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Multi-Omics Data Analysis Identifies Prognostic Biomarkers across Cancers
Combining omics data from different layers using integrative methods provides a better understanding of the biology of a complex disease such as cancer. The discovery of biomarkers related to cancer development or prognosis helps to find more effective treatment options. This study integrates multi-...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10366886/ https://www.ncbi.nlm.nih.gov/pubmed/37489460 http://dx.doi.org/10.3390/medsci11030044 |
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author | Demir Karaman, Ezgi Işık, Zerrin |
author_facet | Demir Karaman, Ezgi Işık, Zerrin |
author_sort | Demir Karaman, Ezgi |
collection | PubMed |
description | Combining omics data from different layers using integrative methods provides a better understanding of the biology of a complex disease such as cancer. The discovery of biomarkers related to cancer development or prognosis helps to find more effective treatment options. This study integrates multi-omics data of different cancer types with a network-based approach to explore common gene modules among different tumors by running community detection methods on the integrated network. The common modules were evaluated by several biological metrics adapted to cancer. Then, a new prognostic scoring method was developed by weighting mRNA expression, methylation, and mutation status of genes. The survival analysis pointed out statistically significant results for GNG11, CBX2, CDKN3, ARHGEF10, CLN8, SEC61G and PTDSS1 genes. The literature search reveals that the identified biomarkers are associated with the same or different types of cancers. Our method does not only identify known cancer-specific biomarker genes, but also proposes new potential biomarkers. Thus, this study provides a rationale for identifying new gene targets and expanding treatment options across cancer types. |
format | Online Article Text |
id | pubmed-10366886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103668862023-07-26 Multi-Omics Data Analysis Identifies Prognostic Biomarkers across Cancers Demir Karaman, Ezgi Işık, Zerrin Med Sci (Basel) Article Combining omics data from different layers using integrative methods provides a better understanding of the biology of a complex disease such as cancer. The discovery of biomarkers related to cancer development or prognosis helps to find more effective treatment options. This study integrates multi-omics data of different cancer types with a network-based approach to explore common gene modules among different tumors by running community detection methods on the integrated network. The common modules were evaluated by several biological metrics adapted to cancer. Then, a new prognostic scoring method was developed by weighting mRNA expression, methylation, and mutation status of genes. The survival analysis pointed out statistically significant results for GNG11, CBX2, CDKN3, ARHGEF10, CLN8, SEC61G and PTDSS1 genes. The literature search reveals that the identified biomarkers are associated with the same or different types of cancers. Our method does not only identify known cancer-specific biomarker genes, but also proposes new potential biomarkers. Thus, this study provides a rationale for identifying new gene targets and expanding treatment options across cancer types. MDPI 2023-06-27 /pmc/articles/PMC10366886/ /pubmed/37489460 http://dx.doi.org/10.3390/medsci11030044 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Demir Karaman, Ezgi Işık, Zerrin Multi-Omics Data Analysis Identifies Prognostic Biomarkers across Cancers |
title | Multi-Omics Data Analysis Identifies Prognostic Biomarkers across Cancers |
title_full | Multi-Omics Data Analysis Identifies Prognostic Biomarkers across Cancers |
title_fullStr | Multi-Omics Data Analysis Identifies Prognostic Biomarkers across Cancers |
title_full_unstemmed | Multi-Omics Data Analysis Identifies Prognostic Biomarkers across Cancers |
title_short | Multi-Omics Data Analysis Identifies Prognostic Biomarkers across Cancers |
title_sort | multi-omics data analysis identifies prognostic biomarkers across cancers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10366886/ https://www.ncbi.nlm.nih.gov/pubmed/37489460 http://dx.doi.org/10.3390/medsci11030044 |
work_keys_str_mv | AT demirkaramanezgi multiomicsdataanalysisidentifiesprognosticbiomarkersacrosscancers AT isıkzerrin multiomicsdataanalysisidentifiesprognosticbiomarkersacrosscancers |