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Xiangjun Xiao



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    MA10 - Emerging Technologies for Lung Cancer Detection (ID 129)

    • Event: WCLC 2019
    • Type: Mini Oral Session
    • Track: Screening and Early Detection
    • Presentations: 1
    • Now Available
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      MA10.07 - Integrative Analysis of Epistasis Involving Oncogenesis-Related Genes in Lung Cancer Risk Development (Now Available) (ID 2502)

      15:15 - 16:45  |  Author(s): Xiangjun Xiao

      • Abstract
      • Presentation
      • Slides

      Background

      Our previous study identified significant genetic interactions within oncogenesis-related genes in lung cancer risk development. More genetic interactions may exist between oncogenesis-related genes and outside regions in the genome. A functional annotation and pathway analysis of the identified epistasis-related genes will advance our understanding about the complicated biological mechanisms underlying lung tumorigenesis.

      Method

      The genotypes from two independent lung cancer GWAS studies including a total of 23,351 lung cancer patients and 19,657 health controls with European ancestry were collected for the analysis. Pairwise epistasis was conducted between 27,722 SNPs, from 2,027 oncogenesis-related genes, and 317,624 SNPs from the rest of the genome. A two-stage study design including discovery and replication studies, and stringent Bonferroni correction for multiple statistical analysis were applied in the analysis, Additional genotyping and gene expression data from 409 independent individuals with Caucasian ancestry were used to evaluate the effect of identified epistasis on gene expression levels. The epistasis-involved genes, were submitted to DAVID, Reactome, and GeneMANIA for gene functional annotation and pathway analysis.

      Result

      Significant genetic interactions were identified between SNPs in gene pairs ATR-GALNT18 (Interaction OR=0.76, p value=7.98x10-13) and MET-DPF3 (Interaction OR=0.76, p value=1.62x10-12) in lung adenocarcinoma; and PICALM-PDZRN4 (Interaction OR=1.47, p value=1.67x10-12) in lung squamous carcinoma. None of these genes have been identified from previous main effect association studies in lung cancer. Further eQTL gene expression analysis revealed the significant association in expression levels between joint genotypes at rs637304:rs285581 and the PICALM gene expression (p=0.009). A total of 12 unique genes, from six significant interactions, including those from within oncogenesis-related genes and between oncogenesis-related genes and outside variants, were submitted to functional annotation and pathway analysis. Three of them (ATR, MET and FHIT) are shown to be related with lung cancer, and six of them (RAD51B, FHIT, CALNT18, RGL1, SYNE1 and TSPAN8) are involved in tobacco-use disorders. The top 10 pathways include TP53 regulates transcription of DNA repair genes (FDR=1.67x10-2), homologous DNA pairing and strand exchange (FDR=2.57x10-2), and Meiotic synapsis (3.08x10-2), etc. GeneMANIA predicted one gene network harboring all the 12 candidate genes, supporting the epistasis at 3 genes pairs and indirect interactions at 3 gene pairs.

      Conclusion

      We identified novel genes involved in lung cancer risk development by interacting with other genetic variants. The study provides evidence that epistasis explains part of the missing heritability in lung cancer; and complex gene network and pathways contribute to lung carcinogenesis.

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