Zhou Ying, Zhang Yuhong, Zhou Yang, Gu Yanzheng, Chen Youguo, Wang Juan
Department of Obstetrics and Gynecology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Jiangsu Institute of Clinical Immunology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Discov Oncol. 2025 Jan 8;16(1):18. doi: 10.1007/s12672-025-01752-8.
Ovarian cancer significantly impacts women's reproductive health and remains challenging to diagnose and treat. Despite advancements in understanding DNA repair mechanisms and identifying novel therapeutic targets, additional strategies are still needed. Recently, a novel form of cell death called disulfidptosis, which is triggered by glucose deprivation, has been linked to treatment resistance and changes in the tumor microenvironment (TME). However, its role in ovarian cancer is not well understood.
Bioinformatics analysis was performed on RNA-seq data from TCGA and GEO databases to identify disulfidptosis-related genes in ovarian cancer. Differential expression analysis and pathway enrichment were conducted, followed by the development of a prognostic model using LASSO Cox regression, validated with GEO datasets (GSE13876, GSE26712). Clinical samples were analyzed using quantitative polymerase chain reaction (qPCR) and immunohistochemistry (IHC) to validate gene expression.
This study identified disulfidptosis-related gene subtypes in ovarian cancer and demonstrated their influence on the tumor microenvironment (TME), immunotherapy responses, and patient prognosis. Six genes (IFNB1, IGF2, CD40LG, IL1B, IL21, CD38) associated with disulfidptosis were identified and incorporated into a prognostic model. This model predicted patient outcomes and was validated externally. Clinical validation showed its accuracy in predicting progression-free survival and resistance to platinum-based chemotherapy.
Our findings highlight the significant impact of disulfidptosis-related genes on the ovarian cancer tumor microenvironment, providing insights that could support the development of clinical evaluations and personalized treatment strategies.
卵巢癌对女性生殖健康有重大影响，其诊断和治疗仍然具有挑战性。尽管在理解DNA修复机制和确定新的治疗靶点方面取得了进展，但仍需要其他策略。最近，一种由葡萄糖剥夺引发的新型细胞死亡形式——二硫化物诱导的细胞死亡（disulfidptosis），已被证明与治疗耐药性和肿瘤微环境（TME）的变化有关。然而，其在卵巢癌中的作用尚不清楚。
对来自TCGA和GEO数据库的RNA测序数据进行生物信息学分析，以确定卵巢癌中与二硫化物诱导的细胞死亡相关的基因。进行差异表达分析和通路富集，随后使用LASSO Cox回归开发预后模型，并通过GEO数据集（GSE13876、GSE26712）进行验证。使用定量聚合酶链反应（qPCR）和免疫组织化学（IHC）分析临床样本，以验证基因表达。
本研究确定了卵巢癌中与二硫化物诱导的细胞死亡相关的基因亚型，并证明了它们对肿瘤微环境（TME）、免疫治疗反应和患者预后的影响。鉴定出六个与二硫化物诱导的细胞死亡相关的基因（IFNB1、IGF2、CD40LG、IL1B、IL21、CD38），并将其纳入预后模型。该模型预测了患者的预后，并在外部得到验证。临床验证表明其在预测无进展生存期和铂类化疗耐药性方面的准确性。
我们的研究结果突出了与二硫化物诱导的细胞死亡相关的基因对卵巢癌肿瘤微环境的重大影响，为支持临床评估和个性化治疗策略的发展提供了见解。
