科研之友
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摘要
Recent technological advancements have permitted high-throughput measurement of the human genome, epigenome, metabolome, transcriptome, and proteome at the population level. We hypothesized that subsets of genes identified from omic studies might have closely related biological functions and thus might interact directly at the network level. Therefore, we conducted an integrative analysis of multi-omic datasets of nonsmall cell lung cancer (NSCLC) to search for association patterns beyond the genome and transcriptome. A large, complex, and robust gene network containing well-known lung cancer-related genes, including EGFR and TERT, was identified from combined gene lists for lung adenocarcinoma. Members of the hypoxia-inducible factor (HIF) gene familywere at the center of this network. Subsequent sequencing of network hub geneswithin a subset of samples fromthe Transdisciplinary Research in Cancer of the Lung-International Lung Cancer Consortium (TRICL-ILCCO) consortium revealed a SNP (rs12614710) in EPAS1 associated with NSCLC that reached genome-wide significance (OR = 1.50; 95% CI: 1.31-1.72; p = 7.75 x 10(-9)). Using imputed data, we found that this SNP remained significant in the entire TRICL-ILCCO consortium (p =.03). Additional functional studies are warranted to better understand interrelationships among genetic polymorphisms, DNA methylation status, and EPAS1 expression.
