Li Ying, Fang Tian, Shan Wanying, Gao Qinglei
Key Laboratory of the Ministry of Education, Cancer Biology Research Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Cancers (Basel). 2023 Jan 18;15(3):579. doi: 10.3390/cancers15030579.
(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.
(1) 背景:卵巢癌(OV)具有高度恶性且预后较差。细胞死亡对于维持组织功能和形态至关重要。铜死亡和铁死亡是两种新型的死亡形式,我们期望找到它们与卵巢癌的关系并为治疗提供指导。(2) 方法:我们从公共数据库中获取有关卵巢癌的信息。基于与铜死亡相关和与铁死亡相关的基因,成功构建了一个风险模型,并识别出不同的亚型。接下来,应用各种方法评估预后价值和治疗敏感性。此外,对肿瘤环境以及免疫细胞浸润、免疫功能状态、免疫检查点和人类HLA基因进行综合分析,有望为卵巢癌的预后和治疗提供帮助。(3) 结果:特定的分子亚型和模型具有出色的预后预测潜力。各组之间免疫浸润丰度有所不同。基于特定分组可以预测个体对不同化疗药物和免疫疗法的敏感性。(4) 结论:我们的分子亚型和风险模型具有强大的免疫预测和预后预测能力,致力于指导卵巢癌治疗。