An analysis about heterogeneity among cancers based on the DNA methylation patterns
BACKGROUND: It is generally believed that DNA methylation, as one of the most important epigenetic modifications, participates in the regulation of gene expression and plays an important role in the development of cancer, and there exits epigenetic heterogeneity among cancers. Therefore, this study tried to screen for reliable prognostic markers for different cancers, providing further explanation for the heterogeneity of cancers, and more targets for clinical transformation studies of cancer from epigenetic perspective.
METHODS: This article discusses the epigenetic heterogeneity of cancer in detail. Firstly, DNA methylation data of seven cancer types were obtained from Illumina Infinium HumanMethylation 450 K platform of TCGA database. Then, differential methylation analysis was performed in the promotor region. Secondly, pivotal gene markers were obtained by constructing the DNA methylation correlation network and the gene interaction network in the KEGG pathway, and 317 marker genes obtained from two networks were integrated as candidate markers for the prognosis model. Finally, we used the univariate and multivariate COX regression models to select specific independent prognostic markers for each cancer, and studied the risk factor of these genes by doing survival analysis.
RESULTS: First, the cancer type-specific gene markers were obtained by differential methylation analysis and they were found to be involved in different biological functions by enrichment analysis. Moreover, specific and common diagnostic markers for each type of cancer was sorted out and Kaplan-Meier survival analysis showed that there was significant difference in survival between the two risk groups.
CONCLUSIONS: This study screened out reliable prognostic markers for different cancers, providing a further explanation for the heterogeneity of cancer at the DNA methylation level and more targets for clinical conversion studies of cancer.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2019 |
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| Erschienen: |
2019 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:19 |
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| Enthalten in: |
BMC cancer - 19(2019), 1 vom: 30. Dez., Seite 1259 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Liu, Yang [VerfasserIn] |
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| Links: |
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| Themen: |
Biomarkers, Tumor |
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| Anmerkungen: |
Date Completed 05.05.2020 Date Revised 05.05.2020 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1186/s12885-019-6455-x |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM304885487 |
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| 245 | 1 | 3 | |a An analysis about heterogeneity among cancers based on the DNA methylation patterns |
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| 500 | |a Date Completed 05.05.2020 | ||
| 500 | |a Date Revised 05.05.2020 | ||
| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a BACKGROUND: It is generally believed that DNA methylation, as one of the most important epigenetic modifications, participates in the regulation of gene expression and plays an important role in the development of cancer, and there exits epigenetic heterogeneity among cancers. Therefore, this study tried to screen for reliable prognostic markers for different cancers, providing further explanation for the heterogeneity of cancers, and more targets for clinical transformation studies of cancer from epigenetic perspective | ||
| 520 | |a METHODS: This article discusses the epigenetic heterogeneity of cancer in detail. Firstly, DNA methylation data of seven cancer types were obtained from Illumina Infinium HumanMethylation 450 K platform of TCGA database. Then, differential methylation analysis was performed in the promotor region. Secondly, pivotal gene markers were obtained by constructing the DNA methylation correlation network and the gene interaction network in the KEGG pathway, and 317 marker genes obtained from two networks were integrated as candidate markers for the prognosis model. Finally, we used the univariate and multivariate COX regression models to select specific independent prognostic markers for each cancer, and studied the risk factor of these genes by doing survival analysis | ||
| 520 | |a RESULTS: First, the cancer type-specific gene markers were obtained by differential methylation analysis and they were found to be involved in different biological functions by enrichment analysis. Moreover, specific and common diagnostic markers for each type of cancer was sorted out and Kaplan-Meier survival analysis showed that there was significant difference in survival between the two risk groups | ||
| 520 | |a CONCLUSIONS: This study screened out reliable prognostic markers for different cancers, providing a further explanation for the heterogeneity of cancer at the DNA methylation level and more targets for clinical conversion studies of cancer | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Cancer | |
| 650 | 4 | |a DNA methylation | |
| 650 | 4 | |a Epigenetic heterogeneity | |
| 650 | 4 | |a Survival analysis | |
| 650 | 7 | |a Biomarkers, Tumor |2 NLM | |
| 700 | 1 | |a Gu, Yue |e verfasserin |4 aut | |
| 700 | 1 | |a Su, Mu |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Hui |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Shumei |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Yan |e verfasserin |4 aut | |
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