Abstract
BACKGROUND: Ovarian cancer (OC) ranks as the fifth most prevalent neoplasm in women and exhibits an unfavorable prognosis. To improve the OC patient's prognosis, a pioneering risk signature was formulated by amalgamating disulfidptosis-related genes. METHODS: A comparative analysis of OC tissues and normal tissues was carried out, and differentially expressed disulfidptosis-related genes (DRGs) were found using the criteria of |log2 (fold change) | > 0.585 and adjusted P-value <0.05. Subsequently, the TCGA training set was utilized to create a prognostic risk signature, which was validated by employing both the TCGA testing set and the GEO dataset. Moreover, the immune cell infiltration, mutational load, response to chemotherapy, and response to immunotherapy were analyzed. To further validate these findings, QRT-PCR analysis was conducted on ovarian tumor cell lines. RESULTS: A risk signature was created using fourteen differentially expressed genes (DEGs) associated with disulfidptosis, enabling the classification of ovarian cancer (OC) patients into high-risk group (HRG) and low-risk group (LRG). The HRG exhibited a lower overall survival (OS) compared to the LRG. In addition, the risk score remained an independent predictor even after incorporating clinical factors. Furthermore, the LRG displayed lower stromal, immune, and estimated scores compared to the HRG, suggesting a possible connection between the risk signature, immune cell infiltration, and mutational load. Finally, the QRT-PCR experiments revealed that eight genes were upregulated in the human OC cell line SKOV3 compared with the human normal OC line IOSE80, while six genes were down-regulated. CONCLUSIONS: A fourteen-biomarker signature composed of disulfidptosis-related genes could serve as a valuable risk stratification tool in OC, facilitating the identification of patients who may benefit from individualized treatment and follow-up management.