Large-scale transcriptome analysis reveals KIF20A as a novel indicator of cisplatin resistance in high-grade serous ovarian cancer

Abstract

Accurately assessing chemosensitivity to drugs such as cisplatin is crucial for optimizing outcomes of high-grade serous ovarian carcinoma (HGSOC) patients. Developing prediction models and identifying biomarkers can assist differentiate chemotherapy-sensitive from chemotherapy-resistant subtypes. We integrated 908 transcriptome samples from 12 HGSOC datasets of GEO and TCGA across four detection platforms. Differentially ranked genes (DRGs) were identified by applying intra-sample rank transformation and performing T-test. To refine the selection of informative DRGs, a recurrent logistic regression (RLR) model was employed, followed by model optimization using the Pairwise Analysis of Gene Expression (PAGE) algorithm to establish clinically applicable gene pair signature. Kinesin Family Member 20 A (KIF20A) and Chromogranin B (CHGB) were paired to establish a robust gene pair signature, KIF20A::CHGB Pair (KCP), which exhibited remarkable discriminant accuracy (Accuracy = 0.9397; AUROC = 0.9668; AUPRC = 0.9799) in distinguishing HGSOC from controls in eight independent validation cohorts. Further survival and functional analyses revealed that altered rank relationships between KIF20A and CHGB were significantly associated with prognosis and platinum resistance in HGSOC. Following exposure to standard chemotherapy regimens, we conducted RT-qPCR, CCK-8(Cell Counting Kit-8) viability assays, EdU proliferation assays, flow cytometry, and SynergyFinder, which collectively assessed cellular proliferation and cell-cycle responses, demonstrating that both genes contribute comparably to the malignant phenotype. Elevated KIF20A or CHGB expression drives chemoresistance and correlates with poor prognosis in HGSOC. Silencing either gene significantly enhances the growth‑inhibitory effects of cisplatin and other standard chemotherapeutic agents. Our findings establish KCP as a robust diagnostic and prognostic biomarker and highlight KIF20A and CHGB as synergistic targets for overcoming platinum resistance in ovarian cancer. • In silico experiments identified KIF20A::CHGB (KCP) as a cross-platform gene pair signature for distinguishing high-grade serous ovarian carcinoma (HGSOC) from normal tissues, achieving exceptional accuracy (AUROC = 0.9715) across eight independent cohorts. • In vitro experiments demonstrated that KIF20A and CHGB knockdown enhanced the sensitivity of ovarian cancer cells to cisplatin and suppressed tumor cell proliferation. • We developed a novel Recurrent Logistic Regression (RLR) model combined with Pairwise Analysis of Gene Expression (PAGE) to overcome batch effects and improve biomarker generalizability, offering a framework for multi-cohort transcriptomic studies.