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Exploring the importance of cancer pathways by meta-analysis of differential protein expression networks in three different cancers

BACKGROUND: It is believed that all cancers occur due to the mutation or change in one or more genes. In order to investigate the significance of the biological pathways which are interrupted by these genetic mutations, we pursue an integrated analysis using multiple cancer datasets released by the...

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Autores principales: Sikdar, Sinjini, Datta, Somnath, Datta, Susmita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5168844/
https://www.ncbi.nlm.nih.gov/pubmed/27993151
http://dx.doi.org/10.1186/s13062-016-0168-8
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author Sikdar, Sinjini
Datta, Somnath
Datta, Susmita
author_facet Sikdar, Sinjini
Datta, Somnath
Datta, Susmita
author_sort Sikdar, Sinjini
collection PubMed
description BACKGROUND: It is believed that all cancers occur due to the mutation or change in one or more genes. In order to investigate the significance of the biological pathways which are interrupted by these genetic mutations, we pursue an integrated analysis using multiple cancer datasets released by the International Cancer Genome Consortium (ICGC). This dataset consists of expression profiles for genes/proteins of patients receiving treatment, for three types of cancer - Head and Neck Squamous Cell Carcinoma (HNSC), Lung Adenocarcinoma (LUAD) and Kidney Renal Clear Cell Carcinoma (KIRC). We consider pathway analysis to identify all the biological pathways which are active among the patients and investigate the roles of the significant pathways using a differential network analysis of the protein expression datasets for the three cancers separately. We then integrate the pathway based results of all the three cancers which provide a more comprehensive picture of the three cancers. RESULTS: From our analysis of the protein expression data, overall, RAS and PI3K signaling pathways appear to play the most significant roles in the three cancers - Head and Neck Squamous Cell Carcinoma (HNSC), Lung Adenocarcinoma (LUAD) and Kidney Renal Clear Cell Carcinoma (KIRC). CONCLUSION: This analysis suggests that the RAS and PI3K signaling pathways are the two most important pathways in all the three cancers and should be investigated further for their potential roles in cancers. REVIEWERS: This article was reviewed by Joaquin Dopazo and Samiran Ghosh.
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spelling pubmed-51688442016-12-23 Exploring the importance of cancer pathways by meta-analysis of differential protein expression networks in three different cancers Sikdar, Sinjini Datta, Somnath Datta, Susmita Biol Direct Research BACKGROUND: It is believed that all cancers occur due to the mutation or change in one or more genes. In order to investigate the significance of the biological pathways which are interrupted by these genetic mutations, we pursue an integrated analysis using multiple cancer datasets released by the International Cancer Genome Consortium (ICGC). This dataset consists of expression profiles for genes/proteins of patients receiving treatment, for three types of cancer - Head and Neck Squamous Cell Carcinoma (HNSC), Lung Adenocarcinoma (LUAD) and Kidney Renal Clear Cell Carcinoma (KIRC). We consider pathway analysis to identify all the biological pathways which are active among the patients and investigate the roles of the significant pathways using a differential network analysis of the protein expression datasets for the three cancers separately. We then integrate the pathway based results of all the three cancers which provide a more comprehensive picture of the three cancers. RESULTS: From our analysis of the protein expression data, overall, RAS and PI3K signaling pathways appear to play the most significant roles in the three cancers - Head and Neck Squamous Cell Carcinoma (HNSC), Lung Adenocarcinoma (LUAD) and Kidney Renal Clear Cell Carcinoma (KIRC). CONCLUSION: This analysis suggests that the RAS and PI3K signaling pathways are the two most important pathways in all the three cancers and should be investigated further for their potential roles in cancers. REVIEWERS: This article was reviewed by Joaquin Dopazo and Samiran Ghosh. BioMed Central 2016-12-20 /pmc/articles/PMC5168844/ /pubmed/27993151 http://dx.doi.org/10.1186/s13062-016-0168-8 Text en © The Author(s). 2016 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
Sikdar, Sinjini
Datta, Somnath
Datta, Susmita
Exploring the importance of cancer pathways by meta-analysis of differential protein expression networks in three different cancers
title Exploring the importance of cancer pathways by meta-analysis of differential protein expression networks in three different cancers
title_full Exploring the importance of cancer pathways by meta-analysis of differential protein expression networks in three different cancers
title_fullStr Exploring the importance of cancer pathways by meta-analysis of differential protein expression networks in three different cancers
title_full_unstemmed Exploring the importance of cancer pathways by meta-analysis of differential protein expression networks in three different cancers
title_short Exploring the importance of cancer pathways by meta-analysis of differential protein expression networks in three different cancers
title_sort exploring the importance of cancer pathways by meta-analysis of differential protein expression networks in three different cancers
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5168844/
https://www.ncbi.nlm.nih.gov/pubmed/27993151
http://dx.doi.org/10.1186/s13062-016-0168-8
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