Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/91101
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Type: | Journal article |
Title: | Prediction of potential cancer-risk regions based on transcriptome data: towards a comprehensive view |
Author: | Alisoltani, A. Fallahi, H. Ebrahimi, M. Ebrahimi, M. Ebrahimie, E. |
Citation: | PLoS One, 2014; 9(5):e96320-1-e96320-13 |
Publisher: | Public Library of Science |
Issue Date: | 2014 |
ISSN: | 1932-6203 1932-6203 |
Editor: | Coleman, W. |
Statement of Responsibility: | Arghavan Alisoltani, Hossein Fallahi, Mahdi Ebrahimi, Mansour Ebrahimi, Esmaeil Ebrahimie |
Abstract: | A novel integrative pipeline is presented for discovery of potential cancer-susceptibility regions (PCSRs) by calculating the number of altered genes at each chromosomal region, using expression microarray datasets of different human cancers (HCs). Our novel approach comprises primarily predicting PCSRs followed by identification of key genes in these regions to obtain potential regions harboring new cancer-associated variants. In addition to finding new cancer causal variants, another advantage in prediction of such risk regions is simultaneous study of different types of genomic variants in line with focusing on specific chromosomal regions. Using this pipeline we extracted numbers of regions with highly altered expression levels in cancer condition. Regulatory networks were also constructed for different types of cancers following the identification of altered mRNA and microRNAs. Interestingly, results showed that GAPDH, LIFR, ZEB2, mir-21, mir-30a, mir-141 and mir-200c, all located at PCSRs, are common altered factors in constructed networks. We found a number of clusters of altered mRNAs and miRNAs on predicted PCSRs (e.g.12p13.31) and their common regulators including KLF4 and SOX10. Large scale prediction of risk regions based on transcriptome data can open a window in comprehensive study of cancer risk factors and the other human diseases. |
Keywords: | Chromosomes, Human Humans Neoplasms Genetic Predisposition to Disease MicroRNAs Risk Factors Gene Expression Profiling Gene Regulatory Networks Promoter Regions, Genetic Kruppel-Like Factor 4 |
Rights: | © 2014 Alisoltani et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
DOI: | 10.1371/journal.pone.0096320 |
Published version: | http://www.ncbi.nlm.nih.gov/pubmed/24796549 |
Appears in Collections: | Aurora harvest 2 Genetics publications |
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hdl_91101.pdf | Published version | 745.64 kB | Adobe PDF | View/Open |
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