Decoding The Epitranscriptome: In Silico Insights Into m6A Regulatory Network In Breast Cancer

Summary

This protocol presents an approach for conducting in silico genetic, molecular, and prognostic analyses of m6A modification regulators by integrating mutation profiles, copy number alterations, gene expression, and clinical outcomes using publicly available datasets from the Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) project, and microarray platforms.

Abstract

N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic transcripts and plays a critical role in RNA metabolism, gene expression, and cellular homeostasis. Dysregulation of m6A regulators, including “writers,” “erasers,” and “readers”, has been increasingly implicated in cancer biology; however, their comprehensive roles in breast cancer remain to be understood. The primary objective of this methods article is to provide bioinformatics beginners with a step-by-step framework for utilizing publicly available cancer datasets to perform mutational analyses, assess gene expression alterations, and examine their associations with patient survival. As a case study, m6A regulators in breast cancer were analyzed using datasets from the Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) project, and microarray platforms. Transcriptomic profiles were systematically analyzed to demonstrate workflows for evaluating the prognostic relevance of m6A regulatory components in breast cancer. Using this analytical framework, distinct patterns of genetic alterations and differential expression among key m6A regulators were identified. Several regulators, including METTL14, CBLL1, YTHDC1, HNRNPC, HNRNPA2B1, and RBMX, were associated with better patient survival, while YWHAG was associated with poor overall survival. This study provides a comprehensive systems genomics overview of m6A regulatory genes in breast cancer while demonstrating a practical and reproducible web-based bioinformatics workflow. These findings advance the understanding of epitranscriptomic regulation in breast cancer and offer a foundation for the development of novel m6A-based diagnostic and therapeutic strategies.

Introduction

Epitranscriptomic modifications represent an important layer of post-transcriptional gene regulation and contribute to diverse cellular processes and disease states. Among more than 170 RNA modifications identified to date, N6-methyladenosine (m6A) is the most prevalent and well-characterized in eukaryotic mRNAs¹. Installed by “writer” complexes including METTL3/METTL14, removed by “erasers” including FTO and ALKBH5, and interpreted by “reader” proteins including YTH and IGF2BP family members, m6A orchestrates RNA splicing, stability, transport, and translation, thereby influencing key biological processes in....

Protocol

NOTE: The list of genes encoding m6A methylation regulators, categorized as writers, readers, and erasers, is presented in Table 1. All listed genes were included in the subsequent analyses of mutations, expression patterns, and overall survival. All software and tools used in this study are listed in the Table of Materials.

1. Identification of genetic alterations in m6A regulators

1. Access the cBioPortal for cancer genomics. Navigate to the cBioportal website (www.cbioportal.org)^27,28. From the homepage, select the ̶....

Results

Mutational landscape of m6a methylation regulators in breast cancer

In an earlier study on the genomic analysis of TCGA datasets, recurrent mutations in several genes encoding regulators of DNA methylation were reported³¹. In the present study, cBioPortal was utilized to analyze the “Breast Invasive Carcinoma (TCGA, PanCancer Atlas)” dataset in order to examine mutational profiles of genes encoding the writers, readers, and erasers of m6A RNA methylatio.......

Discussion

This Method's article provides a comprehensive, accessible, and integrated workflow for the systematic multi-omics profiling and clinical translation of any gene signature in cancer research, demonstrated here through the analysis of m6A RNA methylation regulators in breast cancer. By combining these major public bioinformatics platforms, this approach enables researchers to efficiently progress from genomic discovery to clinically relevant hypotheses without requiring advanced computational expertise.

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
cBioPortal	Memorial Sloan-Kettering Cancer Center	https://www.cbioportal.org
Genotype-Tissue Expression (GTEx)	GTEx Consortium	https://gtexportal.org
Kaplan-Meier Plotter	Gyorffy lab/A5 Genetics Ltd	https://kmplot.com
The Cancer Genome Atlas (TCGA)	National Cancer Institute (NCI)	https://www.cancer.gov/tcga
UCSC Xena Browser	University of California Santa Cruz	https://xenabrowser.net