{"title":"Competing endogenous RNAs (ceRNAs) and drug resistance to cancer therapy.","authors":"Kenneth K W To, Hang Zhang, William C Cho","doi":"10.20517/cdr.2024.66","DOIUrl":null,"url":null,"abstract":"<p><p>Competing endogenous RNAs (ceRNAs) are transcripts that possess highly similar microRNA response elements (MREs). microRNAs (miRNAs) are short, endogenous, single-stranded non-coding RNAs (ncRNAs) that can repress gene expression by binding to MREs on the 3' untranslated regions (UTRs) of the target mRNA transcripts to suppress gene expression by promoting mRNA degradation and/or inhibiting protein translation. mRNA transcripts, circular RNAs (circRNAs), long non-coding RNAs (lncRNAs), and transcribed pseudogenes could share similar MREs, and they can compete for the same pool of miRNAs. These ceRNAs may affect the level of one another by competing for their shared miRNAs. This interplay between different RNAs constitutes a ceRNA network, which regulates many important biological processes. Cancer drug resistance is a major factor leading to treatment failure in patients receiving chemotherapy. It can be acquired through genetic, epigenetic, and various tumor microenvironment mechanisms. The involvement of ceRNA crosstalk and its disruption in chemotherapy resistance is attracting attention in the cancer research community. This review presents an updated summary of the latest research on ceRNA dysregulation causing drug resistance across different cancer types and chemotherapeutic drug classes. Interestingly, accumulating evidence suggests that ceRNAs may be used as prognostic biomarkers to predict clinical response to cancer chemotherapy. Nevertheless, detailed experimental investigations of the putative ceRNA networks generated by computational algorithms are needed to support their translation for therapeutic and prognostic applications.</p>","PeriodicalId":70759,"journal":{"name":"癌症耐药(英文)","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11472581/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"癌症耐药(英文)","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.20517/cdr.2024.66","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Competing endogenous RNAs (ceRNAs) are transcripts that possess highly similar microRNA response elements (MREs). microRNAs (miRNAs) are short, endogenous, single-stranded non-coding RNAs (ncRNAs) that can repress gene expression by binding to MREs on the 3' untranslated regions (UTRs) of the target mRNA transcripts to suppress gene expression by promoting mRNA degradation and/or inhibiting protein translation. mRNA transcripts, circular RNAs (circRNAs), long non-coding RNAs (lncRNAs), and transcribed pseudogenes could share similar MREs, and they can compete for the same pool of miRNAs. These ceRNAs may affect the level of one another by competing for their shared miRNAs. This interplay between different RNAs constitutes a ceRNA network, which regulates many important biological processes. Cancer drug resistance is a major factor leading to treatment failure in patients receiving chemotherapy. It can be acquired through genetic, epigenetic, and various tumor microenvironment mechanisms. The involvement of ceRNA crosstalk and its disruption in chemotherapy resistance is attracting attention in the cancer research community. This review presents an updated summary of the latest research on ceRNA dysregulation causing drug resistance across different cancer types and chemotherapeutic drug classes. Interestingly, accumulating evidence suggests that ceRNAs may be used as prognostic biomarkers to predict clinical response to cancer chemotherapy. Nevertheless, detailed experimental investigations of the putative ceRNA networks generated by computational algorithms are needed to support their translation for therapeutic and prognostic applications.