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Prognostic Value of a Three-DNA Methylation Biomarker in Patients with Soft Tissue Sarcoma
Soft tissue sarcomas (STS) are a highly aggressive and heterogeneous group of malignant mesenchymal tumors. The prognosis of patients with advanced or metastatic STS remains poor, and the main therapy of STS patients combines primary surgery, radiotherapy, and chemotherapy. Aberrant DNA methylation...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7245661/ https://www.ncbi.nlm.nih.gov/pubmed/32508922 http://dx.doi.org/10.1155/2020/8106212 |
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author | Chen, Yuxiao Zhu, Rui Chen, Min Guo, Wenna Yang, Xin Xu, Xin-Jian Zhu, Liucun |
author_facet | Chen, Yuxiao Zhu, Rui Chen, Min Guo, Wenna Yang, Xin Xu, Xin-Jian Zhu, Liucun |
author_sort | Chen, Yuxiao |
collection | PubMed |
description | Soft tissue sarcomas (STS) are a highly aggressive and heterogeneous group of malignant mesenchymal tumors. The prognosis of patients with advanced or metastatic STS remains poor, and the main therapy of STS patients combines primary surgery, radiotherapy, and chemotherapy. Aberrant DNA methylation shows close association with the pathogenesis and tumor progression. Therefore, DNA methylation biomarkers might have the potential in accurately predicting the survival of STS patients. In order to identify a prognostic biomarker based on DNA methylation sites, a comprehensive analysis of the DNA methylation profile of STS patients in the Cancer Genome Atlas (TCGA) database was performed. All samples were randomly divided into training and testing datasets. Cox proportional hazards regression analysis was performed to identify a prognostic biomarker that contains three DNA methylation sites. The Kaplan–Meier analysis demonstrated that the 3-DNA methylation biomarker discriminated patients into high-risk and low-risk groups, both in the training and in the testing datasets, and the area under the receiver operating characteristic curve values (AUCs) were 0.844 (P < 0.001, 95% CI: 0.740–0.948) and 0.710 (P = 0.002, 95% CI: 0.595–0.823), respectively. Besides, this biomarker presented superior prognostic performance in STS patients with different age, sex, tissue of origin, therapy, and histologic subtypes. Compared with other prognostic biomarkers, this biomarker tended to be a more precise prognostic factor in STS patients. Moreover, methylation sites in this biomarker might provide a new way for clinicians to make decisions regarding the intervention and assess the effectiveness of an individual therapeutic strategy. |
format | Online Article Text |
id | pubmed-7245661 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-72456612020-06-06 Prognostic Value of a Three-DNA Methylation Biomarker in Patients with Soft Tissue Sarcoma Chen, Yuxiao Zhu, Rui Chen, Min Guo, Wenna Yang, Xin Xu, Xin-Jian Zhu, Liucun J Oncol Research Article Soft tissue sarcomas (STS) are a highly aggressive and heterogeneous group of malignant mesenchymal tumors. The prognosis of patients with advanced or metastatic STS remains poor, and the main therapy of STS patients combines primary surgery, radiotherapy, and chemotherapy. Aberrant DNA methylation shows close association with the pathogenesis and tumor progression. Therefore, DNA methylation biomarkers might have the potential in accurately predicting the survival of STS patients. In order to identify a prognostic biomarker based on DNA methylation sites, a comprehensive analysis of the DNA methylation profile of STS patients in the Cancer Genome Atlas (TCGA) database was performed. All samples were randomly divided into training and testing datasets. Cox proportional hazards regression analysis was performed to identify a prognostic biomarker that contains three DNA methylation sites. The Kaplan–Meier analysis demonstrated that the 3-DNA methylation biomarker discriminated patients into high-risk and low-risk groups, both in the training and in the testing datasets, and the area under the receiver operating characteristic curve values (AUCs) were 0.844 (P < 0.001, 95% CI: 0.740–0.948) and 0.710 (P = 0.002, 95% CI: 0.595–0.823), respectively. Besides, this biomarker presented superior prognostic performance in STS patients with different age, sex, tissue of origin, therapy, and histologic subtypes. Compared with other prognostic biomarkers, this biomarker tended to be a more precise prognostic factor in STS patients. Moreover, methylation sites in this biomarker might provide a new way for clinicians to make decisions regarding the intervention and assess the effectiveness of an individual therapeutic strategy. Hindawi 2020-05-15 /pmc/articles/PMC7245661/ /pubmed/32508922 http://dx.doi.org/10.1155/2020/8106212 Text en Copyright © 2020 Yuxiao Chen 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 Chen, Yuxiao Zhu, Rui Chen, Min Guo, Wenna Yang, Xin Xu, Xin-Jian Zhu, Liucun Prognostic Value of a Three-DNA Methylation Biomarker in Patients with Soft Tissue Sarcoma |
title | Prognostic Value of a Three-DNA Methylation Biomarker in Patients with Soft Tissue Sarcoma |
title_full | Prognostic Value of a Three-DNA Methylation Biomarker in Patients with Soft Tissue Sarcoma |
title_fullStr | Prognostic Value of a Three-DNA Methylation Biomarker in Patients with Soft Tissue Sarcoma |
title_full_unstemmed | Prognostic Value of a Three-DNA Methylation Biomarker in Patients with Soft Tissue Sarcoma |
title_short | Prognostic Value of a Three-DNA Methylation Biomarker in Patients with Soft Tissue Sarcoma |
title_sort | prognostic value of a three-dna methylation biomarker in patients with soft tissue sarcoma |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7245661/ https://www.ncbi.nlm.nih.gov/pubmed/32508922 http://dx.doi.org/10.1155/2020/8106212 |
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