Patient-derived xenograft (PDX) models of colorectal carcinoma (CRC) as a platform for chemosensitivity and biomarker analysis in personalized medicine

Abstract

Patient-derived xenograft (PDX) tumor models represent a valuable platform for identifying new biomarkers and novel targets, to evaluate therapy response and resistance mechanisms. This study aimed at establishment, characterization and therapy testing of colorectal carcinoma-derived PDX. We generated 49 PDX and validated identity between patient tumor and corresponding PDX. Sensitivity of PDX toward conventional and targeted drugs revealed that 92% of PDX responded toward irinotecan, 45% toward 5-FU, 65% toward bevacizumab, and 61% toward cetuximab. Expression of epidermal growth factor receptor (EGFR) ligands correlated to the sensitivity toward cetuximab. Proto-oncogene B-RAF, EGFR, Kirsten rat sarcoma virus oncogene homolog gene copy number correlated positively with cetuximab and erlotinib sensitivity. The mutational analyses revealed an individual mutational profile of PDX and mainly identical profiles of PDX from primary tumor vs corresponding metastasis. Mutation in PIK3CA was a determinant of accelerated tumor doubling time. PDX with wildtype Kirsten rat sarcoma virus oncogene homolog, proto-oncogene B-RAF, and phosphatidylinositol-4,5-bisphosphate 3-kinaseM catalytic subunit alfa showed higher sensitivity toward cetuximab and erlotinib. To study the molecular mechanism of cetuximab resistance, cetuximab resistant PDX models were generated, and changes in HER2, HER3, betacellulin, transforming growth factor alfa were observed. Global proteome and phosphoproteome profiling showed a reduction in canonical EGFR-mediated signaling via PTPN11 (SHP2) and AKT1S1 (PRAS40) and an increase in anti-apoptotic signaling as a consequence of acquired cetuximab resistance. This demonstrates that PDX models provide a multitude of possibilities to identify and validate biomarkers, signaling pathways and resistance mechanisms for clinically relevant improvement in cancer therapy.

Keywords

• Colorectal carcinoma
• Patient-derived xenograft models
• In vivo drug testing
• Personalized medicine