Systemic characterization of alternative splicing related to prognosis, immune infiltration, and drug sensitivity analysis in ovarian cancer.

ABSTRACT:

Background

Alternative splicing (AS) plays an essential role in tumorigenesis and progression. This study intended to construct an innovative prognostic model based on AS events to gain more precise survival prediction and search for potential therapeutic targets in ovarian cancer.

Methods

Seven types of AS events in ovarian serous cystadenocarcinoma (OV) patients with RNA-seq were obtained using The Cancer Genome Atlas (TCGA) SpliceSeq tool and database. Cox and Kaplan-Meier curve analyses were employed to establish the prognostic models. Relying on drug sensitivity data from the CellMiner database, Genomics of Drug Sensitivity (GDS) was adopted to estimate the platinum-sensitive analysis. Furthermore, a prognostic splicing factor (SF)-AS network was constructed using Cytos

SUBMITTER: Liu Q 

PROVIDER: S-EPMC8848412 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature