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A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction

机译:一种基于五种基于宫颈癌的预后签名,用于宫颈癌整体生存预测

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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.
机译:目标。本研究旨在鉴定宫颈癌的预后签名。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癌症基因组地图集和基因表达式综合数据库的三种数据集中获取。使用DESEQ2和雷玛用于筛选差异表达基因(DEGS)。所有数据集之间的重叠段都被认为是最后的参数。然后,进行功能性富集分析。此外,进行了COX比例危害回归以建立段的预后特征。应用了Kaplan-Meier分析来测试模型。 CHI方检验分析了宫颈癌中基因表达与临床病理学参数的关系,包括年龄,HPV状态,组织学,阶段和淋巴结转移。通过Cbioportal评估这些预后基因的体细胞突变。模型的稳健性在另外两个独立的验证队列中核实。主要发现。与正常宫颈组织相比,总共在宫颈癌中鉴定出169个重叠的上调基因和29个重叠的下调基因。功能性富集分析表明,DNA复制,细胞周期和P53信号传导途径主要富集。最后,建立了基于5-基因(ITM2A,DSG2,SPP1,EFNA1和MMP1)的预后签名。根据该模型,每位患者被赋予预后相关的风险价值。 Kaplan-Meier分析表明,宫颈癌中较差的风险较高有关,接收器下的面积为0.811,持续15年。在另外两个独立数据集中验证了该模型在预测宫颈癌结果中的有效性。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。我们的研究在宫颈癌中构建了预后模型,发现了与宫颈发生和存活的两种新的基因,ITM2A和DSG2。

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