EBioMedicine (Jun 2018)

Multi-Omics Analysis Reveals a HIF Network and Hub Gene EPAS1 Associated with Lung Adenocarcinoma

  • Zhaoxi Wang,
  • Yongyue Wei,
  • Ruyang Zhang,
  • Li Su,
  • Stephanie M. Gogarten,
  • Geoffrey Liu,
  • Paul Brennan,
  • John K. Field,
  • James D. McKay,
  • Jolanta Lissowska,
  • Beata Swiatkowska,
  • Vladimir Janout,
  • Ciprian Bolca,
  • Milica Kontic,
  • Ghislaine Scelo,
  • David Zaridze,
  • Cathy C. Laurie,
  • Kimberly F. Doheny,
  • Elizabeth K. Pugh,
  • Beth A. Marosy,
  • Kurt N. Hetrick,
  • Xiangjun Xiao,
  • Claudio Pikielny,
  • Rayjean J. Hung,
  • Christopher I. Amos,
  • Xihong Lin,
  • David C. Christiani

Journal volume & issue
Vol. 32
pp. 93 – 101

Abstract

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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 non-small 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 family were at the center of this network. Subsequent sequencing of network hub genes within a subset of samples from the 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 × 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. Keywords: Non-small cell lung cancer, Lung adenocarcinoma, Integrated analysis, Network analysis, Hypoxia-inducible factor