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The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma
BACKGROUND: Feed-forward loops (FFLs), consisting of miRNAs, transcription factors (TFs) and their common target genes, have been validated to be important for the initialization and development of complex diseases, including cancer. Esophageal Carcinoma (ESCA) and Stomach Adenocarcinoma (STAD) are...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6936086/ https://www.ncbi.nlm.nih.gov/pubmed/31888440 http://dx.doi.org/10.1186/s12859-019-3230-6 |
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author | Qin, Guimin Yang, Luqiong Ma, Yuying Liu, Jiayan Huo, Qiuyan |
author_facet | Qin, Guimin Yang, Luqiong Ma, Yuying Liu, Jiayan Huo, Qiuyan |
author_sort | Qin, Guimin |
collection | PubMed |
description | BACKGROUND: Feed-forward loops (FFLs), consisting of miRNAs, transcription factors (TFs) and their common target genes, have been validated to be important for the initialization and development of complex diseases, including cancer. Esophageal Carcinoma (ESCA) and Stomach Adenocarcinoma (STAD) are two types of malignant tumors in the digestive tract. Understanding common and distinct molecular mechanisms of ESCA and STAD is extremely crucial. RESULTS: In this paper, we presented a computational framework to explore common and distinct FFLs, and molecular biomarkers for ESCA and STAD. We identified FFLs by combining regulation pairs and RNA-seq data. Then we constructed disease-specific co-expression networks based on the FFLs identified. We also used random walk with restart (RWR) on disease-specific co-expression networks to prioritize candidate molecules. We identified 148 and 242 FFLs for these two types of cancer, respectively. And we found that one TF, E2F3 was related to ESCA, two genes, DTNA and KCNMA1 were related to STAD, while one TF ESR1 and one gene KIT were associated with both of the two types of cancer. CONCLUSIONS: This proposed computational framework predicted disease-related biomolecules effectively and discovered the correlation between two types of cancers, which helped develop the diagnostic and therapeutic strategies of Esophageal Carcinoma and Stomach Adenocarcinoma. |
format | Online Article Text |
id | pubmed-6936086 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-69360862019-12-31 The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma Qin, Guimin Yang, Luqiong Ma, Yuying Liu, Jiayan Huo, Qiuyan BMC Bioinformatics Research BACKGROUND: Feed-forward loops (FFLs), consisting of miRNAs, transcription factors (TFs) and their common target genes, have been validated to be important for the initialization and development of complex diseases, including cancer. Esophageal Carcinoma (ESCA) and Stomach Adenocarcinoma (STAD) are two types of malignant tumors in the digestive tract. Understanding common and distinct molecular mechanisms of ESCA and STAD is extremely crucial. RESULTS: In this paper, we presented a computational framework to explore common and distinct FFLs, and molecular biomarkers for ESCA and STAD. We identified FFLs by combining regulation pairs and RNA-seq data. Then we constructed disease-specific co-expression networks based on the FFLs identified. We also used random walk with restart (RWR) on disease-specific co-expression networks to prioritize candidate molecules. We identified 148 and 242 FFLs for these two types of cancer, respectively. And we found that one TF, E2F3 was related to ESCA, two genes, DTNA and KCNMA1 were related to STAD, while one TF ESR1 and one gene KIT were associated with both of the two types of cancer. CONCLUSIONS: This proposed computational framework predicted disease-related biomolecules effectively and discovered the correlation between two types of cancers, which helped develop the diagnostic and therapeutic strategies of Esophageal Carcinoma and Stomach Adenocarcinoma. BioMed Central 2019-12-30 /pmc/articles/PMC6936086/ /pubmed/31888440 http://dx.doi.org/10.1186/s12859-019-3230-6 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Qin, Guimin Yang, Luqiong Ma, Yuying Liu, Jiayan Huo, Qiuyan The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma |
title | The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma |
title_full | The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma |
title_fullStr | The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma |
title_full_unstemmed | The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma |
title_short | The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma |
title_sort | exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6936086/ https://www.ncbi.nlm.nih.gov/pubmed/31888440 http://dx.doi.org/10.1186/s12859-019-3230-6 |
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