Aims. This study is aimed at identifying a prognostic signature for cervical cancer. Main Methods. The gene expression data and clinical information of cervical cancer and normal cervical tissues were acquired from The Cancer Genome Atlas and from three datasets of the Gene Expression Omnibus database. DESeq2 and Limma were employed to screen differentially expressed genes (DEGs). The overlapping DEGs among all datasets were considered the final DEGs. Then, the functional enrichment analysis was performed. Moreover, the Cox proportional hazards regression was performed to establish a prognostic signature of the DEGs. The Kaplan-Meier analysis was applied to test the model. Relationships between gene expression and clinicopathological parameters in cervical cancer, including age, HPV status, histology, stage, and lymph node metastasis, were analysed by the chi-square test. The somatic mutations of these prognostic genes were assessed through cBioPortal. The robustness of the model was verified in another two independent validation cohorts. Key Findings. In total, 169 overlapping upregulated genes and 29 overlapping downregulated genes were identified in cervical cancer compared with normal cervical tissues. Functional enrichment analysis indicated that the DEGs were mainly enriched in DNA replication, the cell cycle, and the p53 signalling pathway. Finally, a 5-gene- (ITM2A, DSG2, SPP1, EFNA1, and MMP1) based prognostic signature was built. According to this model, each patient was given a prognostic-related risk value. The Kaplan-Meier analysis showed that a higher risk was related to worse overall survival in cervical cancer, with an area under the receiver operating characteristic curve of 0.811 for 15 years. The validity of this model in the prediction of cervical cancer outcome was verified in another two independent datasets. In addition, our study also found that the low expression of ITM2A was associated with cervical adenocarcinoma. Interestingly, DSG2 was associated with the HPV status of cervical cancer. Significance. Our study constructed a prognostic model in cervical cancer and discovered two novel genes, ITM2A and DSG2, associated with cervical carcinogenesis and survival.

中文翻译：

---

基于五基因的宫颈癌总体生存预测的预后签名。

目的。这项研究旨在确定子宫颈癌的预后标志。主要方法。宫颈癌和正常宫颈组织的基因表达数据和临床信息是从The Cancer Genome Atlas和Gene Expression Omnibus数据库的三个数据集中获得的。DESeq2和Limma用于筛选差异表达基因（DEG）。所有数据集之间重叠的DEG被视为最终DEG。然后，进行功能富集分析。此外，进行了Cox比例风险回归以建立DEG的预后标志。应用Kaplan-Meier分析来测试模型。卡方检验分析了宫颈癌中基因表达与临床病理参数之间的关系，包括年龄，HPV状况，组织学，分期和淋巴结转移。通过cBioPortal评估了这些预后基因的体细胞突变。在另外两个独立的验证队列中验证了模型的鲁棒性。主要发现。与正常宫颈组织相比，宫颈癌中总共鉴定出169个重叠的上调基因和29个重叠的下调基因。功能富集分析表明，DEG主要富集于DNA复制，细胞周期和p53信号传导途径。最后，建立了一个基于5基因（ITM2A，DSG2，SPP1，EFNA1和MMP1）的预后签名。根据该模型，为每个患者提供了与预后相关的风险值。Kaplan-Meier分析显示，子宫颈癌的较高风险与总体生存期较差有关，接受者工作特征曲线下的面积在15年内为0.811。在另外两个独立的数据集中验证了该模型在预测宫颈癌预后中的有效性。此外，我们的研究还发现，ITM2A的低表达与宫颈腺癌有关。有趣的是，DSG2与宫颈癌的HPV状态有关。意义。我们的研究构建了宫颈癌的预后模型，并发现了两个与宫颈癌发生和生存相关的新基因ITM2A和DSG2。