Identification of a Novel Model for Predicting the Prognosis and Immune Response Based on Genes Related to Cuproptosis and Ferroptosis in Ovarian Cancer

Simple Summary Ovarian cancer is highly malignant with a poor prognosis, and there is still a lack of effective treatment methods. The exploration of modulating cell death processes has facilitated cancer treatment. Cuproptosis and ferroptosis are two novel forms of dying, and we sought to explore new biomarkers associated with them to guide the treatment of ovarian cancer. Our study established specific molecular types based on 39 genes related to cuproptosis and ferroptosis. And we systematically evaluated the differences in prognosis, drugs, and immunotherapy response between different subtypes of ovarian cancer. Molecular subtypes and risk model showed superior prognosis prediction and immune response prediction capabilities, which can provide a reference for personalized treatment of ovarian cancer. (1) Background: Ovarian cancer (OV) presents a high degree of malignancy and a poor prognosis. Cell death is necessary to maintain tissue function and morphology. Cuproptosis and ferroptosis are two novel forms of death, and we look forward to finding their relationship with OV and providing guidance for treatment. (2) Methods: We derived information about OV from public databases. Based on cuproptosis-related and ferroptosis-related genes, a risk model was successfully constructed, and exceptional subtypes were identified. Next, various methods are applied to assess prognostic value and treatment sensitivity. Besides, the comprehensive analysis of the tumor environment, together with immune cell infiltration, immune function status, immune checkpoint, and human HLA genes, is expected to grant assistance for the prognosis and treatment of OV. (3) Results: Specific molecular subtypes and models possessed excellent potential to predict prognosis. Immune infiltration abundance varied between groups. The susceptibility of individuals to different chemotherapy drugs and immunotherapies could be predicted based on specific groups. (4) Conclusions: Our molecular subtypes and risk model, with strong immune prediction and prognostic prediction capabilities, are committed to guiding ovarian cancer treatment.