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Copyright ©The Author(s) 2016. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jan 14, 2016; 22(2): 534-545
Published online Jan 14, 2016. doi: 10.3748/wjg.v22.i2.534
Integration of genome scale data for identifying new players in colorectal cancer
Viktorija Sokolova, Elisabetta Crippa, Manuela Gariboldi
Viktorija Sokolova, Elisabetta Crippa, Manuela Gariboldi, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milano, Italy
Viktorija Sokolova, Elisabetta Crippa, Manuela Gariboldi, Molecular Genetics of Cancer, Fondazione Istituto FIRC di Oncologia Molecolare, 20139 Milano, Italy
Author contributions: Sokolova V and Gariboldi M wrote the manuscript; Crippa E contributed to writing the manuscript and collected the bibliography.
Supported by Associazione Italiana per la Ricerca sul Cancro, Grants No. 10529 and No. 12162; and by funds obtained through an Italian law that allows taxpayers to allocate 0.5% share of their income tax contribution to a research institution of their choice.
Conflict-of-interest statement: No potential conflicts of interest.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Manuela Gariboldi, PhD, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, via G. Venezian 1, 20133 Milan, Italy. manuela.gariboldi@istitutotumori.mi.it
Telephone: +39-2-23902042 Fax: +39-2-23903141
Received: June 22, 2015
Peer-review started: June 26, 2015
First decision: September 11, 2015
Revised: October 13, 2015
Accepted: November 9, 2015
Article in press: November 9, 2015
Published online: January 14, 2016
Processing time: 197 Days and 17.7 Hours
Abstract

Colorectal cancers (CRCs) display a wide variety of genomic aberrations that may be either causally linked to their development and progression, or might serve as biomarkers for their presence. Recent advances in rapid high-throughput genetic and genomic analysis have helped to identify a plethora of alterations that can potentially serve as new cancer biomarkers, and thus help to improve CRC diagnosis, prognosis, and treatment. Each distinct data type (copy number variations, gene and microRNAs expression, CpG island methylation) provides an investigator with a different, partially independent, and complementary view of the entire genome. However, elucidation of gene function will require more information than can be provided by analyzing a single type of data. The integration of knowledge obtained from different sources is becoming increasingly essential for obtaining an interdisciplinary view of large amounts of information, and also for cross-validating experimental results. The integration of numerous types of genetic and genomic data derived from public sources, and via the use of ad-hoc bioinformatics tools and statistical methods facilitates the discovery and validation of novel, informative biomarkers. This combinatory approach will also enable researchers to more accurately and comprehensively understand the associations between different biologic pathways, mechanisms, and phenomena, and gain new insights into the etiology of CRC.

Keywords: Colorectal cancer; Copy number variations; Gene expression; miRNA expression; Methylome; Data integration

Core tip: The development of colorectal cancer (CRC) is driven by the accumulation of various genetic and epigenetic alterations, which have been only partially identified. The increasing financial affordability of high-throughput genome-wide assays has enabled the comprehensive analysis of genomic, transcriptomic, and epigenetic data obtained by analyzing the same biologic samples, and thereby facilitated the identification of new molecular players in CRC. An integrative approach that considers all of these multiple factors provides for better results when seeking to identify genes or microRNAs related to new interactions or biomarkers that might improve CRC diagnosis, prognosis, and treatment.