Abstract
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.
Highlights
Cervical cancer ranks as the fourth most common cancer in women worldwide [1]
Compared with the normal cervical samples, 169 upregulated differentially expressed genes (DEGs) and 29 downregulated DEGs in cervical cancer overlapped among the three microarray datasets and the The Cancer Genome Atlas (TCGA) dataset (Figure 1)
The analysis identified 8 upregulated DEGs that were significantly related to poor overall survival in the TCGA cohort and 3 downregulated DEGs that were related to good overall survival (P < 0:05)
Summary
Cervical cancer ranks as the fourth most common cancer in women worldwide [1]. Even in developed countries such as the United States, there were approximately 13 170 newly diagnosed cases of cervical cancer and 4 250 deaths in 2019 [2]. Some advances have been made in the screening technology for cervical cancer and human papillomavirus vaccine applications, the survival rate remains poor [3]. Another critical problem with cervical cancer is the heterogeneity in clinical outcomes among individuals with the same disease [4]. Numerous studies have shown the clinical importance of the messenger RNA expression in numerous cancers, including cervical cancer [6]. Messenger RNAs play pivotal roles in diverse physiological and pathological processes, such as differentiation, cell proliferation, development, apoptosis, and stress responses [7]
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