Prognostic signature and immune efficacy of m1A-, m5C- and m6A-related regulators in cutaneous melanoma

Cutaneous melanoma (CM) is an aggressive cancer; given that initial and specific signs are lacking, diagnosis is often late and the prognosis is poor. RNA modification has been widely studied in tumour progression. Nevertheless, little progress has been made in the signature of N-1-methyladenosine (m(1)A), 5-methylcytosine (m(5)C), N-6-methyladenosine (m(6)A)-related regulators and the tumour microenvironment (TME) cell infiltration in CM. Our study identified the characteristics of m(1)A-, m(5)C- and m(6)A-related regulators based on 468 CM samples from the public database. Using univariate, multivariate and LASSO Cox regression analysis, a risk model of regulators was established and validated by a nomogram on independent prognostic factors. The gene set variation analysis (GSVA) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) clarified the involved functional pathways. A combined single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT approach revealed TME of regulator-related prognostic signature. The nine-gene signature stratified the patients into distinct risk subgroups for personalized prognostic assessment. Additionally, functional enrichment, immune infiltration and immunotherapy response analysis indicated that the high-risk group was correlated with T-cell suppression, while the low-risk group was more sensitive to immunotherapy. The findings presented here contribute to our understanding of the TME molecular heterogeneity in CM. Nine m(1)A-, m(5)C- and m(6)A-related regulators may also be promising biomarkers for future research.

Automated summary

The study on Cutaneous Melanoma (CM) identified specific RNA regulators and their impact on tumor progression, leading to the development of a prognostic risk model and functional pathway analysis. The findings also highlighted the correlation between immune infiltration and immunotherapy response in different risk subgroups of CM patients, contributing to the understanding of molecular heterogeneity in the tumor microenvironment.