts. FINDINGS: Mean age for extreme cases and controls was 50.7 and 79.1 years respectively, and mean tobacco consumption was 34.6 and 62.3 pack-years. We validated 16 individual variants and 33 variant-rich genes. The gene harbouring the most validated variants was HLA-A in extreme controls (4 variants in the discovery cohort, p = 3.46E-07; and 4 in the validation cohort, p = 1.67E-06). We trained ML models using as input the 16 individual variants in the discovery cohort and tested them on the validation cohort, obtaining an accuracy of 76.5% and an AUC-ROC of 83.6%. Functions of validated genes included candidate oncogenes, tumour-suppressors, DNA repair, HLA-mediated antigen presentation and regulation of proliferation, apoptosis, inflammation and immune response. INTERPRETATION: Individuals presenting extreme phenotypes of high and low risk of developing tobacco-associated lung adenocarcinoma show different germline profiles. Our strategy may allow the identification of high-risk subjects and the development of new therapeutic approaches. FUNDING: See a detailed list of funding bodies in the Acknowledgements section at the end of the manuscript.

Bioinformatics Platform Cima and IdisNA University of Navarra Pamplona Spain

CIMA LAB Diagnostics and IdisNA University of Navarra Pamplona Spain

Computational Biology Program Cima Data Science and Artificial Intelligence Institute CCUN IdisNA and CIBERONC University of Navarra Pamplona Spain

Department of Biotechnology Universitat Politècnica de València Unidad Mixta TRIAL and CIBERONC Valencia Spain

Department of Medical Oncology Hospital General Universitario de Valencia Unidad Mixta TRIAL Valencia Spain

Department of Medical Oncology Hospital La Luz Quirón Madrid Spain

Department of Oncology CUN CCUN and IdisNA University of Navarra Pamplona Spain

Department of Oncology CUN CCUN IdisNA and CIBERONC University of Navarra Pamplona Spain

Department of Oncology CUN Division of Immunology Cima CCUN IdisNA and CIBERONC University of Navarra Pamplona Spain

Department of Pediatrics and Clinical Genetics Clínica Universidad de Navarra University of Navarra Pamplona Spain

Department of Radiology CUN CCUN and IdisNA Pamplona Spain

Division of Immunology Cima and Immunotherapy CUN CCUN IdisNA and CIBERONC University of Navarra Pamplona Spain

Electrical and Electronic Engineering Department Tecnun DATAI University of Navarra San Sebastian Spain

Electrical and Electronic Engineering Department Tecnun University of Navarra San Sebastian Spain

Institute for Clinical Chemistry and Laboratory Medicine Mildred Scheel Early Career Center National Center for Tumor Diseases Dresden University Hospital and Faculty of Medicine Medical Clinic 1 University Hospital Carl Gustav Carus Technische Universität Dresden Dresden Germany Laboratory of Cancer Cell Biology Institute of Molecular Genetics of the Czech Academy of Sciences Prague Czech Republic

Program in Solid Tumors Cima CCUN Department of Biochemistry and Genetics School of Science IdisNA and CIBERONC University of Navarra Pamplona Spain

Program in Solid Tumors Cima Department of Pathology Anatomy and Physiology Schools of Medicine and Sciences CCUN IdisNA and CIBERONC University of Navarra Pamplona Spain

Pulmonary Critical Care and Sleep Division Mount Sinai Morningside Hospital New York USA

Pulmonary Department CUN CCUN and Centro de Investigación Biomédica en Red de Enfermedades Respiratorias University of Navarra Madrid Spain

Pulmonary Department CUN CCUN and IdisNA University of Navarra Pamplona Spain

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