Wang Wei, Wu Qianqian, Wang Ziheng, Ren Shiqi, Shen Hanyu, Shi Wenyu, Xu Yunzhao
Department of Clinical Biobank, Nantong University Affiliated Hospital, Nantong, China.
Department of Medicine, Nantong University Xinling College, Nantong, China.
Front Oncol. 2021 Mar 31;11:647273. doi: 10.3389/fonc.2021.647273. eCollection 2021.
Ovarian cancer (OV) has become the most lethal gynecological cancer. However, its treatment methods and staging system are far from ideal. In the present study, taking the advantage of large-scale public cohorts, we extracted a list of immune-related prognostic genes that differentially expressed in tumor and normal ovarian tissues. Importantly, an individualized immune-related gene based prognostic model (IPM) for OV patients were developed. Furthermore, we validated our IPM in Gene Expression Omnibus (GEO) repository and compared the immune landscape and pathways between high-risk and low-risk groups. The results of our study can serve as an important model to identify the immune subset of patients and has potential for use in immune therapeutic selection and patient management.
卵巢癌（OV）已成为最致命的妇科癌症。然而，其治疗方法和分期系统远非理想。在本研究中，利用大规模公共队列，我们提取了一份在肿瘤和正常卵巢组织中差异表达的免疫相关预后基因列表。重要的是，我们开发了一种基于个体免疫相关基因的卵巢癌患者预后模型（IPM）。此外，我们在基因表达综合数据库（GEO）中验证了我们的IPM，并比较了高风险和低风险组之间的免疫格局和通路。我们的研究结果可作为识别患者免疫亚群的重要模型，并具有用于免疫治疗选择和患者管理的潜力。
