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Identification of Potential Prognostic Long Non-Coding RNA Biomarkers for Predicting Recurrence in Patients with Cervical Cancer

BACKGROUND: Cervical cancer (CC) is one of the most common malignant tumors in women, and its treatment is often accompanied by high recurrence. We aimed to identify the long non-coding RNAs (lncRNAs) associated with CC recurrence. METHODS: We downloaded lncRNAs expression data of CC patients from T...

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Autores principales: Zhang, Yan, Zhang, Xing, Zhu, Haixia, Liu, Yang, Cao, Jian, Li, Dake, Ding, Bo, Yan, Wenjing, Jin, Hua, Wang, Shizhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7002755/
https://www.ncbi.nlm.nih.gov/pubmed/32099468
http://dx.doi.org/10.2147/CMAR.S231796
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author Zhang, Yan
Zhang, Xing
Zhu, Haixia
Liu, Yang
Cao, Jian
Li, Dake
Ding, Bo
Yan, Wenjing
Jin, Hua
Wang, Shizhi
author_facet Zhang, Yan
Zhang, Xing
Zhu, Haixia
Liu, Yang
Cao, Jian
Li, Dake
Ding, Bo
Yan, Wenjing
Jin, Hua
Wang, Shizhi
author_sort Zhang, Yan
collection PubMed
description BACKGROUND: Cervical cancer (CC) is one of the most common malignant tumors in women, and its treatment is often accompanied by high recurrence. We aimed to identify the long non-coding RNAs (lncRNAs) associated with CC recurrence. METHODS: We downloaded lncRNAs expression data of CC patients from The Cancer Genome Atlas (TCGA) dataset and used Cox regression models to analyze the lncRNAs relationship with CC recurrence. The significantly associated lncRNAs were utilized to construct a recurrence risk score (RRS) model. Bioinformatics analyses were used to assess the potential role of the critical lncRNAs in CC recurrence. The effect of critical lncRNAs on CC phenotype was determined by in vitro experiments. RESULTS: Using Cox regression analysis, four lncRNAs, ie, HCG11, CASC15, LINC00189, and LINC00905, were markedly associated with worse recurrence-free survival (RFS) of CC, whereas three lncRNAs, including HULC, LINC00173, and MIR22HG, were the opposite. After constructing the RRS model, Kaplan-Meier analysis revealed that patients with high RRS had significantly increased risk of recurrence. Among the 20 types of tumors in the TCGA database which all had adjacent normal tissues, MIR22HG and HCG11were significantly downregulated in 18 and 10 types of tumors including CC, respectively. Increased MIR22HG was significantly relevant to decreased risks of recurrence among the subgroups of age at diagnosis < 45 (Hazard Ratio (HR) = 0.26), stage I/II (HR = 0.33), T stage I/II (HR = 0.30), chemotherapy (HR = 0.18), and molecular therapy (HR = 0.16). Functionally, elevated MIR22HG expression could suppress CC cell proliferation, migration and invasion. CONCLUSION: MIR22HG has a fundamental role in CC recurrence and could be served as a potential prognostic biomarker.
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spelling pubmed-70027552020-02-25 Identification of Potential Prognostic Long Non-Coding RNA Biomarkers for Predicting Recurrence in Patients with Cervical Cancer Zhang, Yan Zhang, Xing Zhu, Haixia Liu, Yang Cao, Jian Li, Dake Ding, Bo Yan, Wenjing Jin, Hua Wang, Shizhi Cancer Manag Res Original Research BACKGROUND: Cervical cancer (CC) is one of the most common malignant tumors in women, and its treatment is often accompanied by high recurrence. We aimed to identify the long non-coding RNAs (lncRNAs) associated with CC recurrence. METHODS: We downloaded lncRNAs expression data of CC patients from The Cancer Genome Atlas (TCGA) dataset and used Cox regression models to analyze the lncRNAs relationship with CC recurrence. The significantly associated lncRNAs were utilized to construct a recurrence risk score (RRS) model. Bioinformatics analyses were used to assess the potential role of the critical lncRNAs in CC recurrence. The effect of critical lncRNAs on CC phenotype was determined by in vitro experiments. RESULTS: Using Cox regression analysis, four lncRNAs, ie, HCG11, CASC15, LINC00189, and LINC00905, were markedly associated with worse recurrence-free survival (RFS) of CC, whereas three lncRNAs, including HULC, LINC00173, and MIR22HG, were the opposite. After constructing the RRS model, Kaplan-Meier analysis revealed that patients with high RRS had significantly increased risk of recurrence. Among the 20 types of tumors in the TCGA database which all had adjacent normal tissues, MIR22HG and HCG11were significantly downregulated in 18 and 10 types of tumors including CC, respectively. Increased MIR22HG was significantly relevant to decreased risks of recurrence among the subgroups of age at diagnosis < 45 (Hazard Ratio (HR) = 0.26), stage I/II (HR = 0.33), T stage I/II (HR = 0.30), chemotherapy (HR = 0.18), and molecular therapy (HR = 0.16). Functionally, elevated MIR22HG expression could suppress CC cell proliferation, migration and invasion. CONCLUSION: MIR22HG has a fundamental role in CC recurrence and could be served as a potential prognostic biomarker. Dove 2020-01-31 /pmc/articles/PMC7002755/ /pubmed/32099468 http://dx.doi.org/10.2147/CMAR.S231796 Text en © 2020 Zhang et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Zhang, Yan
Zhang, Xing
Zhu, Haixia
Liu, Yang
Cao, Jian
Li, Dake
Ding, Bo
Yan, Wenjing
Jin, Hua
Wang, Shizhi
Identification of Potential Prognostic Long Non-Coding RNA Biomarkers for Predicting Recurrence in Patients with Cervical Cancer
title Identification of Potential Prognostic Long Non-Coding RNA Biomarkers for Predicting Recurrence in Patients with Cervical Cancer
title_full Identification of Potential Prognostic Long Non-Coding RNA Biomarkers for Predicting Recurrence in Patients with Cervical Cancer
title_fullStr Identification of Potential Prognostic Long Non-Coding RNA Biomarkers for Predicting Recurrence in Patients with Cervical Cancer
title_full_unstemmed Identification of Potential Prognostic Long Non-Coding RNA Biomarkers for Predicting Recurrence in Patients with Cervical Cancer
title_short Identification of Potential Prognostic Long Non-Coding RNA Biomarkers for Predicting Recurrence in Patients with Cervical Cancer
title_sort identification of potential prognostic long non-coding rna biomarkers for predicting recurrence in patients with cervical cancer
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7002755/
https://www.ncbi.nlm.nih.gov/pubmed/32099468
http://dx.doi.org/10.2147/CMAR.S231796
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