Review Volume 15, Issue 13 pp 6577—6619
Crosstalk between m6A and coding/non-coding RNA in cancer and detection methods of m6A modification residues
- 1 National Clinical Research Center for Infectious Diseases, Shenzhen Third People’s Hospital, The Second Hospital Affiliated with the Southern University of Science and Technology, Shenzhen, Guangdong Province, China
- 2 Department of Veterinary Pathobiology, University of Missouri, Columbia, MO 65211, USA
- 3 International Cancer Center, Shenzhen University Medical School, Shenzhen, Guangdong Province, China
Received: March 1, 2023 Accepted: June 15, 2023 Published: July 11, 2023
https://doi.org/10.18632/aging.204836How to Cite
Copyright: © 2023 Meng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
N6-methyladenosine (m6A) is one of the most common and well-known internal RNA modifications that occur on mRNAs or ncRNAs. It affects various aspects of RNA metabolism, including splicing, stability, translocation, and translation. An abundance of evidence demonstrates that m6A plays a crucial role in various pathological and biological processes, especially in tumorigenesis and tumor progression. In this article, we introduce the potential functions of m6A regulators, including “writers” that install m6A marks, “erasers” that demethylate m6A, and “readers” that determine the fate of m6A-modified targets. We have conducted a review on the molecular functions of m6A, focusing on both coding and noncoding RNAs. Additionally, we have compiled an overview of the effects noncoding RNAs have on m6A regulators and explored the dual roles of m6A in the development and advancement of cancer. Our review also includes a detailed summary of the most advanced databases for m6A, state-of-the-art experimental and sequencing detection methods, and machine learning-based computational predictors for identifying m6A sites.