Genetic and Expression Analysis of MET, MACC1, and HGF in Metastatic Colorectal Cancer: Response to Met Inhibition in Patient Xenografts and Pathologic Correlations

Francesco Galimi(Azienda Ospedaliero Universitaria San Giovanni Battista), Davide Torti(Candiolo Cancer Institute), Francesco Sassi(Candiolo Cancer Institute), Claudio Isella(Azienda Ospedaliero Universitaria San Giovanni Battista), Davide Corà(Azienda Ospedaliero Universitaria San Giovanni Battista), Stefania Gastaldi(Candiolo Cancer Institute), Dario Ribero(Azienda Ospedaliero Universitaria San Giovanni Battista), Andrea Muratore(Azienda Ospedaliero Universitaria San Giovanni Battista), Paolo Massucco(Azienda Ospedaliero Universitaria San Giovanni Battista), Dimitrios Siatis(Azienda Ospedaliero Universitaria San Giovanni Battista), Gianluca Paraluppi(Azienda Ospedaliero Universitaria San Giovanni Battista), Federica Gonella(Azienda Ospedaliero Universitaria San Giovanni Battista), Francesca Maione(Azienda Ospedaliero Universitaria San Giovanni Battista), Alberto Pisacane(Azienda Ospedaliero Universitaria San Giovanni Battista), Ezio David(Azienda Ospedaliero Universitaria San Giovanni Battista), Bruno Torchio(Azienda Ospedaliero Universitaria San Giovanni Battista), Mauro Risio(Azienda Ospedaliero Universitaria San Giovanni Battista), Mauro Salizzoni(Azienda Ospedaliero Universitaria San Giovanni Battista), Lorenzo Capussotti(Azienda Ospedaliero Universitaria San Giovanni Battista), Timothy Perera(Azienda Ospedaliero Universitaria San Giovanni Battista), Enzo Médico(Candiolo Cancer Institute), Maria Flavia Di Renzo(Candiolo Cancer Institute), Paolo M. Comoglio(Candiolo Cancer Institute), Livio Trusolino(Candiolo Cancer Institute), Andrea Bertotti(Candiolo Cancer Institute)
Clinical Cancer Research
March 29, 2011
Cited by 128Open Access
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Abstract

PURPOSE: We determined the gene copy numbers for MET, for its transcriptional activator MACC1 and for its ligand hepatocyte growth factor (HGF) in liver metastases from colorectal carcinoma (mCRC). We correlated copy numbers with mRNA levels and explored whether gain and/or overexpression of MET and MACC1 predict response to anti-Met therapies. Finally, we assessed whether their genomic or transcriptional deregulation correlates with pathologic and molecular parameters of aggressive disease. EXPERIMENTAL DESIGN: One hundred three mCRCs were analyzed. Copy numbers and mRNA were determined by quantitative PCR (qPCR). Thirty nine samples were implanted and expanded in NOD (nonobese diabetic)/SCID (severe combined immunodeficient) mice to generate cohorts that were treated with the Met inhibitor JNJ-38877605. In silico analysis of MACC1 targets relied on genome-wide mapping of promoter regions and on expression data from two CRC datasets. RESULTS: No focal, high-grade amplifications of MET, MACC1, or HGF were detected. Chromosome 7 polysomy and gain of the p-arm were observed in 21% and 8% of cases, respectively, and significantly correlated with higher expression of both Met and MACC1. Met inhibition in patient-derived xenografts did not modify tumor growth. Copy number gain and overexpression of MACC1 correlated with unfavorable pathologic features better than overexpression of Met. Bioinformatic analysis of putative MACC1 targets identified elements besides Met, whose overexpression cosegregated with aggressive forms of colorectal cancer. CONCLUSIONS: Experiments in patient-derived xenografts suggest that mCRCs do not rely on Met genomic gain and/or overexpression for growth. On the basis of pathologic correlations and bioinformatic analysis, MACC1 could contribute to CRC progression through mechanisms other than or additional to Met transcriptional upregulation.


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