A large-scale microRNA transcriptome-wide association study identifies two susceptibility microRNAs, miR-1307-5p and miR-192-3p, for colorectal cancer risk.
Zhishan ChenWeiqiang LinQiuyin CaiSun-Seog KweonXiao-Ou ShuChizu TanikawaWei-Hua JiaYing WangXinwan SuYuan YuanWanqing WenJeong-Seon KimAesun ShinSun Ha JeeKeitaro MatsuoDong-Hyun KimNan WangJie PingMin-Ho ShinZefang RenJae Hwan OhIsao OzeYoon-Ok AhnKeum Ji JungYu-Tang GaoZhi-Zhong PanYoichiro KamataniWeidong HanJirong LongKoichi MatsudaWei ZhengXingyi GuoPublished in: Human molecular genetics (2023)
Transcriptome-wide association studies (TWAS) have identified many putative susceptibility genes for colorectal cancer (CRC) risk. However, susceptibility miRNAs, critical dysregulators of gene expression, remain unexplored. We genotyped DNA samples from 313 CRC East Asian patients and performed small RNA sequencing in their normal colon tissues distant from tumors to build genetic models for predicting miRNA expression. We applied these models and data from genome-wide association studies (GWAS) including 23 942 cases and 217 267 controls of East Asian ancestry to investigate associations of predicted miRNA expression with CRC risk. Perturbation experiments separately by promoting and inhibiting miRNAs expressions and further in vitro assays in both SW480 and HCT116 cells were conducted. At a Bonferroni-corrected threshold of P < 4.5 × 10-4, we identified two putative susceptibility miRNAs, miR-1307-5p and miR-192-3p, located in regions more than 500 kb away from any GWAS-identified risk variants in CRC. We observed that a high predicted expression of miR-1307-5p was associated with increased CRC risk, while a low predicted expression of miR-192-3p was associated with increased CRC risk. Our experimental results further provide strong evidence of their susceptible roles by showing that miR-1307-5p and miR-192-3p play a regulatory role, respectively, in promoting and inhibiting CRC cell proliferation, migration, and invasion, which was consistently observed in both SW480 and HCT116 cells. Our study provides additional insights into the biological mechanisms underlying CRC development.
Keyphrases
- gene expression
- poor prognosis
- cell proliferation
- genome wide
- single cell
- binding protein
- cell cycle arrest
- oxidative stress
- end stage renal disease
- chronic kidney disease
- machine learning
- ejection fraction
- high throughput
- artificial intelligence
- deep learning
- peritoneal dialysis
- prognostic factors
- genome wide association