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

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 databa...

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Autores principales: Zhao, Menghuang, Huang, Wenbin, Zou, Shuangwei, Shen, Qi, Zhu, Xueqiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7136791/
https://www.ncbi.nlm.nih.gov/pubmed/32300605
http://dx.doi.org/10.1155/2020/8347639
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author Zhao, Menghuang
Huang, Wenbin
Zou, Shuangwei
Shen, Qi
Zhu, Xueqiong
author_facet Zhao, Menghuang
Huang, Wenbin
Zou, Shuangwei
Shen, Qi
Zhu, Xueqiong
author_sort Zhao, Menghuang
collection PubMed
description 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.
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spelling pubmed-71367912020-04-16 A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction Zhao, Menghuang Huang, Wenbin Zou, Shuangwei Shen, Qi Zhu, Xueqiong Int J Genomics Research Article 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. Hindawi 2020-03-25 /pmc/articles/PMC7136791/ /pubmed/32300605 http://dx.doi.org/10.1155/2020/8347639 Text en Copyright © 2020 Menghuang Zhao et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhao, Menghuang
Huang, Wenbin
Zou, Shuangwei
Shen, Qi
Zhu, Xueqiong
A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction
title A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction
title_full A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction
title_fullStr A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction
title_full_unstemmed A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction
title_short A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction
title_sort five-genes-based prognostic signature for cervical cancer overall survival prediction
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7136791/
https://www.ncbi.nlm.nih.gov/pubmed/32300605
http://dx.doi.org/10.1155/2020/8347639
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