M5C-Related Signatures for Predicting Prognosis in Cutaneous Melanoma with Machine Learning.

ABSTRACT:

Background

Cutaneous melanoma (CM) is one of the most life-threatening primary skin cancers and is prone to distant metastases. A widespread presence of posttranscriptional modification of RNA, 5-methylcytosine (m5C), has been observed in human cancers. However, the potential mechanism of the tumorigenesis and prognosis in CM by dysregulated m5C-related regulators is obscure.

Methods

We use comprehensive bioinformatics analyses to explore the expression of m5C regulators in CM, the prognostic implications of the m5C regulators, the frequency of the copy number variant (CNV), and somatic mutations in m5C regulators. Additionally, the CM patients were divided into three clusters for better predicting clinical features and outcomes via consensus clustering of m5C regulators. Th

SUBMITTER: Huang M 

PROVIDER: S-EPMC8360728 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature