Open AccessPrognostic signature and immune efficacy of m 1 A‐, m 5 C‐ and m 6 A‐related regulators in cutaneous melanoma
Author(s) -
Wu Xian rui,
Chen Zheng,
Liu Yang,
Chen Zi zi,
Tang Fengjie,
Chen Zhi zhao,
Li Jing jing,
Liao Jun lin,
Cao Ke,
Chen Xiang,
Zhou Jianda
Publication year - 2021
Publication title -
journal of cellular and molecular medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.44
H-Index - 130
eISSN - 1582-4934
pISSN - 1582-1838
DOI - 10.1111/jcmm.16800
Subject(s) - gene signature , kegg , immunotherapy , melanoma , nomogram , biology , immune system , proportional hazards model , tumor microenvironment , oncology , computational biology , cancer research , gene , medicine , immunology , transcriptome , gene expression , genetics
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.