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. 2023 May 16;16(1):105.
doi: 10.1186/s12920-023-01509-8.

Comprehensive analysis of m6A related gene mutation characteristics and prognosis in colorectal cancer

Tao Jiang #  1 , Linshuai Xing #  2 , Lipeng Zhao  2 , Ziqi Ye  2 , Dong Yu  1 , Shengtao Lin  3   4
Affiliations

Comprehensive analysis of m6A related gene mutation characteristics and prognosis in colorectal cancer

Tao Jiang et al. BMC Med Genomics. .

Abstract

Background: Colorectal cancer is considered as the second most common cancer worldwide. Studies have shown that m6A RNA methylation abnormalities play an important role in the pathogenesis of many human diseases, including cancer. The current study was designed to characterize the mutation of m6A related genes and explore their prognostic role in colorectal cancer.

Methods: RNA-seq data and somatic mutation data of TCGA-COAD and TCGA-READ were downloaded from UCSC xena for comprehensive analysis. M6A related genes were selected from previous literatures, including "Writer" protein (METTL3, METTL5, METTL14, METTL16, ZC3H13, RBM15, WTAP, KIAA1429), "Reader" protein YTHDF1, YTHDF2, YTHDF3, YTHDC1, YTHDC2, HNRNPC, IGF2BP1, IGF2BP2, IGF2BP3), and "Eraser" protein (FTO, ALKBH5). Kaplan-Meier diagrams were used to explore the correlation between m6A-related genes and colorectal cancer prognosis. The correlations between m6A-related genes and clinical parameters and immune-related indicators were explored by Spearman correlation analysis. And finally, the expression patterns of five key genes (RBMX, FMR1, IGF2BP1, LRPPRC and YTHDC2) were detected by qPCR in CRC specimens.

Results: In CRC, the expressions of m6A-related genes were significantly different between CRC and normal control except METTL14, YTHDF2, YTHDF3. Some of CRC patients (178 in 536) have a m6A-related genes mutation. ZC3H13 has highest mutation frequency of all m6A-related genes. M6A-related genes mainly enrich in regulation of mRNA metabolic process pathway. Patients with high expressions of FMR1, LRPPRC, METTL14, RBMX, YTHDC2, YTHDF2, YTHDF3 have poor prognosis in CRC. There was a significant correlation between the FMR1, LRPPRC, RBMX, YTHDC2, IGF2BP1 expression and the clinical characteristics of CRC. In addition, these genes are significantly associated with immune-related indicators. According to the expression patterns of FMR1, LRPPRC, RBMX, YTHDC2, and IGF2BP1, patients with CRC were clustered into two groups, and their survival was significantly different. By evaluating the tumor microenvironment in two clusters using ssGSEA, expressions of immune checkpoints and GSVA enrichment analysis, we observed that the immune and stem cell index of two cluster were much different. The qPCR results showed that RBMX expression was markedly elevated in cancerous tissues than in the normal colonic tissues.

Conclusion: Our study identified novel prognostic markers associated with immune of CRC cancer patients. Moreover, the potential mechanisms of prognostic markers in regulating the etiology of CRC cancer were investigated. These findings enrich our understanding of the relationships between m6a related genes and CRC, and may provide novel ideas in the therapy of CRC patients.

Keywords: Colorectal cancer; Immune; Prognosis; m6A.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Differential expression patterns and mutation analysis of m6A regulators in CRC. A All m6A related genes expression were significantly different between tumor and control group except METTL14, YTHDF2 and YTHDF3. B 33.21%CRC patients contained mutated m6A related genes. C > T and T > G are the two main mutation types. The rainfall map shows high mutation genomic regions according to different SNP mutation types
Fig. 2
Fig. 2
Go and KEGG enrichment analysis of m6a regulators in CRC. A Bar chart, B Bubble chart: mRNA metabolism process and spliceosome pathway enriched in GO and KEGG pathway
Fig. 3
Fig. 3
Survival analysis of m6A regulators in CRC. A Results of m6A regulators related with CRC prognosis were identified by Kaplan Meier analysis. B The correlation between expression of RBMX and clinical parameters, including stage, T, N, M in CRC
Fig. 4
Fig. 4
Correlation between m6A gene expression and immune infiltration, and clustering analysis in CRC. A FMR1, LRPPRC, RBMX, YTHDC2, HNRNPC and IGF2BP1 expression levels correlated with immune infiltration identified by CIBERSORTx database. B Results of significant differences of Kaplan–Meier curve between cluster A and Cluster B identified by R software package of ConsensusClusterPlus
Fig. 5
Fig. 5
GSVA analysis between two different clusters. Results of GSVA analysis indicated that hypertrophic_cardiomyopathy_hcm and fatty_acid_metabolism were the most significant differences between the two clusters
Fig. 6
Fig. 6
Analysis of immune infiltration between two different clusters. A Results of immune cell infiltration between the two clusters identified by ssGSEA. B Results of Immunescore, Stromalscore and Estimatescore between the two clusters by using estimate package. C CD44, CD40LG, CD276 and TNFSF18 were significantly difference between the two clusters identified by immune checkpoint analysis
Fig. 7
Fig. 7
GSEA analysis between different clusters and validation of five potential biomarker for prognosis in CRC. A Results of enrichment pathways between the two clusters identified by GSEA analysis. B The expression patterns of RBMX, FMR1, IGF2BP1, LRPPRC and YTHDC2 were detected. RBMX expression was markedly elevated in cancerous tissues than in the normal colonic tissues
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