Cargando…
A 3-DNA methylation signature as a novel prognostic biomarker in patients with sarcoma by bioinformatics analysis
BACKGROUND: Tumor-specific DNA methylation can potentially be a useful indicator in cancer diagnostics and monitoring. Sarcomas comprise a heterogeneous group of mesenchymal neoplasms which cause life-threatening tumors occurring throughout the body. Therefore, potential molecular detection and prog...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8137010/ https://www.ncbi.nlm.nih.gov/pubmed/34011115 http://dx.doi.org/10.1097/MD.0000000000026040 |
_version_ | 1783695538810519552 |
---|---|
author | Wang, Xiao-Wei Sun, Qi Xu, Shi-Bin Xu, Chao Xia, Chen-Jie Zhao, Qi-Ming Zhang, Hua-Hui Tan, Wei-Qiang Zhang, Lei Yao, Shu-Dong |
author_facet | Wang, Xiao-Wei Sun, Qi Xu, Shi-Bin Xu, Chao Xia, Chen-Jie Zhao, Qi-Ming Zhang, Hua-Hui Tan, Wei-Qiang Zhang, Lei Yao, Shu-Dong |
author_sort | Wang, Xiao-Wei |
collection | PubMed |
description | BACKGROUND: Tumor-specific DNA methylation can potentially be a useful indicator in cancer diagnostics and monitoring. Sarcomas comprise a heterogeneous group of mesenchymal neoplasms which cause life-threatening tumors occurring throughout the body. Therefore, potential molecular detection and prognostic evaluation is very important for early diagnosis and treatment. METHODS: We performed a retrospective study analyzing DNA methylation of 261 patients with sarcoma from The Cancer Genome Atlas (TCGA) database. Cox regression analyses were conducted to identify a signature associated with the overall survival (OS) of patients with sarcoma, which was validated in a validation dataset. RESULTS: Three DNA methylation signatures were identified to be significantly associated with OS. Kaplan–Meier analysis showed that the 3-DNA methylation signature could significantly distinguish the high- and low-risk patients in both training (first two-thirds) and validation datasets (remaining one-third). Receiver operating characteristic (ROC) analysis confirmed that the 3-DNA methylation signature exhibited high sensitivity and specificity in predicting OS of patients. Also, the Kaplan–Meier analysis and the area under curve (AUC) values indicated that the 3-DNA methylation signature was independent of clinical characteristics, including age at diagnosis, sex, anatomic location, tumor residual classification, and histological subtypes. CONCLUSIONS: The current study showed that the 3-DNA methylation model could efficiently function as a novel and independent prognostic biomarker and therapeutic target for patients with sarcoma. |
format | Online Article Text |
id | pubmed-8137010 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-81370102021-05-25 A 3-DNA methylation signature as a novel prognostic biomarker in patients with sarcoma by bioinformatics analysis Wang, Xiao-Wei Sun, Qi Xu, Shi-Bin Xu, Chao Xia, Chen-Jie Zhao, Qi-Ming Zhang, Hua-Hui Tan, Wei-Qiang Zhang, Lei Yao, Shu-Dong Medicine (Baltimore) 5700 BACKGROUND: Tumor-specific DNA methylation can potentially be a useful indicator in cancer diagnostics and monitoring. Sarcomas comprise a heterogeneous group of mesenchymal neoplasms which cause life-threatening tumors occurring throughout the body. Therefore, potential molecular detection and prognostic evaluation is very important for early diagnosis and treatment. METHODS: We performed a retrospective study analyzing DNA methylation of 261 patients with sarcoma from The Cancer Genome Atlas (TCGA) database. Cox regression analyses were conducted to identify a signature associated with the overall survival (OS) of patients with sarcoma, which was validated in a validation dataset. RESULTS: Three DNA methylation signatures were identified to be significantly associated with OS. Kaplan–Meier analysis showed that the 3-DNA methylation signature could significantly distinguish the high- and low-risk patients in both training (first two-thirds) and validation datasets (remaining one-third). Receiver operating characteristic (ROC) analysis confirmed that the 3-DNA methylation signature exhibited high sensitivity and specificity in predicting OS of patients. Also, the Kaplan–Meier analysis and the area under curve (AUC) values indicated that the 3-DNA methylation signature was independent of clinical characteristics, including age at diagnosis, sex, anatomic location, tumor residual classification, and histological subtypes. CONCLUSIONS: The current study showed that the 3-DNA methylation model could efficiently function as a novel and independent prognostic biomarker and therapeutic target for patients with sarcoma. Lippincott Williams & Wilkins 2021-05-21 /pmc/articles/PMC8137010/ /pubmed/34011115 http://dx.doi.org/10.1097/MD.0000000000026040 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) |
spellingShingle | 5700 Wang, Xiao-Wei Sun, Qi Xu, Shi-Bin Xu, Chao Xia, Chen-Jie Zhao, Qi-Ming Zhang, Hua-Hui Tan, Wei-Qiang Zhang, Lei Yao, Shu-Dong A 3-DNA methylation signature as a novel prognostic biomarker in patients with sarcoma by bioinformatics analysis |
title | A 3-DNA methylation signature as a novel prognostic biomarker in patients with sarcoma by bioinformatics analysis |
title_full | A 3-DNA methylation signature as a novel prognostic biomarker in patients with sarcoma by bioinformatics analysis |
title_fullStr | A 3-DNA methylation signature as a novel prognostic biomarker in patients with sarcoma by bioinformatics analysis |
title_full_unstemmed | A 3-DNA methylation signature as a novel prognostic biomarker in patients with sarcoma by bioinformatics analysis |
title_short | A 3-DNA methylation signature as a novel prognostic biomarker in patients with sarcoma by bioinformatics analysis |
title_sort | 3-dna methylation signature as a novel prognostic biomarker in patients with sarcoma by bioinformatics analysis |
topic | 5700 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8137010/ https://www.ncbi.nlm.nih.gov/pubmed/34011115 http://dx.doi.org/10.1097/MD.0000000000026040 |
work_keys_str_mv | AT wangxiaowei a3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT sunqi a3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT xushibin a3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT xuchao a3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT xiachenjie a3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT zhaoqiming a3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT zhanghuahui a3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT tanweiqiang a3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT zhanglei a3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT yaoshudong a3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT wangxiaowei 3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT sunqi 3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT xushibin 3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT xuchao 3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT xiachenjie 3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT zhaoqiming 3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT zhanghuahui 3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT tanweiqiang 3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT zhanglei 3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis AT yaoshudong 3dnamethylationsignatureasanovelprognosticbiomarkerinpatientswithsarcomabybioinformaticsanalysis |