Quan Qingli, Xiong Xinxin, Wu Shanyun, Yu Meixing
Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.
School of Life Sciences, Fudan University, Shanghai, China.
Front Genet. 2021 Nov 15;12:760225. doi: 10.3389/fgene.2021.760225. eCollection 2021.
Ovarian cancer (OV) is a fatal gynecologic malignancy and has poor survival rate in women over the age of forty. In our study, we aimed to identify genes related to immune microenvironment regulations and explore genes associated with OV prognosis. The RNA-seq data of GDC TCGA Ovarian Cancer cohort of 376 patients was retrieved from website. Weighted gene co-expression network analysis (WGCNA) and ESTIMATE algorithm were applied to identify the key genes associated with the immune scores. The correlation between key genes and 22 immune cell types were estimated by using CIBERSORT algorithms. WGCNA showed that the pink module was most correlated with the immune score. Seven of 14 key genes (FCRL3, IFNG, KCNA3, LY9, PLA2G2D, THEMIS, and TRAT1) were significantly associated with the OS of OV patients. Correlation analysis showed our key genes positively related to M1 macrophages, CD8 T cells, plasma cells, regulatory T (Treg) cells and activated memory CD4 T cells, and negatively related to naive CD4 T cells, M0 macrophages, activated dendritic cells (DCs) and memory B cells. Kaplan-Meier survival analysis showed that lower abundances of neutrophils and higher abundances of M1 macrophages, plasma cells, T cells gamma delta (γδT) cells and follicular helper T (Tfh) cells predicted better OV prognosis. Forteen key genes related to the immune infiltrating of OV were identified, and seven of them were significantly related to prognosis. These key genes have potential roles in tumor infiltrating immune cells differentiation and proliferation. This study provided potential prognostic markers and immunotherapy targets for OV.
卵巢癌（OV）是一种致命的妇科恶性肿瘤，40岁以上女性的生存率较低。在我们的研究中，我们旨在鉴定与免疫微环境调节相关的基因，并探索与OV预后相关的基因。从网站上检索了376例患者的GDC TCGA卵巢癌队列的RNA测序数据。应用加权基因共表达网络分析（WGCNA）和ESTIMATE算法来鉴定与免疫评分相关的关键基因。使用CIBERSORT算法估计关键基因与22种免疫细胞类型之间的相关性。WGCNA显示粉色模块与免疫评分相关性最高。14个关键基因中的7个（FCRL3、IFNG、KCNA3、LY9、PLA2G2D、THEMIS和TRAT1）与OV患者的总生存期显著相关。相关性分析表明，我们的关键基因与M1巨噬细胞、CD8 T细胞、浆细胞、调节性T（Treg）细胞和活化记忆CD4 T细胞呈正相关，与初始CD4 T细胞、M0巨噬细胞、活化树突状细胞（DCs）和记忆B细胞呈负相关。Kaplan-Meier生存分析表明，中性粒细胞丰度较低以及M1巨噬细胞、浆细胞、γδT细胞和滤泡辅助性T（Tfh）细胞丰度较高预示着更好的OV预后。鉴定出14个与OV免疫浸润相关的关键基因，其中7个与预后显著相关。这些关键基因在肿瘤浸润免疫细胞的分化和增殖中具有潜在作用。本研究为OV提供了潜在的预后标志物和免疫治疗靶点。
