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HPV‐related methylation‐based reclassification and risk stratification of cervical cancer

Human papillomavirus (HPV) is a clear etiology of cervical cancer (CC). However, the associations between HPV infection and DNA methylation have not been thoroughly investigated. Additionally, it remains unknown whether HPV‐related methylation signatures can identify subtypes of CC and stratify the...

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Autores principales: Yang, Si, Wu, Ying, Wang, Shuqian, Xu, Peng, Deng, Yujiao, Wang, Meng, Liu, Kang, Tian, Tian, Zhu, Yuyao, Li, Na, Zhou, Linghui, Dai, Zhijun, Kang, Huafeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7463306/
https://www.ncbi.nlm.nih.gov/pubmed/32408396
http://dx.doi.org/10.1002/1878-0261.12709
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author Yang, Si
Wu, Ying
Wang, Shuqian
Xu, Peng
Deng, Yujiao
Wang, Meng
Liu, Kang
Tian, Tian
Zhu, Yuyao
Li, Na
Zhou, Linghui
Dai, Zhijun
Kang, Huafeng
author_facet Yang, Si
Wu, Ying
Wang, Shuqian
Xu, Peng
Deng, Yujiao
Wang, Meng
Liu, Kang
Tian, Tian
Zhu, Yuyao
Li, Na
Zhou, Linghui
Dai, Zhijun
Kang, Huafeng
author_sort Yang, Si
collection PubMed
description Human papillomavirus (HPV) is a clear etiology of cervical cancer (CC). However, the associations between HPV infection and DNA methylation have not been thoroughly investigated. Additionally, it remains unknown whether HPV‐related methylation signatures can identify subtypes of CC and stratify the prognosis of CC patients. DNA methylation profiles were obtained from The Cancer Genome Atlas to identify HPV‐related methylation sites. Unsupervised clustering analysis of HPV‐related methylation sites was performed to determine the different CC subtypes. CC patients were categorized into cluster 1 (Methylation‐H), cluster 2 (Methylation‐M), and cluster 3 (Methylation‐L). Compared to Methylation‐M and Methylation‐L, Methylation‐H exhibited a significantly improved overall survival (OS). Gene set enrichment analysis (GSEA) was conducted to investigate the functions that correlated with different CC subtypes. GSEA indicated that the hallmarks of tumors, including KRAS signaling, TNFα signaling via NF‐κB, inflammatory response, epithelial–mesenchymal transition, and interferon‐gamma response, were enriched in Methylation‐M and Methylation‐L. Based on mutation and copy number variation analyses, we found that aberrant mutations, amplifications, and deletions among the MYC, Notch, PI3K‐AKT, and RTK‐RAS pathways were most frequently detected in Methylation‐H. Additionally, mutations, amplifications, and deletions within the Hippo, PI3K‐AKT, and TGF‐β pathways were presented in Methylation‐M. Genes within the cell cycle, Notch, and Hippo pathways possessed aberrant mutations, amplifications, and deletions in Methylation‐L. Moreover, the analysis of tumor microenvironments revealed that Methylation‐H was characterized by a relatively low degree of immune cell infiltration. Finally, a prognostic signature based on six HPV‐related methylation sites was developed and validated. Our study revealed that CC patients could be classified into three heterogeneous clusters based on HPV‐related methylation signatures. Additionally, we derived a prognostic signature using six HPV‐related methylation sites that stratified the OS of patients with CC into high‐ and low‐risk groups.
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spelling pubmed-74633062020-09-08 HPV‐related methylation‐based reclassification and risk stratification of cervical cancer Yang, Si Wu, Ying Wang, Shuqian Xu, Peng Deng, Yujiao Wang, Meng Liu, Kang Tian, Tian Zhu, Yuyao Li, Na Zhou, Linghui Dai, Zhijun Kang, Huafeng Mol Oncol Research Articles Human papillomavirus (HPV) is a clear etiology of cervical cancer (CC). However, the associations between HPV infection and DNA methylation have not been thoroughly investigated. Additionally, it remains unknown whether HPV‐related methylation signatures can identify subtypes of CC and stratify the prognosis of CC patients. DNA methylation profiles were obtained from The Cancer Genome Atlas to identify HPV‐related methylation sites. Unsupervised clustering analysis of HPV‐related methylation sites was performed to determine the different CC subtypes. CC patients were categorized into cluster 1 (Methylation‐H), cluster 2 (Methylation‐M), and cluster 3 (Methylation‐L). Compared to Methylation‐M and Methylation‐L, Methylation‐H exhibited a significantly improved overall survival (OS). Gene set enrichment analysis (GSEA) was conducted to investigate the functions that correlated with different CC subtypes. GSEA indicated that the hallmarks of tumors, including KRAS signaling, TNFα signaling via NF‐κB, inflammatory response, epithelial–mesenchymal transition, and interferon‐gamma response, were enriched in Methylation‐M and Methylation‐L. Based on mutation and copy number variation analyses, we found that aberrant mutations, amplifications, and deletions among the MYC, Notch, PI3K‐AKT, and RTK‐RAS pathways were most frequently detected in Methylation‐H. Additionally, mutations, amplifications, and deletions within the Hippo, PI3K‐AKT, and TGF‐β pathways were presented in Methylation‐M. Genes within the cell cycle, Notch, and Hippo pathways possessed aberrant mutations, amplifications, and deletions in Methylation‐L. Moreover, the analysis of tumor microenvironments revealed that Methylation‐H was characterized by a relatively low degree of immune cell infiltration. Finally, a prognostic signature based on six HPV‐related methylation sites was developed and validated. Our study revealed that CC patients could be classified into three heterogeneous clusters based on HPV‐related methylation signatures. Additionally, we derived a prognostic signature using six HPV‐related methylation sites that stratified the OS of patients with CC into high‐ and low‐risk groups. John Wiley and Sons Inc. 2020-06-02 2020-09 /pmc/articles/PMC7463306/ /pubmed/32408396 http://dx.doi.org/10.1002/1878-0261.12709 Text en © 2020 The Authors. Published by FEBS Press and John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Yang, Si
Wu, Ying
Wang, Shuqian
Xu, Peng
Deng, Yujiao
Wang, Meng
Liu, Kang
Tian, Tian
Zhu, Yuyao
Li, Na
Zhou, Linghui
Dai, Zhijun
Kang, Huafeng
HPV‐related methylation‐based reclassification and risk stratification of cervical cancer
title HPV‐related methylation‐based reclassification and risk stratification of cervical cancer
title_full HPV‐related methylation‐based reclassification and risk stratification of cervical cancer
title_fullStr HPV‐related methylation‐based reclassification and risk stratification of cervical cancer
title_full_unstemmed HPV‐related methylation‐based reclassification and risk stratification of cervical cancer
title_short HPV‐related methylation‐based reclassification and risk stratification of cervical cancer
title_sort hpv‐related methylation‐based reclassification and risk stratification of cervical cancer
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7463306/
https://www.ncbi.nlm.nih.gov/pubmed/32408396
http://dx.doi.org/10.1002/1878-0261.12709
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