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

机译:肿瘤发生相关基因之间的遗传相互作用分析揭示了肺癌发展中的新基因和新网络

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摘要

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.
机译:癌症的发展是由许多与肿瘤发生有关的基因改变的积累所驱动的,而肿瘤的发生则是由所涉及基因的复杂网络而不是独立的作用所触发的。为了探讨肺癌发生中与肿瘤发生相关的基因之间的上位性,我们对来自2027个肿瘤发生相关基因的35,031个SNP之间进行了成对遗传相互作用分析。在这项研究中,对来自三项独立的全基因组关联研究的基因型进行了分析,包括总共24,037名肺癌患者和20,401名具有白种人血统的健康对照。使用包括发现和复制研究以及严格的Bonferroni校正的两阶段研究设计进行多重统计分析,我们确定了RGL1:RAD51B中SNP之间的显着遗传相互作用(OR = 0.44,p值= 3.27x10 -11 ,OR = 0.41,非小细胞肺癌中p值= 9.71x10 -11 ),SYNE1:RNF43(OR = 0.73,p值= 1.01x10 在腺癌中为-12 )和FHIT:TSPAN8(鳞状细胞癌为OR = 1.82,p值= 7.62x10 -11 )。从先前的肺癌主要效应关联研究中未鉴定出这些基因。肺组织中进一步的eQTL基因表达分析提供了支持已确定的上位性在肺肿瘤发生中的功能作用的信息。基因集富集分析揭示了整个肺癌以及组织学亚型发展中潜在分子机制的潜在途径和基因网络。我们的结果提供了证据,证明与肿瘤发生相关的基因之间的遗传相互作用在肺肿瘤发生和上位性分析中起着重要作用,并结合功能注释,为揭示功能性易感性新基因提供了有价值的工具,这些新易感性基因通过与其他修饰基因相互作用而有助于肺癌的发展。

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