Seven m6A-related genes linked to cuproptosis predict colorectal cancer survival

Researchers have identified seven genes tied to N6-methyladenosine (m6A) RNA methylation that are also correlated with cuproptosis-related genes in colorectal cancer, and used them to build a prognostic model for the disease. The study, published in Medical Oncology, combined public datasets, machine learning and laboratory validation to pinpoint MMP1, TIMP1, SNAI1, CDC25C, XRN2, COX5A and FBXL5 as prognostic genes in colorectal cancer.

The team set out to uncover m6A RNA methylation-related prognostic genes correlated with cuproptosis-related genes in colorectal cancer and to develop an effective prognostic model from them. Using publicly available datasets, the researchers performed differential expression analysis, correlation analysis and machine learning to identify candidate genes, then constructed and validated a prognostic signature.

Survival analysis revealed a notable contrast in survival outcomes between patients classified into high- and low-risk groups by the seven-gene model. To make the model usable alongside clinical information, the researchers also identified independent predictive markers by combining clinical characteristics with the risk score, and used them to establish a prognostic nomogram. This nomogram, built on age, stage, T stage and risk scores, demonstrated good predictive ability.

The bioinformatics findings were checked experimentally. Reverse transcription-quantitative PCR (RT-qPCR) on colorectal cancer and normal samples showed that MMP1, TIMP1, SNAI1 and CDC25C were upregulated in tumour samples, while COX5A was downregulated, consistent with the bioinformatics analysis results.

Beyond prognosis, the study explored therapeutic leads. Based on the prognostic genes, potential drugs for colorectal cancer were predicted using artificial intelligence drug design (AIDD) and computer-aided drug design (CADD). This computational screen identified 186 candidate drugs targeting COX5A, 153 of which showed better predicted binding affinity than the positive-control ligand 3,5-diiodo-L-thyronine. These are computational predictions of binding, not experimentally confirmed drug effects, and would require further validation.

The authors state that their analysis sets the groundwork for a more comprehensive comprehension of the fundamental molecular pathways involved in colorectal cancer. As an analysis based on public datasets with RT-qPCR validation, the model's clinical utility will need to be confirmed in independent patient populations before any practical use.

Subject of Research: Identification of m6A RNA methylation-related prognostic genes associated with cuproptosis in colorectal cancer

Article Title: Transcriptomics analysis and experimental assay to screen prognostic genes of N6-methyladenosine RNA methylation related to cuproptosis in colorectal cancer

Article References: Sun, D., Liu, Z., Chen, M., He, Y., Zeng, X., Li, D., & Wang, W. (2026). Transcriptomics analysis and experimental assay to screen prognostic genes of N6-methyladenosine RNA methylation related to cuproptosis in colorectal cancer. Medical Oncology, 43(11), Article 334. https://doi.org/10.1007/s12032-026-03441-0

Image Credits: AI Generated

DOI: 10.1007/s12032-026-03441-0

Keywords: colorectal cancer, m6A RNA methylation, cuproptosis, prognostic model, RT-qPCR, nomogram, drug design, COX5A, bioinformatics, biomarkers, Transcriptomics, analysis