A m⁶A regulators-related classifier for prognosis and tumor microenvironment characterization in hepatocellular carcinoma.

ABSTRACT:

Background

Increasing evidence have highlighted the biological significance of mRNA N⁶-methyladenosine (m⁶A) modification in regulating tumorigenicity and progression. However, the potential roles of m⁶A regulators in tumor microenvironment (TME) formation and immune cell infiltration in liver hepatocellular carcinoma (LIHC or HCC) requires further clarification.

Method

RNA sequencing data were obtained from TCGA-LIHC databases and ICGC-LIRI-JP databases. Consensus clustering algorithm was used to identify m⁶A regulators cluster subtypes. Weighted gene co-expression network analysis (WGCNA), LASSO regression, Random Forest (RF), and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) were applied to identify candidate bi

SUBMITTER: Xu S 

PROVIDER: S-EPMC11306056 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature