Mechanism-anchored profiling derived from epigenetic networks predicts outcome in acute lymphoblastic leukemia

Abstract

Background: Current outcome predictors based on "molecular profiling" rely on gene lists selected without consideration for their molecular mechanisms. This study was designed to demonstrate that we could learn about genes related to a specific mechanism and further use this knowledge to predict outcome in patients -a paradigm shift towards accurate "mechanismanchored profiling". We propose a novel algorithm, PGnet, which predicts a tripartite mechanismanchored network associated to epigenetic regulation consisting of phenotypes, genes and mechanisms. Genes termed as GEMs in this network meet all of the following criteria: (i) they are co-expressed with genes known to be involved in the biological mechanism of interest, (ii) they are also differentially expressed between distinct phenotypes relevant to the study, and (iii) as a biomodule, genes correlate with both the mechanism and the phenotype.

research paper: Differential expression of HDAC3, HDAC7 and HDAC9 is associated with prognosis and survival in childhood acute lymphoblastic leukaemia

“…The data regarding status of the disease were not available in this dataset. Similarly, Yang et al (2009) analysed another published childhood ALL dataset (Ross et al , 2003) by a novel algorithm that predicts a tripartite mechanism‐anchored network associated with epigenetic regulation, and found upregulation of HDAC4 and downregulation of HDAC5 in T‐ALL. Similar to our findings, these authors also found a significant association between up‐regulation of HDAC9 and relapse (Yang et al , 2009).…”

“…Similarly, Yang et al (2009) analysed another published childhood ALL dataset (Ross et al , 2003) by a novel algorithm that predicts a tripartite mechanism‐anchored network associated with epigenetic regulation, and found upregulation of HDAC4 and downregulation of HDAC5 in T‐ALL. Similar to our findings, these authors also found a significant association between up‐regulation of HDAC9 and relapse (Yang et al , 2009). Although the microarray and RQ‐PCR data were not exactly comparable, these results of microarray gene analysis were similar to those obtained in our study, reinforcing the participation of the HDAC genes in childhood ALL.…”

Connecting the dots in translational bioinformatics: TBC 2014 collection

“…While therapy-related, secondary acute myeloid leukemia (t-AML) has been suggested to be related to the suppression of a histone methyltransferase, EZH2, the critical target genes of EZH2 and their regulatory roles are largely unknown. Yang et al developed the 'seq2gene' algorithm to explore target genes of immuneprecipitation sequencing (ChIP-seq) enriched regions and then extracted regulatory 'biomodules' enriched with genes with similar expression profile and genomic or functional characteristics by combining the seq2gene algorithm with Phenotype-Genotype-Network (PGnet) algorithm [ 9 ]. This preliminary analysis suggested SEMA3A (Semaphoring 3A) as a novel oncogenic candidate that is regulated by EZH2 silencing and warranted further study.…”

Selected proceedings of the 2009 Summit on Translational Bioinformatics

“…Dean et al demonstrated how evolutionary conserved binding sites of transcriptional factors used jointly with expression profiling can be used to subsequently construct cis-regulatory expression modules in osteocytes [ 6 ]. Yang and Lussier propose a novel and robust algorithm to identify epigenetic regulation derived from co-expression networks and epigenetic targets in the literature, with a specific evaluation in terms of significance and accuracy in the context of Acute Lymphobalstic Leukemia [ 7 ].…”