Dataset Information

Integrating germline and somatic genetics to identify genes associated with lung cancer.

ABSTRACT: Genome-wide association studies (GWAS) have successfully identified many genetic variants associated with complex traits. However, GWAS experience power issues, resulting in the failure to detect certain associated variants. Additionally, GWAS are often unable to parse the biological mechanisms of driving associations. An existing gene-based association test framework, Transcriptome-Wide Association Studies (TWAS), leverages expression quantitative trait loci data to increase the power of association tests and illuminate the biological mechanisms by which genetic variants modulate complex traits. We extend the TWAS methodology to incorporate somatic information from tumors. By integrating germline and somatic data we are able to leverage information from the nuanced somatic landscape of tumors. Thus we can augment the power of TWAS-type tests to detect germline genetic variants associated with cancer phenotypes. We use somatic and germline data on lung adenocarcinomas from The Cancer Genome Atlas in conjunction with a meta-analyzed lung cancer GWAS to identify novel genes associated with lung cancer.

SUBMITTER: Pattee J

PROVIDER: S-EPMC7064390 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Integrating germline and somatic genetics to identify genes associated with lung cancer.

Pattee Jack J Zhan Xiaowei X Xiao Guanghua G Pan Wei W

Genetic epidemiology 20191210 3

Genome-wide association studies (GWAS) have successfully identified many genetic variants associated with complex traits. However, GWAS experience power issues, resulting in the failure to detect certain associated variants. Additionally, GWAS are often unable to parse the biological mechanisms of driving associations. An existing gene-based association test framework, Transcriptome-Wide Association Studies (TWAS), leverages expression quantitative trait loci data to increase the power of associ ...[more]

PMID: 31821614

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Project description:Recent advances in high-throughput genotyping and the recent surge of next generation sequencing of the cancer genomes have enabled discovery of germline mutations associated with an increased risk of developing breast cancer and acquired somatic mutations driving the disease. Emerging evidence indicates that germline mutations may interact with somatic mutations to drive carcinogenesis. However, the possible oncogenic interactions and cooperation between germline and somatic alterations in triple-negative breast cancer (TNBC) have not been characterized. The objective of this study was to investigate the possible oncogenic interactions and cooperation between genes containing germline and somatic mutations in TNBC. Our working hypothesis was that genes containing germline mutations associated with an increased risk developing breast cancer also harbor somatic mutations acquired during tumorigenesis, and that these genes are functionally related. We further hypothesized that TNBC originates from a complex interplay among and between genes containing germline and somatic mutations, and that these complex array of interacting genetic factors affect entire molecular networks and biological pathways which in turn drive the disease. We tested this hypothesis by integrating germline mutation information from genome-wide association studies (GWAS) with somatic mutation information on TNBC from The Cancer Genome Atlas (TCGA) using gene expression data from 110 patients with TNBC and 113 controls. We discovered a signature of 237 functionally related genes containing both germline and somatic mutations. We discovered molecular networks and biological pathways enriched for germline and somatic mutations. The top pathways included the hereditary breast cancer and role of BRCA1 in DNA damage response signaling pathways. In conclusion, this is the first large-scale and comprehensive analysis delineating possible oncogenic interactions and cooperation among and between genes containing germline and somatic mutations in TNBC. Genetic and somatic mutations, along with the genes discovered in this study, will require experimental functional validation in different ethnic populations. Functionally validated genetic and somatic variants will have important implications for the development of novel precision prevention strategies and discovery of prognostic markers in TNBC.

Dataset Information

Integrating germline and somatic genetics to identify genes associated with lung cancer.

Publications

Integrating germline and somatic genetics to identify genes associated with lung cancer.

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