Sherlock-Lung: Tracing Lung Cancer Mutational Processes in Never Smokers

Lung cancer is the leading cause of cancer mortality worldwide, and lung cancers arising in people who have never smoked (LCINS) account for an estimated 10–25% of all lung cancer cases. LCINS, most commonly presenting as lung adenocarcinoma (NS-LUAD), shows marked demographic variation, including higher incidence in females and individuals of East Asian ancestry, as well as molecular and clinical features that differ from lung cancer in subjects who smoke.

Although exposure to air pollution, radon, second-hand tobacco smoke, asbestos, several additional environmental and occupational factors, and lung infections are established risk factors, a substantial proportion of LCINS remains poorly understood, limiting opportunities for prevention, early detection, and tailored therapy. Mutational signature analyses indicate that most NS-LUAD are dominated by endogenous mutagenic processes, some of unknown origin, and only a minor subset shows evidence of combustion-related exposures. It is unclear why NS-LUAD has heterogenous demographic distributions, driver mutation patterns such as the predominance of EGFR mutations, and varied clinical behavior.

Sherlock-Lung (doi: 10.1093/aje/kwaa234) is the largest and most comprehensive international effort to characterize LCINS to date and is designed to address these gaps. This retrospective, case-only study integrates whole-genome and transcriptome sequencing, genome-wide DNA methylation profiling, microbiome analysis, histopathology, AI, and imaging with detailed clinical, demographic, environmental, and occupational data.

Sherlock-Lung has two major aims: (1) to characterize the genomic architecture and evolutionary history of LCINS, using genomic alterations as molecular footprints of the mutational processes underlying disease etiology and tumor development; and (2) to establish an integrated molecular, histologic, and radiologic classification of LCINS to identify biologically distinct subtypes and their associations with etiologic factors, tumor evolution, and clinical outcomes. Since LCINS represents a clinical entity with distinct epidemiology and tumor biology, insights from Sherlock-Lung are critical for uncovering lung cancer causes beyond tobacco exposure. Weaving together Sherlock-Lung current genomic, environmental, and experimental findings, LCINS appear to have distinct mechanistic subtypes defined by specific mutational processes, driver landscapes, ancestry-associated vulnerabilities, and potentially divergent cells of origin. A mechanistic understanding of tumor heterogeneity is required to enable a biology-driven framework for risk stratification, early detection, and therapeutic intervention. 

The Sherlock-Lung study is a large-scale effort to characterize LCINS molecular drivers, tumor evolution, and molecular processes, and to develop an integrated molecular, histologic, and radiologic classification of these tumors. Building on the successful Phase 1 effort analyzing genomic data from over 1,200 subjects, the study has expanded to include ~3,000 multi-ethnic, geographically diverse lung cancer cases. Sherlock’s resource comprises deep whole-genome sequencing from ~3,000 individuals; RNA sequencing from ~1,100 individuals; DNA methylation profiling ~1,800 individuals; histological images from all cases, and CT scan imaging from ~700 individuals.

Multi-omic data, including whole-genome, whole-transcriptome, methylome, and microbiome profiles are being analyzed to map the genomic landscape of LCINS and to identify exogenous and endogenous processes that contribute to lung tumorigenesis. In a subset of cases, additional studies will interrogate tumor cells of origin, normal-to-tumor trajectories, and the tumor microenvironment (including spatial transcriptomics), leveraging single-cell and oligo-cell sequencing approaches. These molecular findings are integrated with histologic and radiologic features to refine LCINS classification and to inform prognostic and therapeutic stratification. Complementing tumor-focused analyses, Sherlock-Lung also includes a large germline short-long-read and long-read whole genome sequencing analysis to detect single nucleaotide variants (including those with rare frequency) structural variants and other difficult-to-capture variant classes and non-coding regulatory regions. Germline findings are then linked to tumor molecular phenotypes, including genomic alterations, mutational processes, epigenomic states, and transcriptional programs to connect inherited risk with downstream tumor biology.

Findings from LCINS are compared with those from lung cancer in subjects who smoke to investigate differences and similarities between the two cancer types and obtain information for improved prevention, interception, prognostication, and treatment. To this end, we integrated Sherlock-Lung with EAGLE (doi: 10.1186/1471-2458-8-203)  and multiple public datasets, currently including data and biospecimens from >6,200 individuals worldwide, of whom >4,200 cases with ongoing multi-omics profiling. 

Australia

• QIMR Berghofer
• University of Queensland Thoracic Research Centre

Barbados & Jamaica

• African Caribbean Cancer Consortium
• University of the West Indies

Brazil

• A. C. Camargo Cancer Center
• Hospital de Amor Barretos

Canada

• University Health Network Toronto
• University of Laval
• University of Montreal

Chile

• Universidad del Desarrollo

China

• University of Hong Kong

Czechia

• Charles University
• Palacky University

Colombia

• Foundation Clinical & Applied Cancer Research
• Fundacion Valle de Lili

France

• Centre Hospitalier Universitaire de Nice
• International Agency for Research on Cancer
• Université Côte d’Azur

Israel

• Hadassah Cancer Research Institute
• The Israeli Biorespository Network for Research

Italy

• IRCCS INRCA
• Scientific Institute for Research and Health Casa Sollievo Della Sofferenza
• University of Milan

Mexico

• Instituto Nacional de Cancerología (INCan)

Nigeria

• Institute of Human Virology

Peru

• Instituto Nacional de Enfermedades Neoplasicas

Poland

• Maria Skłodowska-Curie National Research Institute of Oncology

Russia

• N.N. Blokhin National Medical Research Centre of Oncology

Serbia

• Clinical Center of Serbia

South Korea

• Yonsei University Health System

Spain

• Biobanco Hospital Ramon y Cajal
• Biobanco Vasco
• National Network Respiratory Research
• Red Valenciana de Biobancos
• Spanish National Cancer Research Center
• Universidad de Salamanca
• Universidad Santiago de Compostela

Taiwan

• National Health Research Institutes

United Kingdom

• The Institute of Cancer Research
• University of Cambridge
• University of Manchester
• University of Cambridge

United States of America

• Baylor College of Medicine
• Cancer Genomics Research Laboratory, DCEG, NCI
• Center for Cancer Research, NCI
• Cornell University
• Florida-H. Lee Moffitt Cancer Center & Research Institute
• Harvard University
• Mayo Clinic
• Memorial Sloan Kettering Cancer Center
• Multi-ancestry Cancer Genomics Atlas
• National Cancer Institute Technology Transfer Center
• National Institute of Environmental Health Sciences
• Princeton University
• Roswell Park Comprehensive Cancer Center
• Stanford University
• University of California San Diego
• University of California San Francisco
• University of Chicago
• Yale University

Uruguay

• Banco de Tumores

Tracing lung cancer risk factors through mutational signatures in never-smokers

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Genomic and evolutionary classification of lung cancer in never smokers

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Distinct Genomic Landscape of Lung Adenocarcinoma from Household Use of Smoky Coal

• Zhang T, Hoang PH, Wong JYY, Yang K, Chen K, Wong MP, Vermeulen RCH; Xuanwei study team; Huang Y, Chanock SJ, Rothman N, Lan Q, Landi MT; Xuanwei study team members. Distinct Genomic Landscape of Lung Adenocarcinoma from Household Use of Smoky Coal. Am J Respir Crit Care Med. 2023 Sep 15;208(6):733-736. doi: 10.1164/rccm.202302-0340LE. PMID: 37406454; PMCID: PMC10515572. 

The mutagenic forces shaping the genomic landscape of lung cancer in never smokers

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Microbiome analysis of 940 lung cancers in never-smokers reveals lack of clinically relevant associations

• McElderry JP, Zhang T, Zhao W, Hoang PH, Anyaso-Samuel S, Sang J, Khandekar A, Hartman C, Colón-Matos FJ, Miraftab M, Saha M, Lee O, Sharma S, Jones KM, Zhu B, Díaz-Gay M, Mas L, Arrieta O, Edell ES, Santamaría JM, Schabath MB, Yendamuri S, Manczuk M, Lissowska J, Świątkowska B, Mukeria A, Shangina O, Zaridze D, Holcatova I, Janout V, Mates D, Ognjanovic S, Savic M, Kontic M, Bossé Y, Gould Rothberg BE, Christiani DC, Gaborieau V, Brennan P, Liu G, Hofman P, Wong MP, Leung KC, Chen CY, Hsiung CA, Rothman N, Leduc C, Baine MK, Travis WD, Sholl LM, Joubert P, Homer R, Yang SR, Lan Q, Nowak MA, Wedge DC, Alexandrov LB, Chanock SJ, Vogtmann E, Abnet CC, Shi J, Landi MT. Microbiome analysis of 940 lung cancers in never-smokers reveals lack of clinically relevant associations. Nat Commun. 2025 Dec 12;17(1):192. doi: 10.1038/s41467-025-66780-y. PMID: 41387456; PMCID: PMC12780107. 

Inflammatory diseases and risk of lung cancer among individuals who have never smoked

• D'Arcy ME, Pfeiffer RM, Bradley MC, Hoang PH, Tran TV, McElderry JP, Li M, Kebede M, DellaValle CT, Rivas S, Wang Y, Gadalla SM, Landi MT. Inflammatory diseases and risk of lung cancer among individuals who have never smoked. Nat Commun. 2025 Jun 2;16(1):5095. doi: 10.1038/s41467-025-56803-z. PMID: 40456733; PMCID: PMC12130270.

Genomic characterization of lung cancer in never-smokers using deep learning

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A prognostic signature for lung adenocarcinoma in people who have never smoked

• Zhao W, Zhang T, Hua X, Hoang PH, Miraftab M, Saha M, McElderry JP, Sang J, Lee OW, Hartman C, Khandekar A, Sharma S, Colón-Matos FJ, Anyaso-Samuel S, Wang D, Jones K, Hutchinson A, Hicks B, Rosenbaum J, Zhong X, Yang Y, Pesatori AC, Consonni D, Christiani DC, Leung KC, Wong MP, Manczuk M, Lissowska J, Świątkowska B, Mukeria A, Shangina O, Zaridze D, Holcatova I, Mates D, Milosavljevic S, Ognjanovic S, Savic M, Kontic M, Gaborieau V, Brennan P, Arrieta O, Bossé Y, Edell ES, Schabath MB, Hofman P, Mas L, Yendamuri SS, Chen CY, Chang IS, Hsiung CA, Liu G, Martinez Santamaría J, Gould Rothberg BE, Mutreja K, Lawrence S, Rothman N, Alexandrov LB, Leduc C, Baine MK, Joubert P, Sholl LM, Travis WD, Homer R, Lan Q, Chanock SJ, Yang L, Yang SR, Shi J, Landi MT. A Prognostic Signature for Lung Adenocarcinoma in Patients Who Have Never Smoked. Cancer Discov. 2026 Mar 2;16(3):460-477. doi: 10.1158/2159-8290.CD-25-0581. PMID: 41165571; PMCID: PMC12822368.

Uncovering the role of LINE-1 in the evolution of lung adenocarcinoma

• Zhang T, Zhao W, Wirth C, Díaz-Gay M, Yin J, Cecati M, Marchegiani F, Hoang PH, Leduc C, Baine MK, Travis WD, Sholl LM, Joubert P, Sang J, McElderry JP, Antony M, Klein A, Khandekar A, Hartman C, Rosenbaum J, Colón-Matos FJ, Miraftab M, Saha M, Lee OW, Jones KM, Caporaso NE, Wong MP, Leung KC, Hsiung CA, Chen CY, Edell ES, Santamaría JM, Schabath MB, Yendamuri SS, Manczuk M, Lissowska J, Świątkowska B, Mukeria A, Shangina O, Zaridze D, Holcatova I, Mates D, Milosavljevic S, Savic M, Bossé Y, Rothberg BEG, Christiani DC, Gaborieau V, Brennan P, Liu G, Hofman P, Homer R, Yang SR, Pesatori AC, Consonni D, Yang L, Zhu B, Shi J, Brown K, Rothman N, Chanock SJ, Alexandrov LB, Choi J, Cardelli M, Lan Q, Nowak MA, Wedge DC, Landi MT. Uncovering the role of LINE-1 in the evolution of lung adenocarcinoma. Nature. 2026 Feb;650(8100):230-241. doi: 10.1038/s41586-025-09825-y. Epub 2025 Dec 10. PMID: 41372401; PMCID: PMC12823094.

• Many Lung Cancers Are Now in Nonsmokers. Scientists Want to Know Why
• NCI Symposium on Mutation Signatures and Cancer: Future Directions

Data from Sherlock-Lung are shared in accordance with NIH policies and are accessible to qualified investigators. For inquiries, contact:

•    Maria Teresa Landi, M.D., Ph.D. – landim@mail.nih.gov  
•    Phuc H. Hoang, Ph.D. – phuc.hoang@nih.gov

Lead Investigator

• Maria Teresa Landi, M.D., Ph.D. – Senior Investigator, Integrative Tumor Epidemiology Branch; 

Senior Advisor for Genomic Epidemiology

DCEG Collaborators

• Christian Abnet, Ph.D., M.P.H – Director, Senior Investigator, Metabolic Epidemiology Branch
• Mustapha Abubakar, M.D., Ph.D. – Earl Stadtman Investigator, Intergrative Tumor Epidemiology Branch
• Jonas De Almeida, Ph.D. – Director, Data Science Senior Investigator, Trans-Divisional Research Program
• Praphulla Bhawasar, M.S.– Predoctoral Fellow, Trans-Divisional Research Program

Data Science & Engineering Research Group

• Stephen Chanock, M.D. – Director, Division of Cancer Epidemiology and Genetics
•  Jiyeon Choi, Ph.D., M.S. – Earl Stadtman Investigator Head, Laboratory of Translational Genomics
• Diptavo Dutta. Ph.D. – Earl Stadtman Investigator, Integrative Tumor Epidemiology Branch
• Grace Hong, Ph.D. – Senior Investigator, Biostatistics Branch
• Jung Kim, Ph.D. – Staff Scientist, Clinical Genetics Branch
• Qing Lan, M.D., Ph.D., M.P.H. – Senior Investigator, Occupational and Environmental Epidemiology Branch
• Ruth Pfeiffer, Ph.D. – Senior Investigator, Biostatistics Branch
• Nat Rothman, M.D., M.P.H, M.H.S. – Senior Investigator Head of Molecular Studies, Occupational and Environmental Epidemiology Branch
• Jianxin Shi, Ph.D. – Senior Investigator, Biostatistics Branch
• Emily Vogtmann, Ph.D., M.P.H – Earl Stadtman Investigator, Metabolic Epidemiology Branch
• Wendy Wong, Ph.D. – Senior Biomedical Research Scientist, Trans-Divisional Research Program
• Tongwu Zhang, Ph.D. – Earl Stadtman Investigator, Biostatistics Branch
• Bin Zhu, Ph.D. – Senior Investigator, Biostatistics Branch

Lead Project Manager

• Phuc H. Hoang, Ph.D. – Staff Scientist, Integrative Tumor Epidemiology Branch

Early-career scientists interested in training and fellowship opportunities in genomic epidemiology, molecular pathology, computational biology, and cancer prevention research can apply here.

For inquiries on opening positions, please contact phuc.hoang@nih.gov.