Large-scale alternative polyadenylation (APA)-wide association studies to identify putative susceptibility genes in human common cancers.
Xingyi GuoJie PingYaohua YangXinwan SuXiao-Ou ShuWanqing WenZhishan ChenYunjing ZhangRan TaoGuochong JiaJingni HeQiuyin CaiQingrun ZhangGraham G GilesRachel PearlmanGad RennertPavel VodickaAmanda PhippsStephen B GruberGraham CaseyUlrike PetersJirong LongWeiqiang LinWei ZhengPublished in: medRxiv : the preprint server for health sciences (2023)
Alternative polyadenylation (APA) modulates mRNA processing in the 3' untranslated regions (3'UTR), which affect mRNA stability and translation efficiency. Here, we build genetic models to predict APA levels in multiple tissues using sequencing data of 1,337 samples from the Genotype-Tissue Expression, and apply these models to assess associations between genetically predicted APA levels and cancer risk with data from large genome-wide association studies of six common cancers, including breast, ovary, prostate, colorectum, lung, and pancreas among European-ancestry populations. At a Bonferroni-corrected P □<□0.05, we identify 58 risk genes, including seven in newly identified loci. Using luciferase reporter assays, we demonstrate that risk alleles of 3'UTR variants, rs324015 ( STAT6 ), rs2280503 ( DIP2B ), rs1128450 ( FBXO38 ) and rs145220637 ( LDAH ), could significantly increase post-transcriptional activities of their target genes compared to reference alleles. Further gene knockdown experiments confirm their oncogenic roles. Our study provides additional insight into the genetic susceptibility of these common cancers.
Keyphrases
- genome wide
- copy number
- dna methylation
- genome wide association
- genome wide identification
- transcription factor
- gene expression
- electronic health record
- prostate cancer
- poor prognosis
- endothelial cells
- big data
- bioinformatics analysis
- genome wide analysis
- case control
- cell proliferation
- crispr cas
- single cell
- high throughput
- genome wide association study
- induced pluripotent stem cells
- heat shock
- young adults
- benign prostatic hyperplasia
- artificial intelligence
- childhood cancer