A novel defined programmed cell death related gene signature for predicting the prognosis of serous ovarian cancer.

ABSTRACT:

Purpose

This study aims to explore the contribution of differentially expressed programmed cell death genes (DEPCDGs) to the heterogeneity of serous ovarian cancer (SOC) through single-cell RNA sequencing (scRNA-seq) and assess their potential as predictors for clinical prognosis.

Methods

SOC scRNA-seq data were extracted from the Gene Expression Omnibus database, and the principal component analysis was used for cell clustering. Bulk RNA-seq data were employed to analyze SOC-associated immune cell subsets key genes. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were utilized to calculate immune cell scores. Prognostic models and nomograms were developed through univariate and multivariate Cox analyses.

Results

Our analysis revealed that 48 DEPCDGs

SUBMITTER: Zhan F 

PROVIDER: S-EPMC11057167 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature