Functional studies of lung cancer GWAS beyond association

Author:

Long Erping1,Patel Harsh1,Byun Jinyoung234,Amos Christopher I2345,Choi Jiyeon1ORCID

Affiliation:

1. Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health , Bethesda, MD, 20892 , USA

2. Institute for Clinical and Translational Research, Baylor College of Medicine , Houston, TX, 77030 , USA

3. Section of Epidemiology and Population Sciences , Department of Medicine, , Houston, TX, 77030 , USA

4. Baylor College of Medicine , Department of Medicine, , Houston, TX, 77030 , USA

5. Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine , Houston, TX, 77030 , USA

Abstract

Abstract Fourteen years after the first genome-wide association study (GWAS) of lung cancer was published, approximately 45 genomic loci have now been significantly associated with lung cancer risk. While functional characterization was performed for several of these loci, a comprehensive summary of the current molecular understanding of lung cancer risk has been lacking. Further, many novel computational and experimental tools now became available to accelerate the functional assessment of disease-associated variants, moving beyond locus-by-locus approaches. In this review, we first highlight the heterogeneity of lung cancer GWAS findings across histological subtypes, ancestries and smoking status, which poses unique challenges to follow-up studies. We then summarize the published lung cancer post-GWAS studies for each risk-associated locus to assess the current understanding of biological mechanisms beyond the initial statistical association. We further summarize strategies for GWAS functional follow-up studies considering cutting-edge functional genomics tools and providing a catalog of available resources relevant to lung cancer. Overall, we aim to highlight the importance of integrating computational and experimental approaches to draw biological insights from the lung cancer GWAS results beyond association.

Funder

National Institutes of Health

Integrative Analysis of Lung Cancer Etiology and Risk

Sequencing Familial Lung Cancer

Genetic Analysis of Lung Cancer Etiology and Risk

Cancer Prevention Research Interest of Texas

Publisher

Oxford University Press (OUP)

Subject

Genetics (clinical),Genetics,Molecular Biology,General Medicine

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