Abstract 5663: Confirmation of peroxiredoxin II as a driver gene for doxorubicin sensitivity identified from drug-induced expression profiling of the NCI-60 cell lines using Reverse Engineering (REFS) network models

Abstract

Abstract Analysis of expression profiling data from the NCI-60 cell line panel, designed to detect transcripts whose expression levels change in response to doxorubicin (Dox) treatment (100nM and 1000nM) for 2, 6 and 24 h, identified peroxiredoxin II (PRDX2) as a modulator of Dox sensitivity. The antitumor activity of Dox is pleiotropic but has been attributed in part to generation of reactive oxygen species which may also be an important factor in myocardial toxicity. Variation in the gene expression data produced by the increasing Dox concentrations together with the variation in response to Dox across the NCI-60 panel was used to construct causal gene expression network models of the mechanism of efficacy of Dox using the REFS™ platform from GNS Healthcare. REFS™ is a scalable, super computer-enabled framework for discovering causal network models directly from experimental data that requires highly optimized machine-learning algorithms run on massively parallel cloud-based supercomputers. REFS™ extracts information in two steps; Reverse Engineering to identify causal relationships followed by Forward Simulation to simulate interventions in silico. In this case, network models were used to simulate the predicted effect of a gene knockdown for each transcript in the NCI-60 cell lines on Dox sensitivity. PRDX2, which encodes for peroxiredoxin 2, an antioxidant enzyme that reduces hydrogen peroxide and has been demonstrated to have a role in protecting against reactive oxygen damage, was identified as a causal driver gene responsible for Dox sensitivity in the renal cell line, ACHN. Validation of the in silico predictions required RNAi to knock down PRDX2 gene expression (75 - 90% inhibition of expression) with 2 siRNA's in the ACHN and HCT-116 cell lines. Replicate experiments (n=3) demonstrated a significant (p<0.01) increase in sensitivity to Dox in both cell lines after PRDX2 knockdown. Additional cell lines were selected and preliminary data indicated that p53WT (n=4), and not p53mutant (n=7) cells (p=0.005) were susceptible to increased Dox sensitivity in response to RNAi of PRDX2 expression, consistent with these p53WT lines being amongst the most responsive to Dox. However, the relationship between PRDX2 knockdown and altered sensitivity was not correlated with the level of Dox-induced increase in PRDX2 expression, which was up-regulated after 24 h treatment to levels that were comparable in p53WT and several of the p53mutant cell lines. Our data indicates that REFS™ can predict genes that may be important modulators of doxorubicin sensitivity. Funded by NCI Contract No. HHSN261200800001E. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5663. doi:1538-7445.AM2012-5663