Purpose Copper-dependent death is a novel mode of cell death. The prognostic value of copper death-associated genes in ovarian cancer needs further elucidation. In this study, a risk model based on copper death-related genes was identified for predicting prognosis and immunotherapy sensitivity in ovarian cancer patients. Methods Copper death-related genes were obtained according to literature reports. Transcriptome and prognostic information of ovarian cancer patients were obtained from TCGA database. Based on the expression of 10 copper death-associated genes, ovarian cancer patients from TCGA were typed by consensus clustering algorithm. Multi-gene risk profiles were developed from the TCGA cohort using least absolute shrinkage and selection operator (LASSO) regression analysis, followed by external validation set validation using the GEO database. Immunological correlation of the models was calculated by the CIBERSORTx algorithm and ESTIMATE algorithm, and drug sensitivity analysis was performed for patients with different risk models. Results Based on the expression of 10 copper death-related genes, 367 TCGA-OV cases could be better classified into two subtypes. 23 inter-subgroup differential genes screened in TCGA-OV were corrected with GEO data and 15 intersecting genes were extracted. Univariate COX analysis showed a total of 5 inter-subgroup difference genes associated with ovarian cancer survival (P < 0.05), and lasso regression finally screened 5 genes for the construction of risk models. GO and KEGG functional analysis of differential genes between high and low risk groups showed that multiple immune components and immunomodulatory pathways were enriched to. Further analysis of the immune status between the high and low risk groups suggested that the low risk group had more active immune cell infiltration and multiple immune checkpoint enrichment. Drug sensitivity analysis suggested that patients in the risk group had higher sensitivity to multiple chemotherapeutic agents. Conclusion Copper death-related genes may be used as a new biomarker for predicting ovarian cancer prognosis, and treatment targeting copper death genes may be a new therapeutic modality to achieve efficient remission in OC.

Background Under physiological conditions, DNA damage and repair are in a dynamic equilibrium. When this equilibrium is disrupted, the cell undergoes pathological changes, eventually the cell becomes cancerous. Ovarian cancer (OC) is a malignant disease with unique genomic characteristics, most of the chemotherapeutic agents currently used in ovarian cancer depend on the balance between damage and repair of DNA (DDR). DDR-related genes have potential value as prognostic indicators for ovarian cancer. Results DDR-related genes can well typing ovarian cancer patients, 16 genes associated with prognosis of ovarian cancer patients (CH25H, CCR7, CACNA1C, SLC4A8, CXCL11, UBD, TRPV4, RPS6KA2, FCGBP, TOMM20L, STX18, PI3, CMBL, ISG20, AKAP12, and PIGS) were screened as risk genes for the construction of ovarian cancer prognostic models. Conclusion Based on DDR-related genes for ovarian cancer typing and studying the prognostic relevance of differential genes between typing on ovarian cancer, 16 genes were screened for predicting poor prognosis of OC. To provide research directions for subsequent drug development and research basis for clinical application.