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A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction
Joint Authors
Zhu, Xueqiong
Shen, Qi
Huang, Wenbin
Zhao, Menghuang
Zou, Shuangwei
Source
International Journal of Genomics
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-26
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Zhao, Menghuang& Huang, Wenbin& Zou, Shuangwei& Shen, Qi& Zhu, Xueqiong. 2020. A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction. International Journal of Genomics،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1171332
Modern Language Association (MLA)
Zhao, Menghuang…[et al.]. A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction. International Journal of Genomics No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1171332
American Medical Association (AMA)
Zhao, Menghuang& Huang, Wenbin& Zou, Shuangwei& Shen, Qi& Zhu, Xueqiong. A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction. International Journal of Genomics. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1171332
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1171332