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Ras-driven Transcriptome Analysis Identifies Aurora Kinase A As a Potential Malignant Peripheral Nerve Sheath Tumor Therapeutic Target

Overview
Journal Clin Cancer Res
Specialty Oncology
Date 2012 Jul 20
PMID 22811580
Citations 36
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Abstract

Purpose: Patients with neurofibromatosis type 1 (NF1) develop malignant peripheral nerve sheath tumors (MPNST), which are often inoperable and do not respond well to current chemotherapies or radiation. The goal of this study was to use comprehensive gene expression analysis to identify novel therapeutic targets.

Experimental Design: Nerve Schwann cells and/or their precursors are the tumorigenic cell types in MPNST because of the loss of the NF1 gene, which encodes the RasGAP protein neurofibromin. Therefore, we created a transgenic mouse model, CNP-HRas12V, expressing constitutively active HRas in Schwann cells and defined a Ras-induced gene expression signature to drive a Bayesian factor regression model analysis of differentially expressed genes in mouse and human neurofibromas and MPNSTs. We tested functional significance of Aurora kinase overexpression in MPNST in vitro and in vivo using Aurora kinase short hairpin RNAs (shRNA) and compounds that inhibit Aurora kinase.

Results: We identified 2,000 genes with probability of linkage to nerve Ras signaling of which 339 were significantly differentially expressed in mouse and human NF1-related tumor samples relative to normal nerves, including Aurora kinase A (AURKA). AURKA was dramatically overexpressed and genomically amplified in MPNSTs but not neurofibromas. Aurora kinase shRNAs and Aurora kinase inhibitors blocked MPNST cell growth in vitro. Furthermore, an AURKA selective inhibitor, MLN8237, stabilized tumor volume and significantly increased survival of mice with MPNST xenografts.

Conclusion: Integrative cross-species transcriptome analyses combined with preclinical testing has provided an effective method for identifying candidates for molecular-targeted therapeutics. Blocking Aurora kinases may be a viable treatment platform for MPNST.

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