Identification of a prognostic signature of epithelial ovarian cancer based on tumor immune microenvironment exploration
Identification of a prognostic signature of epithelial ovarian cancer based on tumor immune microenvironment exploration
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基于肿瘤免疫微环境探索鉴定上皮性卵巢癌的预后特征
DOI：
10.1016/j.ygeno.2020.08.027
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发表时间：
2020-11-01
期刊：
影响因子：
4.4
通讯作者：
Cheng, Wenjun
中科院分区：
文献类型：
--
作者：
Liu, Jinhui;Meng, Huangyang;Cheng, Wenjun
本研究旨在开发免疫相关基因(IRGS)预后标志物来对上皮性卵巢癌(EOC)患者进行分层。我们发现了332个上调的和154个下调的EoC特定的IRG。结果，候选的IRG被识别，以分别构建总体生存和无进展生存的预后模型。风险评分被确认为预后的危险因素，并被用来建立组合诺模图。根据IRG相关预后模型，将卵巢癌患者分为高危组和低危组，并进一步探讨其与肿瘤免疫微环境(TME)的关系。CiberSort算法显示低危组的巨噬细胞M1细胞、T细胞、滤泡辅助细胞和浆细胞的水平较高。此外，与高风险组相比，低风险组具有更高的免疫表位和明显的突变特征。这些发现可能为新的免疫标志物的开发和卵巢癌的靶向治疗提供参考。
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.