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Integrative analysis of DNA methylation and gene expression profiles identified potential breast cancer-specific diagnostic markers

Breast cancer is a common malignant tumor among women whose prognosis is largely determined by the period and accuracy of diagnosis. We here propose to identify a robust DNA methylation-based breast cancer-specific diagnostic signature. Genome-wide DNA methylation and gene expression profiles of bre...

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Autores principales: Liu, Xinhua, Peng, Yonglin, Wang, Ju
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7263199/
https://www.ncbi.nlm.nih.gov/pubmed/32412047
http://dx.doi.org/10.1042/BSR20201053
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author Liu, Xinhua
Peng, Yonglin
Wang, Ju
author_facet Liu, Xinhua
Peng, Yonglin
Wang, Ju
author_sort Liu, Xinhua
collection PubMed
description Breast cancer is a common malignant tumor among women whose prognosis is largely determined by the period and accuracy of diagnosis. We here propose to identify a robust DNA methylation-based breast cancer-specific diagnostic signature. Genome-wide DNA methylation and gene expression profiles of breast cancer patients along with their adjacent normal tissues from the Cancer Genome Atlas (TCGA) were obtained as the training set. CpGs that with significantly elevated methylation level in breast cancer than not only their adjacent normal tissues and the other ten common cancers from TCGA but also the healthy breast tissues from the Gene Expression Omnibus (GEO) were finally remained for logistic regression analysis. Another independent breast cancer DNA methylation dataset from GEO was used as the testing set. Lots of CpGs were hyper-methylated in breast cancer samples compared with adjacent normal tissues, which tend to be negatively correlated with gene expressions. Eight CpGs located at RIIAD1, ENPP2, ESPN, and ETS1, were finally retained. The diagnostic model was reliable in separating BRCA from normal samples. Besides, chromatin accessibility status of RIIAD1, ENPP2, ESPN and ETS1 showed great differences between MCF-7 and MDA-MB-231 cell lines. In conclusion, the present study should be helpful for breast cancer early and accurate diagnosis.
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spelling pubmed-72631992020-06-10 Integrative analysis of DNA methylation and gene expression profiles identified potential breast cancer-specific diagnostic markers Liu, Xinhua Peng, Yonglin Wang, Ju Biosci Rep Bioinformatics Breast cancer is a common malignant tumor among women whose prognosis is largely determined by the period and accuracy of diagnosis. We here propose to identify a robust DNA methylation-based breast cancer-specific diagnostic signature. Genome-wide DNA methylation and gene expression profiles of breast cancer patients along with their adjacent normal tissues from the Cancer Genome Atlas (TCGA) were obtained as the training set. CpGs that with significantly elevated methylation level in breast cancer than not only their adjacent normal tissues and the other ten common cancers from TCGA but also the healthy breast tissues from the Gene Expression Omnibus (GEO) were finally remained for logistic regression analysis. Another independent breast cancer DNA methylation dataset from GEO was used as the testing set. Lots of CpGs were hyper-methylated in breast cancer samples compared with adjacent normal tissues, which tend to be negatively correlated with gene expressions. Eight CpGs located at RIIAD1, ENPP2, ESPN, and ETS1, were finally retained. The diagnostic model was reliable in separating BRCA from normal samples. Besides, chromatin accessibility status of RIIAD1, ENPP2, ESPN and ETS1 showed great differences between MCF-7 and MDA-MB-231 cell lines. In conclusion, the present study should be helpful for breast cancer early and accurate diagnosis. Portland Press Ltd. 2020-05-27 /pmc/articles/PMC7263199/ /pubmed/32412047 http://dx.doi.org/10.1042/BSR20201053 Text en © 2020 The Author(s). https://creativecommons.org/licenses/by/4.0/ This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).
spellingShingle Bioinformatics
Liu, Xinhua
Peng, Yonglin
Wang, Ju
Integrative analysis of DNA methylation and gene expression profiles identified potential breast cancer-specific diagnostic markers
title Integrative analysis of DNA methylation and gene expression profiles identified potential breast cancer-specific diagnostic markers
title_full Integrative analysis of DNA methylation and gene expression profiles identified potential breast cancer-specific diagnostic markers
title_fullStr Integrative analysis of DNA methylation and gene expression profiles identified potential breast cancer-specific diagnostic markers
title_full_unstemmed Integrative analysis of DNA methylation and gene expression profiles identified potential breast cancer-specific diagnostic markers
title_short Integrative analysis of DNA methylation and gene expression profiles identified potential breast cancer-specific diagnostic markers
title_sort integrative analysis of dna methylation and gene expression profiles identified potential breast cancer-specific diagnostic markers
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7263199/
https://www.ncbi.nlm.nih.gov/pubmed/32412047
http://dx.doi.org/10.1042/BSR20201053
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