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

作者：Xintong Cai, Yanhong Li, Jianfeng Zheng, Li Liu, Zicong Jiao, Jie Lin, Shan Jiang, Xuefen Lin, Yang Sun · 发表于：Frontiers in Oncology · 年份：2024 · DOI：10.3389/fonc.2023.1291559 · 被引用次数：17 · 研究领域：Telomeres, Telomerase, and Senescence、PARP inhibition in cancer therapy、Chromatin Remodeling and Cancer

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 ESTIMATE to unravel the potential functions and immune landscape of the model. Moreover, we explored the correlation between risk scores and potential chemotherapeutic agents. After confirming the congruence between organoids and tumor tissues through immunohistochemistry, we measured the IC 50 of cisplatin in PDOs using the ATP activity assay, categorized by resistance and sensitivity to the drug. We also investigated the expression patterns of model genes across different groups. Results We got 2740 differentially expressed genes between two chemotherapy response groups including 43 senescence-related genes. Model prognostic genes were yielded through univariate cox analysis, and multifactorial cox analy...