Genetic interaction analysis among oncogenesis-related genes revealed novel genes and networks in lung cancer development

Yafang Li, Xiangjun Xiao, Yohan Bossé, Olga Gorlova, Ivan Gorlov, Younghun Han, Jinyoung Byun, Natasha Leighl, Jakob S. Johansen, Matt Barnett, Chu Chen, Gary Goodman, Angela Cox, Fiona Taylor, Penella Woll, H. Erich Wichmann, Judith Manz, Thomas Muley, Angela Risch, Albert RosenbergerJiali Han, Katherine Siminovitch, Susanne M. Arnold, Eric B. Haura, Ciprian Bolca, Ivana Holcatova, Vladimir Janout, Milica Kontic, Jolanta Lissowska, Anush Mukeria, Simona Ognjanovic, Tadeusz M. Orlowski, Ghislaine Scelo, Beata Swiatkowska, David Zaridze, Per Bakke, Vidar Skaug, Shanbeh Zienolddiny, Eric J. Duell, Lesley M. Butler, Richard Houlston, María Soler Artigas, Kjell Grankvist, Mikael Johansson, Frances A. Shepherd, Michael W. Marcus, Hans Brunnström, Jonas Manjer, Pier Alberto Bertazzi, Angela C. Pesatori, David C. Christiani

Research output: Contribution to journalArticle

Abstract

The development of cancer is driven by the accumulation of many oncogenesis-related genetic alterations and tumorigenesis is triggered by complex networks of involved genes rather than independent actions. To explore the epistasis existing among oncogenesis-related genes in lung cancer development, we conducted pairwise genetic interaction analyses among 35,031 SNPs from 2027 oncogenesis-related genes. The genotypes from three independent genome-wide association studies including a total of 24,037 lung cancer patients and 20,401 healthy controls with Caucasian ancestry were analyzed in the study. Using a two-stage study design including discovery and replication studies, and stringent Bonferroni correction for multiple statistical analysis, we identified significant genetic interactions between SNPs in RGL1:RAD51B (OR=0.44, p value=3.27x10 -11 in overall lung cancer and OR=0.41, p value=9.71x10 -11 in non-small cell lung cancer), SYNE1:RNF43 (OR=0.73, p value=1.01x10 -12 in adenocarcinoma) and FHIT:TSPAN8 (OR=1.82, p value=7.62x10 -11 in squamous cell carcinoma) in our analysis. None of these genes have been identified from previous main effect association studies in lung cancer. Further eQTL gene expression analysis in lung tissues provided information supporting the functional role of the identified epistasis in lung tumorigenesis. Gene set enrichment analysis revealed potential pathways and gene networks underlying molecular mechanisms in overall lung cancer as well as histology subtypes development. Our results provide evidence that genetic interactions between oncogenesis-related genes play an important role in lung tumorigenesis and epistasis analysis, combined with functional annotation, provides a valuable tool for uncovering functional novel susceptibility genes that contribute to lung cancer development by interacting with other modifier genes.

Original languageEnglish
Pages (from-to)1760-1774
Number of pages15
JournalOncotarget
Volume10
Issue number19
Publication statusPublished - Mar 1 2019

Keywords

  • Epistasis
  • Functional annotation
  • Lung cancer
  • Oncogenesis

ASJC Scopus subject areas

  • Oncology

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  • Cite this

    Li, Y., Xiao, X., Bossé, Y., Gorlova, O., Gorlov, I., Han, Y., Byun, J., Leighl, N., Johansen, J. S., Barnett, M., Chen, C., Goodman, G., Cox, A., Taylor, F., Woll, P., Erich Wichmann, H., Manz, J., Muley, T., Risch, A., ... Christiani, D. C. (2019). Genetic interaction analysis among oncogenesis-related genes revealed novel genes and networks in lung cancer development. Oncotarget, 10(19), 1760-1774.