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J Transl Med. 2015 Sep 17;13:306. doi: 10.1186/s12967-015-0667-x.

Genomic profiling of a Hepatocyte growth factor-dependent signature for MET-targeted therapy in glioblastoma.

Author information

1
Molecular Oncogenesis and Targeted Therapy, Laboratory of Molecular Oncology, Van Andel Research Institute, 333 Bostwick AVE NE, Grand Rapids, MI, 49503, USA. jennifer.johnson@vai.org.
2
Laboratory of Molecular Oncology, Van Andel Research Institute, Grand Rapids, MI, USA. jennifer.johnson@vai.org.
3
Department of Transfusion Medicine, Infectious Disease and Immunogenetics Section, Clinical Center, Trans-National Institutes of Health Center for Human Immunology, National Institutes of Health, Bethesda, MD, USA. asciertoml@jhu.edu.
4
Department of Oncology, Johns Hopkins University, Baltimore, MD, USA. asciertoml@jhu.edu.
5
Departments of Neurosurgery and Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA. smittal@med.wayne.edu.
6
Vertex Pharmaceutical Inc., Boston, MA, USA. david_newsone@vrtx.com.
7
Molecular Oncogenesis and Targeted Therapy, Laboratory of Molecular Oncology, Van Andel Research Institute, 333 Bostwick AVE NE, Grand Rapids, MI, 49503, USA. liang.kang@vai.org.
8
Laboratory of Molecular Oncology, Van Andel Research Institute, Grand Rapids, MI, USA. liang.kang@vai.org.
9
Woodland Pharmaceuticals, Shrewsbury, MA, USA. mbriggs@woodlandpharma.com.
10
Vertex Pharmaceutical Inc., Boston, MA, USA. kirk_tanner@vrtx.com.
11
Department of Transfusion Medicine, Infectious Disease and Immunogenetics Section, Clinical Center, Trans-National Institutes of Health Center for Human Immunology, National Institutes of Health, Bethesda, MD, USA. fmarincola@sidra.org.
12
Research Branch, Sidra Medical and Research Center, Doha, Qatar. fmarincola@sidra.org.
13
Translational Genomics Research Institute, Phoenix, AZ, USA. mberens@tgen.org.
14
Laboratory of Molecular Oncology, Van Andel Research Institute, Grand Rapids, MI, USA. george.vandewoude@vai.org.
15
Molecular Oncogenesis and Targeted Therapy, Laboratory of Molecular Oncology, Van Andel Research Institute, 333 Bostwick AVE NE, Grand Rapids, MI, 49503, USA. qian.xie@vai.org.

Abstract

BACKGROUND:

Constitutive MET signaling promotes invasiveness in most primary and recurrent GBM. However, deployment of available MET-targeting agents is confounded by lack of effective biomarkers for selecting suitable patients for treatment. Because endogenous HGF overexpression often causes autocrine MET activation, and also indicates sensitivity to MET inhibitors, we investigated whether it drives the expression of distinct genes which could serve as a signature indicating vulnerability to MET-targeted therapy in GBM.

METHODS:

Interrogation of genomic data from TCGA GBM (Student's t test, GBM patients with high and low HGF expression, p ≤ 0.00001) referenced against patient-derived xenograft (PDX) models (Student's t test, sensitive vs. insensitive models, p ≤ 0.005) was used to identify the HGF-dependent signature. Genomic analysis of GBM xenograft models using both human and mouse gene expression microarrays (Student's t test, treated vs. vehicle tumors, p ≤ 0.01) were performed to elucidate the tumor and microenvironment cross talk. A PDX model with EGFR(amp) was tested for MET activation as a mechanism of erlotinib resistance.

RESULTS:

We identified a group of 20 genes highly associated with HGF overexpression in GBM and were up- or down-regulated only in tumors sensitive to MET inhibitor. The MET inhibitors regulate tumor (human) and host (mouse) cells within the tumor via distinct molecular processes, but overall impede tumor growth by inhibiting cell cycle progression. EGFR (amp) tumors undergo erlotinib resistance responded to a combination of MET and EGFR inhibitors.

CONCLUSIONS:

Combining TCGA primary tumor datasets (human) and xenograft tumor model datasets (human tumor grown in mice) using therapeutic efficacy as an endpoint may serve as a useful approach to discover and develop molecular signatures as therapeutic biomarkers for targeted therapy. The HGF dependent signature may serve as a candidate predictive signature for patient enrollment in clinical trials using MET inhibitors. Human and mouse microarrays maybe used to dissect the tumor-host interactions. Targeting MET in EGFR (amp) GBM may delay the acquired resistance developed during treatment with erlotinib.

PMID:
26381735
PMCID:
PMC4574608
DOI:
10.1186/s12967-015-0667-x
[Indexed for MEDLINE]
Free PMC Article

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