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A polygenic methylation prediction model associated with response to chemotherapy in epithelial ovarian cancer
To identify potential aberrantly differentially methylated genes (DMGs) correlated with chemotherapy response (CR) and establish a polygenic methylation prediction model of CR in epithelial ovarian cancer (EOC), we accessed 177 (47 chemo-sensitive and 130 chemo-resistant) samples corresponding to th...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society of Gene & Cell Therapy
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7943968/ https://www.ncbi.nlm.nih.gov/pubmed/33738340 http://dx.doi.org/10.1016/j.omto.2021.02.012 |
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author | Zhao, Lanbo Ma, Sijia Wang, Linconghua Wang, Yiran Feng, Xue Liang, Dongxin Han, Lu Li, Min Li, Qiling |
author_facet | Zhao, Lanbo Ma, Sijia Wang, Linconghua Wang, Yiran Feng, Xue Liang, Dongxin Han, Lu Li, Min Li, Qiling |
author_sort | Zhao, Lanbo |
collection | PubMed |
description | To identify potential aberrantly differentially methylated genes (DMGs) correlated with chemotherapy response (CR) and establish a polygenic methylation prediction model of CR in epithelial ovarian cancer (EOC), we accessed 177 (47 chemo-sensitive and 130 chemo-resistant) samples corresponding to three DNA-methylation microarray datasets from the Gene Expression Omnibus and 306 (290 chemo-sensitive and 16 chemo-resistant) samples from The Cancer Genome Atlas (TCGA) database. DMGs associated with chemotherapy sensitivity and chemotherapy resistance were identified by several packages of R software. Pathway enrichment and protein-protein interaction (PPI) network analyses were constructed by Metascape software. The key genes containing mRNA expressions associated with methylation levels were validated from the expression dataset by the GEO2R platform. The determination of the prognostic significance of key genes was performed by the Kaplan-Meier plotter database. The key genes-based polygenic methylation prediction model was established by binary logistic regression. Among accessed 483 samples, 457 (182 hypermethylated and 275 hypomethylated) DMGs correlated with chemo resistance. Twenty-nine hub genes were identified and further validated. Three genes, anterior gradient 2 (AGR2), heat shock-related 70-kDa protein 2 (HSPA2), and acetyltransferase 2 (ACAT2), showed a significantly negative correlation between their methylation levels and mRNA expressions, which also corresponded to prognostic significance. A polygenic methylation prediction model (0.5253 cutoff value) was established and validated with 0.659 sensitivity and 0.911 specificity. |
format | Online Article Text |
id | pubmed-7943968 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Society of Gene & Cell Therapy |
record_format | MEDLINE/PubMed |
spelling | pubmed-79439682021-03-17 A polygenic methylation prediction model associated with response to chemotherapy in epithelial ovarian cancer Zhao, Lanbo Ma, Sijia Wang, Linconghua Wang, Yiran Feng, Xue Liang, Dongxin Han, Lu Li, Min Li, Qiling Mol Ther Oncolytics Original Article To identify potential aberrantly differentially methylated genes (DMGs) correlated with chemotherapy response (CR) and establish a polygenic methylation prediction model of CR in epithelial ovarian cancer (EOC), we accessed 177 (47 chemo-sensitive and 130 chemo-resistant) samples corresponding to three DNA-methylation microarray datasets from the Gene Expression Omnibus and 306 (290 chemo-sensitive and 16 chemo-resistant) samples from The Cancer Genome Atlas (TCGA) database. DMGs associated with chemotherapy sensitivity and chemotherapy resistance were identified by several packages of R software. Pathway enrichment and protein-protein interaction (PPI) network analyses were constructed by Metascape software. The key genes containing mRNA expressions associated with methylation levels were validated from the expression dataset by the GEO2R platform. The determination of the prognostic significance of key genes was performed by the Kaplan-Meier plotter database. The key genes-based polygenic methylation prediction model was established by binary logistic regression. Among accessed 483 samples, 457 (182 hypermethylated and 275 hypomethylated) DMGs correlated with chemo resistance. Twenty-nine hub genes were identified and further validated. Three genes, anterior gradient 2 (AGR2), heat shock-related 70-kDa protein 2 (HSPA2), and acetyltransferase 2 (ACAT2), showed a significantly negative correlation between their methylation levels and mRNA expressions, which also corresponded to prognostic significance. A polygenic methylation prediction model (0.5253 cutoff value) was established and validated with 0.659 sensitivity and 0.911 specificity. American Society of Gene & Cell Therapy 2021-02-20 /pmc/articles/PMC7943968/ /pubmed/33738340 http://dx.doi.org/10.1016/j.omto.2021.02.012 Text en © 2021 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Article Zhao, Lanbo Ma, Sijia Wang, Linconghua Wang, Yiran Feng, Xue Liang, Dongxin Han, Lu Li, Min Li, Qiling A polygenic methylation prediction model associated with response to chemotherapy in epithelial ovarian cancer |
title | A polygenic methylation prediction model associated with response to chemotherapy in epithelial ovarian cancer |
title_full | A polygenic methylation prediction model associated with response to chemotherapy in epithelial ovarian cancer |
title_fullStr | A polygenic methylation prediction model associated with response to chemotherapy in epithelial ovarian cancer |
title_full_unstemmed | A polygenic methylation prediction model associated with response to chemotherapy in epithelial ovarian cancer |
title_short | A polygenic methylation prediction model associated with response to chemotherapy in epithelial ovarian cancer |
title_sort | polygenic methylation prediction model associated with response to chemotherapy in epithelial ovarian cancer |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7943968/ https://www.ncbi.nlm.nih.gov/pubmed/33738340 http://dx.doi.org/10.1016/j.omto.2021.02.012 |
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