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Identification of significant genes signatures and prognostic biomarkers in cervical squamous carcinoma via bioinformatic data

BACKGROUND: Cervical squamous cancer (CESC) is an intractable gynecological malignancy because of its high mortality rate and difficulty in early diagnosis. Several biomarkers have been found to predict the prognose of CESC using bioinformatics methods, but they still lack clinical effectiveness. Mo...

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Autores principales: He, Yunan, Hu, Shunjie, Zhong, Jiaojiao, Cheng, Anran, Shan, Nianchun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718800/
https://www.ncbi.nlm.nih.gov/pubmed/33344075
http://dx.doi.org/10.7717/peerj.10386
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author He, Yunan
Hu, Shunjie
Zhong, Jiaojiao
Cheng, Anran
Shan, Nianchun
author_facet He, Yunan
Hu, Shunjie
Zhong, Jiaojiao
Cheng, Anran
Shan, Nianchun
author_sort He, Yunan
collection PubMed
description BACKGROUND: Cervical squamous cancer (CESC) is an intractable gynecological malignancy because of its high mortality rate and difficulty in early diagnosis. Several biomarkers have been found to predict the prognose of CESC using bioinformatics methods, but they still lack clinical effectiveness. Most of the existing bioinformatic studies only focus on the changes of oncogenes but neglect the differences on the protein level and molecular biology validation are rarely conducted. METHODS: Gene set data from the NCBI-GEO database were used in this study to compare the differences of gene and protein levels between normal and cancer tissues through significant pathway selection and core gene signature analysis to screen potential clinical biomarkers of CESC. Subsequently, the molecular and protein levels of clinical samples were verified by quantitative transcription PCR, western blot and immunohistochemistry. RESULTS: Three differentially expressed genes (RFC4, MCM2, TOP2A) were found to have a significant survival (P < 0.05) and highly expressed in CESC tissues. Molecular biological verification using quantitative reverse transcribed PCR, western blotting and immunohistochemistry assays exhibited significant differences in the expression of RFC4 between CESC and para-cancerous tissues (P < 0.05). CONCLUSION: This study identified three potential biomarkers (RFC4, MCM2, TOP2A) of CESC which may be useful to clarify the underlying mechanisms of CESC and predict the prognosis of CESC patients.
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spelling pubmed-77188002020-12-17 Identification of significant genes signatures and prognostic biomarkers in cervical squamous carcinoma via bioinformatic data He, Yunan Hu, Shunjie Zhong, Jiaojiao Cheng, Anran Shan, Nianchun PeerJ Bioinformatics BACKGROUND: Cervical squamous cancer (CESC) is an intractable gynecological malignancy because of its high mortality rate and difficulty in early diagnosis. Several biomarkers have been found to predict the prognose of CESC using bioinformatics methods, but they still lack clinical effectiveness. Most of the existing bioinformatic studies only focus on the changes of oncogenes but neglect the differences on the protein level and molecular biology validation are rarely conducted. METHODS: Gene set data from the NCBI-GEO database were used in this study to compare the differences of gene and protein levels between normal and cancer tissues through significant pathway selection and core gene signature analysis to screen potential clinical biomarkers of CESC. Subsequently, the molecular and protein levels of clinical samples were verified by quantitative transcription PCR, western blot and immunohistochemistry. RESULTS: Three differentially expressed genes (RFC4, MCM2, TOP2A) were found to have a significant survival (P < 0.05) and highly expressed in CESC tissues. Molecular biological verification using quantitative reverse transcribed PCR, western blotting and immunohistochemistry assays exhibited significant differences in the expression of RFC4 between CESC and para-cancerous tissues (P < 0.05). CONCLUSION: This study identified three potential biomarkers (RFC4, MCM2, TOP2A) of CESC which may be useful to clarify the underlying mechanisms of CESC and predict the prognosis of CESC patients. PeerJ Inc. 2020-12-02 /pmc/articles/PMC7718800/ /pubmed/33344075 http://dx.doi.org/10.7717/peerj.10386 Text en ©2020 He et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
He, Yunan
Hu, Shunjie
Zhong, Jiaojiao
Cheng, Anran
Shan, Nianchun
Identification of significant genes signatures and prognostic biomarkers in cervical squamous carcinoma via bioinformatic data
title Identification of significant genes signatures and prognostic biomarkers in cervical squamous carcinoma via bioinformatic data
title_full Identification of significant genes signatures and prognostic biomarkers in cervical squamous carcinoma via bioinformatic data
title_fullStr Identification of significant genes signatures and prognostic biomarkers in cervical squamous carcinoma via bioinformatic data
title_full_unstemmed Identification of significant genes signatures and prognostic biomarkers in cervical squamous carcinoma via bioinformatic data
title_short Identification of significant genes signatures and prognostic biomarkers in cervical squamous carcinoma via bioinformatic data
title_sort identification of significant genes signatures and prognostic biomarkers in cervical squamous carcinoma via bioinformatic data
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718800/
https://www.ncbi.nlm.nih.gov/pubmed/33344075
http://dx.doi.org/10.7717/peerj.10386
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