Characterization of tumor prognosis and sensitive chemotherapy drugs based on cuproptosis-related gene signature in ovarian cancer.

Abstract

Background: Cuproptosis is a novel form of cell death, acting on the tricarboxylic acid cycle in mitochondrial respiration and mediated by protein lipoylation. Other cancer cell death processes, such as necroptosis, pyroptosis, and ferroptosis, have been shown to play crucial roles in the therapy and prognosis of ovarian cancer. However, the role of cuproptosis in ovarian cancer remains unclear.

Methods: The expression profiles of 10 cuproptosis-related genes were extracted from GSE140082. Kaplan-Meier survival and Cox proportional hazards regression were used to identify prognostic genes for constructing risk models. Following this, Least Absolute Shrinkage and Selection Operator regression was employed to construct a risk score model. Next, a nomogram was constructed to predict overall survival in ovarian cancer. Ultimately, our analysis compared the two groups across various dimensions, including clinical characteristics, tumor progression, metabolism-related pathways, immune landscape, and drug sensitivity.

Results: MTF1 and LIAS were identified as protective factors in ovarian cancer, with patients in the higher risk group being significantly associated with poorer survival. Furthermore, integrating the risk score with clinical characteristics in the nomogram demonstrated high specificity and sensitivity in predicting survival. A higher propotion of M2 macrophages, follicular helper T cells, and resting mast cells was observed in the high-risk group. Additionally, the IC50 values of Dasatinib, Bortezomib, Parthenolide, and Imatinib were significantly lower in the high-risk group.

Conclusions: The study highlights the prognostic significance of cuproptosis-related genes and provides new insights into developing pharmacological therapeutic strategies targeting cuproptosis for the prevention and treatment of ovarian cancer.