Please use this identifier to cite or link to this item: http://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
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
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.
RMID: 0030008787
DOI: 10.1371/journal.pone.0096320
Published version: http://www.ncbi.nlm.nih.gov/pubmed/24796549
Appears in Collections:Genetics publications

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