Department of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China.
Department of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China.
Genomics. 2020 Nov;112(6):4827-4841. doi: 10.1016/j.ygeno.2020.08.027. Epub 2020 Sep 2.
This study aims to develop an immune-related genes (IRGs) prognostic signature to stratify the epithelial ovarian cancer (EOC) patients. We identified 332 up- and 154 down-regulated EOC-specific IRGs. As a result, candidate IRGs were idendified to construct prognostic models respectivy for overall survial and progression-free survival. The risk score was validated as a risk factor for prognosis and was used to built a combined nomogram. According to the IRG-related prognostic model, EOC patients were divided into high- and low- risk group and were further explored their association with tumor immune microenvironment (TME). CIBERSORT algorithm showed higher macrophages M1 cell, T cells follicular helper cell and plasma cells infiltrating levels in the low-risk group. In addition, the low-risk group was found with higher immunophenoscore and distinct mutation signatures compared with the high-risk group. These findings may shed light on the development of novel immune biomarkers and target therapy of EOC.
本研究旨在开发一种免疫相关基因（IRGs）预后signature，以对上皮性卵巢癌（EOC）患者进行分层。我们鉴定了 332 个上调和 154 个下调的 EOC 特异性 IRGs。结果，确定了候选 IRGs，分别构建了总生存期和无进展生存期的预后模型。风险评分被验证为预后的危险因素，并用于构建联合列线图。根据 IRG 相关的预后模型，EOC 患者被分为高风险和低风险组，并进一步探索了它们与肿瘤免疫微环境（TME）的关联。CIBERSORT 算法显示，低风险组中巨噬细胞 M1 细胞、滤泡辅助性 T 细胞和浆细胞的浸润水平较高。此外，与高风险组相比，低风险组的免疫表型评分更高，且具有明显的突变特征。这些发现可能为 EOC 的新型免疫生物标志物和靶向治疗的发展提供线索。
