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A network biology approach evaluating the anticancer effects of bortezomib identifies SPARC as a therapeutic target in adult T-cell leukemia cells

Authors Junko H Ohyashiki, Ryoko Hamamura, Chiaki Kobayashi, Yu Zhang, Kazuma Ohyashiki

Published Date October 2008 Volume 2008:1 Pages 85—98

DOI http://dx.doi.org/10.2147/AABC.S4133

Published 30 October 2008

Junko H Ohyashiki1, Ryoko Hamamura2, Chiaki Kobayashi2, Yu Zhang2, Kazuma Ohyashiki2

1Intractable Immune System Disease Research Center, Tokyo Medical University, Tokyo, Japan; 2First Department of Internal Medicine, Tokyo Medical University, Tokyo, Japan

Abstract: There is a need to identify the regulatory gene interaction of anticancer drugs on target cancer cells. Whole genome expression profiling offers promise in this regard, but can be complicated by the challenge of identifying the genes affected by hundreds to thousands of genes that induce changes in expression. A proteasome inhibitor, bortezomib, could be a potential therapeutic agent in treating adult T-cell leukemia (ATL) patients, however, the underlying mechanism by which bortezomib induces cell death in ATL cells via gene regulatory network has not been fully elucidated. Here we show that a Bayesian statistical framework by VoyaGene® identified a secreted protein acidic and rich in cysteine (SPARC) gene, a tumor-invasiveness related gene, as a possible modulator of bortezomib-induced cell death in ATL cells. Functional analysis using RNAi experiments revealed that inhibition of the expression SPARC by siRNA enhanced the apoptotic effect of bortezomib on ATL cells in accordance with an increase of cleaved caspase 3. Targeting SPARC may help to treat ATL patients in combination with bortezomib. This work shows that a network biology approach can be used advantageously to identify the genetic interaction related to anticancer effects.

Keywords: network biology, adult T cell leukemia, bortezomib, SPARC

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Downregulated microRNA-148b in circulating PBMCs in chronic myeloid leukemia patients with undetectable minimal residual disease: a possible biomarker to discontinue imatinib safely

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