Gene signature of m6A-related targets to predict prognosis and immunotherapy response in ovarian cancer.

ABSTRACT:

Purpose

The aim of the study was to construct a risk score model based on m6A-related targets to predict overall survival and immunotherapy response in ovarian cancer.

Methods

The gene expression profiles of 24 m6A regulators were extracted. Survival analysis screened 9 prognostic m6A regulators. Next, consensus clustering analysis was applied to identify clusters of ovarian cancer patients. Furthermore, 47 phenotype-related differentially expressed genes, strongly correlated with 9 prognostic m6A regulators, were screened and subjected to univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression. Ultimately, a nomogram was constructed which presented a strong ability to predict overall survival in ovarian cancer.

Results

CBLL1, FTO, HN

SUBMITTER: Tan W 

PROVIDER: S-EPMC11797572 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature