Drug-induced liver injury (DILI) is a leading cause of acute liver failure. Reliable and translational biomarkers are needed for early detection of DILI. microRNAs (miRNAs) have received wide attention as a novel class of potential DILI biomarkers. However, it is unclear how DILI drugs other than acetaminophen may influence miRNA expression or which miRNAs could serve as useful biomarkers in humans. We selected ketoconazole (KCZ), a classic hepatotoxin, to study miRNA biomarkers for DILI as a proof of concept for a workflow that integrated in vivo, in vitro, and bioinformatics analyses. We examined hepatic miRNA expression in KCZ-treated rats at multiple doses and durations using miRNA-sequencing and correlated our results with conventional DILI biomarkers such as liver histology. Significant dysregulation of rno-miR-34a-5p, rno-miR-331-3p, rno-miR-15b-3p, and rno-miR-676 was associated with cytoplasmic vacuolization, a phenotype in rat livers with KCZ-induced injury, which preceded the elevation of serum liver transaminases (ALT and AST). Between rats and humans, miR-34a-5p, miR-331-3p, and miR-15b-3p were evolutionarily conserved with identical sequences, whereas miR-676 showed 73% sequence similarity. Using quantitative PCR, we found that the levels of hsa-miR-34a-5p, hsa-miR-331-3p, and hsa-miR-15b-3p were significantly elevated in the culture media of HepaRG cells treated with 100âµM KCZ (a concentration that induced cytotoxicity). Additionally, we computationally characterized the miRNA candidates for their gene targeting, target functions, and miRNA/target evolutionary conservation. In conclusion, we identified miR-34a-5p, miR-331-3p, and miR-15b-3p as translational biomarker candidates for early detection of KCZ-induced liver injury with a workflow applicable to computational toxicology studies.
Identification of Translational microRNA Biomarker Candidates for Ketoconazole-Induced Liver Injury Using Next-Generation Sequencing.
阅读:14
作者:Li Dongying, Knox Bridgett, Gong Binsheng, Chen Si, Guo Lei, Liu Zhichao, Tong Weida, Ning Baitang
| 期刊: | Toxicological Sciences | 影响因子: | 4.100 |
| 时间: | 2021 | 起止号: | 2021 Jan 6; 179(1):31-43 |
| doi: | 10.1093/toxsci/kfaa162 | ||
特别声明
1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。
2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。
3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。
4、投稿及合作请联系:info@biocloudy.com。
