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Identification of 5-methylcytosine-related signature for predicting prognosis in ovarian cancer

BACKGROUND: Ovarian cancer is one of the most common malignancies often resulting in a poor prognosis. 5-methylcytosine (m5C) is a common epigenetic modification with roles in eukaryotes. However, the expression and function of m5C regulatory factors in ovarian cancer remained unclear. RESULTS: Two...

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Autores principales: Wang, Lei, Gao, Song
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8240302/
https://www.ncbi.nlm.nih.gov/pubmed/34187591
http://dx.doi.org/10.1186/s40659-021-00340-8
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author Wang, Lei
Gao, Song
author_facet Wang, Lei
Gao, Song
author_sort Wang, Lei
collection PubMed
description BACKGROUND: Ovarian cancer is one of the most common malignancies often resulting in a poor prognosis. 5-methylcytosine (m5C) is a common epigenetic modification with roles in eukaryotes. However, the expression and function of m5C regulatory factors in ovarian cancer remained unclear. RESULTS: Two molecular subtypes with different prognostic and clinicopathological features were identified based on m5C regulatory factors. Meanwhile, functional annotation showed that in the two subtypes, 452 differentially expressed genes were significantly related to the malignant progression of ovarian cancer. Subsequently, four m5C genes were screened to construct a risk marker predictive of overall survival and indicative of clinicopathological features of ovarian cancer, also the robustness of the risk marker was verified in external dataset and internal validation set. multifactorial cox regression analysis and nomogram demonstrated that risk score was an independent prognostic factor for ovarian cancer prognosis. CONCLUSION: In conclusion, our results revealed that m5C-related genes play a critical role in tumor progression in ovarian cancer. Further detection of m5C methylation could provide a novel targeted therapy for treating ovarian cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40659-021-00340-8.
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spelling pubmed-82403022021-06-30 Identification of 5-methylcytosine-related signature for predicting prognosis in ovarian cancer Wang, Lei Gao, Song Biol Res Research Article BACKGROUND: Ovarian cancer is one of the most common malignancies often resulting in a poor prognosis. 5-methylcytosine (m5C) is a common epigenetic modification with roles in eukaryotes. However, the expression and function of m5C regulatory factors in ovarian cancer remained unclear. RESULTS: Two molecular subtypes with different prognostic and clinicopathological features were identified based on m5C regulatory factors. Meanwhile, functional annotation showed that in the two subtypes, 452 differentially expressed genes were significantly related to the malignant progression of ovarian cancer. Subsequently, four m5C genes were screened to construct a risk marker predictive of overall survival and indicative of clinicopathological features of ovarian cancer, also the robustness of the risk marker was verified in external dataset and internal validation set. multifactorial cox regression analysis and nomogram demonstrated that risk score was an independent prognostic factor for ovarian cancer prognosis. CONCLUSION: In conclusion, our results revealed that m5C-related genes play a critical role in tumor progression in ovarian cancer. Further detection of m5C methylation could provide a novel targeted therapy for treating ovarian cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40659-021-00340-8. BioMed Central 2021-06-29 /pmc/articles/PMC8240302/ /pubmed/34187591 http://dx.doi.org/10.1186/s40659-021-00340-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Wang, Lei
Gao, Song
Identification of 5-methylcytosine-related signature for predicting prognosis in ovarian cancer
title Identification of 5-methylcytosine-related signature for predicting prognosis in ovarian cancer
title_full Identification of 5-methylcytosine-related signature for predicting prognosis in ovarian cancer
title_fullStr Identification of 5-methylcytosine-related signature for predicting prognosis in ovarian cancer
title_full_unstemmed Identification of 5-methylcytosine-related signature for predicting prognosis in ovarian cancer
title_short Identification of 5-methylcytosine-related signature for predicting prognosis in ovarian cancer
title_sort identification of 5-methylcytosine-related signature for predicting prognosis in ovarian cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8240302/
https://www.ncbi.nlm.nih.gov/pubmed/34187591
http://dx.doi.org/10.1186/s40659-021-00340-8
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