EQTL analysis from co-localization of 2739 GWAS loci detects associated genes across 14 human cancers. (7th February 2019)

• Record Type: Journal Article
• Authors: Li, Weidong; Zhou, Qingniao; Gao, Yong; Jiang, Yonghua; Huang, Yuanjie; Mo, Zengnan; Zou, Yiming; Hu, Yanling
• Is Part Of: Journal of theoretical biology. Volume 462(2019)
• Page Start: 240
• Page End: 246
• Publication Date: 2019-02-07
• Subjects: SNPs -- Cis-regulatory genes -- Multiple cancers -- Stage levels -- Survival events; Biology -- Periodicals; Biological Science Disciplines -- Periodicals; Biology -- Periodicals; Biologie -- Périodiques; Theoretische biologie; Biology; Periodicals; 571.05
• DOI: 10.1016/j.jtbi.2018.10.059
• Languages: English
• ISSNs: 0022-5193

Abstract

Highlights: 17 SNPs were significantly associated with the expression of 18 cis-genes. MYL2 and PTGFR in HNSC, 4 genes (F8, SATB2, G6PD and UGT1A6) in KIRP, 3 genes (CHMP4C, MAP3K1 and MECP2) in LUAD were all strongly associated with cancer stage levels. SATB2 was correlated with HNSC survival, and MPP1was strongly associated with the survival of SARC. Abstract: Genetic variants can predict other "linked" diseases because alterations in one or more genes in vivo may affect relevant phenotype properties. Our study systematically explored the pan-cancer common gene and cancer type-specific genes based on GWAS loci and TCGA data of multiple cancers. It was found that there were 17 SNPs were significantly associated with the expression of 18 genes. Associations between the 18 cis-regulatory genes and the pathologic stage of each cancer showed that MYL2 and PTGFR in HNSC, 4 genes (F8, SATB2, G6PD and UGT1A6) in KIRP, 3 genes (CHMP4C, MAP3K1 and MECP2) in LUAD were all strongly associated with cancer stage levels. Additionally, the survival association analysis showed that SATB2 was correlated with HNSC survival, and MPP1 was strongly associated with the survival of SARC. This study will shed light on the biological pathways involved in cancer-genetic associations, and has the potential to be applied to the predictions of the risk of cancers developing in healthy individuals.