Table of Contents Author Guidelines Submit a Manuscript
BioMed Research International
Volume 2014, Article ID 278748, 7 pages
http://dx.doi.org/10.1155/2014/278748
Research Article

Integrated Analysis of Gene Network in Childhood Leukemia from Microarray and Pathway Databases

1Centre for Advanced Computational Solutions (CfACS), Lincoln University, Lincoln 7647, New Zealand
2Division of Science and Math, New York University Abu Dhabi and Center for Genomics and Systems Biology (CGSB), New York University Abu Dhabi Institute, P.O. Box 129188, Abu Dhabi, UAE
3Integrated Systems Modelling Group, Lincoln University, Lincoln 7647, New Zealand
4Department of Wine, Food & Molecular Biosciences, Lincoln University, Lincoln 7647, New Zealand

Received 22 November 2013; Revised 24 February 2014; Accepted 3 March 2014; Published 15 April 2014

Academic Editor: Shigehiko Kanaya

Copyright © 2014 Amphun Chaiboonchoe et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Glucocorticoids (GCs) have been used as therapeutic agents for children with acute lymphoblastic leukaemia (ALL) for over 50 years. However, much remains to be understood about the molecular mechanism of GCs actions in ALL subtypes. In this study, we delineate differential responses of ALL subtypes, B- and T-ALL, to GCs treatment at systems level by identifying the differences among biological processes, molecular pathways, and interaction networks that emerge from the action of GCs through the use of a selected number of available bioinformatics methods and tools. We provide biological insight into GC-regulated genes, their related functions, and their networks specific to the ALL subtypes. We show that differentially expressed GC-regulated genes participate in distinct underlying biological processes affected by GCs in B-ALL and T-ALL with little to no overlap. These findings provide the opportunity towards identifying new therapeutic targets.