ArticleHeliyon2024
Identification and validation of immunity- and disulfidptosis-related genes signature for predicting prognosis in ovarian cancer.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Disulfidptosis-based cancer therapy: Opportunity and challenge.Genes & diseases · 2027Review
- Retrospective analysis of the occurrence pattern of complications and prognostic influencing factors in elderly patients with squamous cell lung cancer after radical surgery.World journal of surgical oncology · 2026Article
- Metabolic-immune crosstalk in head and neck squamous cell carcinoma: CD44 and APP identified as causal therapeutic targets via integrated lactylation-Mendelian randomization analysis.Frontiers in immunology · 2026Article
- Sulfide regulation and catabolism in health and disease.Signal transduction and targeted therapy · 2025Review
- Unraveling shared diagnostic genes and cellular microenvironmental changes in endometriosis and recurrent implantation failure through multi-omics analysis.Scientific reports · 2025Article
- Establishment of a prognostic signature and immune infiltration characteristics for uterine corpus endometrial carcinoma based on a disulfidptosis/ferroptosis-associated signature.Frontiers in immunology · 2025Article
- Research progress and potential therapeutic targets of a novel disulfide stress-driven cell death-disulfidptosis in gynecological tumors and other gynecological disorders.American journal of cancer research · 2025Review
- The role of molecular subtypes and immune infiltration characteristics based on disulfidptosis-related genes in ovarian cancer.Discover oncology · 2024Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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