Modeling of senescence-related chemoresistance in ovarian cancer using data analysis and patient-derived organoids.

ABSTRACT:

Background

Ovarian cancer (OC) is a malignant tumor associated with poor prognosis owing to its susceptibility to chemoresistance. Cellular senescence, an irreversible biological state, is intricately linked to chemoresistance in cancer treatment. We developed a senescence-related gene signature for prognostic prediction and evaluated personalized treatment in patients with OC.

Methods

We acquired the clinical and RNA-seq data of OC patients from The Cancer Genome Atlas and identified a senescence-related prognostic gene set through differential and cox regression analysis in distinct chemotherapy response groups. A prognostic senescence-related signature was developed and validated by OC patient-derived-organoids (PDOs). We leveraged gene set enrichment analysis (GSEA) and

SUBMITTER: Cai X 

PROVIDER: S-EPMC10869451 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature