Zhou Cankun, Li Chaomei, Yan Fangli, Zheng Yuhua
Department of Gynecology, Southern Medical University Affiliated Maternal & Child Health Hospital of Foshan, Foshan, 528000, Guangdong, China.
Department of Obstetrics and Gynecology, Southern Medical University Affiliated Maternal & Child Health Hospital of Foshan, Foshan, 528000, Guangdong, China.
Cancer Cell Int. 2020 Nov 9;20(1):541. doi: 10.1186/s12935-020-01560-w.
Uterine corpus endometrial carcinoma (UCEC) is a frequent gynecological malignancy with a poor prognosis particularly at an advanced stage. Herein, this study aims to construct prognostic markers of UCEC based on immune-related genes to predict the prognosis of UCEC.
We analyzed expression data of 575 UCEC patients from The Cancer Genome Atlas database and immune genes from the ImmPort database, which were used for generation and validation of the signature. We constructed a transcription factor regulatory network based on Cistrome databases, and also performed functional enrichment and pathway analyses for the differentially expressed immune genes. Moreover, the prognostic value of 410 immune genes was determined using the Cox regression analysis. We then constructed and verified a prognostic signature. Finally, we performed immune infiltration analysis using TIMER-generating immune cell content.
The immune cell microenvironment as well as the PI3K-Akt, and MARK signaling pathways were involved in UCEC development. The established prognostic signature revealed a ten-gene prognostic signature, comprising of PDIA3, LTA, PSMC4, TNF, SBDS, HDGF, HTR3E, NR3C1, PGR, and CBLC. This signature showed a strong prognostic ability in both the training and testing sets and thus can be used as an independent tool to predict the prognosis of UCEC. In addition, levels of B cells and neutrophils were significantly correlated with the patient's risk score, while the expression of ten genes was associated with immune cell infiltrates.
In summary, the ten-gene prognostic signature may guide the selection of the immunotherapy for UCEC.
子宫内膜癌（UCEC）是一种常见的妇科恶性肿瘤，预后较差，尤其是在晚期。本研究旨在基于免疫相关基因构建UCEC的预后标志物，以预测UCEC的预后。
我们分析了来自癌症基因组图谱数据库的575例UCEC患者的表达数据以及来自ImmPort数据库的免疫基因，这些数据用于特征的生成和验证。我们基于Cistrome数据库构建了转录因子调控网络，并对差异表达的免疫基因进行了功能富集和通路分析。此外，使用Cox回归分析确定了410个免疫基因的预后价值。然后我们构建并验证了一个预后特征。最后，我们使用TIMER生成免疫细胞含量进行免疫浸润分析。
免疫细胞微环境以及PI3K-Akt和MARK信号通路参与了UCEC的发生发展。建立的预后特征显示了一个由10个基因组成的预后特征，包括PDIA3、LTA、PSMC4、TNF、SBDS、HDGF、HTR3E、NR3C1、PGR和CBLC。该特征在训练集和测试集中均显示出很强的预后能力，因此可作为预测UCEC预后的独立工具。此外，B细胞和中性粒细胞水平与患者的风险评分显著相关，而10个基因的表达与免疫细胞浸润相关。
总之，这10个基因的预后特征可能指导UCEC免疫治疗的选择。
