Mutation Status of KRAS, BRAF, PIK3CA and Expression Level of AREG and EREG Identify Responders to Cetuximab in a Large Panel of Patient Derived Colorectal Carcinoma Xenografts of All Four UICC Stages

Paulina Pechańska, M. Becker, T. Mayr, B. Hinzmann, H.-P. Adams, I. Klaman, K.-H. Kretschmar, K. Kretschmar, K. Stecker, R. Mantke, R. Pauli, J. Pertschy, K. Hertel, K. Ridwelski, K. Hellwig, M. Pross, C. Radke, I. Fichtner, J. Hoffmann, A. Rosenthal

DRK Kliniken Berlin-K?penik, Klinik für Chirurgie, Institut für Pathologie, Berlin, Germany.
Experimental Pharmacology & Oncology Berlin-Buch GmbH, Berlin, Germany.
HELIOS Klinikum Erfurt, Institut für Pathologie, Erfurt, Germany.
Katholisches Krankenhaus St. Johann Nepomuk, Klinik für Allgemeine Chirurgie, Erfurt, Germany.
Klinikum Magdeburg, Klinik für Allgemein-und Viszeralchirurgie, Institut für Pathologie, Magdeburg, Germany.
Max Delbrück Center für Molekulare Medizin (MDC), Experimentale Pharmakologie, Berlin, Germany.
Signature Diagnostics AG, Potsdam, Germany.
St?dtisches Klinikum Brandenburg GmbH, Klinik für Allgemein-und Viszeralchirurgie, Institut für Pathologie, Brandenburg an der Havel, Germany.

DOI: 10.4236/jct.2013.42083                

Abstract

To advance preclinical testing of novel targeted drugs in colorectal cancer (CRC) we established a panel of 133 mouse xenograft models from fresh tumor specimens of 239 patients with CRC of all four UICC stages. A subgroup of 67 xenograft models was treated with cetuximab, bevacizumab and oxaliplatin as single agents. Mutation status of KRAS (G12, G13, A146T), BRAF (V600E) and PIK3CA (E542K, E545K, H1047R) was assessed in all xenografts by allelespecific real-time PCR. KRAS codon 61 was assessed by conventional sequencing. AREG and EREG expression levels were analyzed by real-time PCR expression assays. In the treatment experiment we observed response rates of 27% (18/67) for cetuximab, 3% (2/67) for bevacizumab, and 6% (4/67) for oxaliplatin. Classification based on KRAS, BRAF and PIK3CA mutation status identified 15 of the responders (sensitivity 83%, confidence interval at p = 0.05 (CI): 59% - 96%), and 38 nonresponders (specificity 78%, CI: 63% - 88%). If any mutation except in KRAS codon 13 were considered, the classifier reached sensitivity of 94% and specificity of 69%. We improved specificity of the classifiers to 90% and 86% respectively by adding AREG and EREG RNA expression thresholds retrospectively. In patient-derived xenograft models, we found a predictive classifier for response to cetuximab that is more accurate than established biomarkers. We confirmed its potential performance in primary human tumors. For patients, the classifier’s sensitivity promises increased response rates and its specificity limits unnecessary toxicity. Given the scope of our xenograft models across all UICC stages, this applies not only to mCRC but also to the adjuvant setting of earlier stages. The xenograft collection allows to mimic randomized phase II trials and to test novel drugs effectively as single agents or in combinations. It also enables the development of highly accurate companion diagnostics as demonstrated by us for cetuximab.

Keywords

Colorectal Cancer; Xenograft; Mutation; Biomarker; Cetuximab

Conflicts of Interest

The authors declare no conflicts of interest.

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