A Personalized Pre-clinical Model to Evaluate the Metastatic Potential of Patient-derived Colon Cancer Initiating Cells
Menée à l'aide d'échantillons de 32 tumeurs primitives colorectales et 8 métastatases hépatiques, cette étude évalue l'intérêt de xénogreffes dérivées des patients sur des modèles murins pour évaluer le potentiel métastatique d'une tumeur et prédire la réponse thérapeutique chez un patient
Purpose: Within the aim of advancing precision oncology, we have generated a collection of patient-derived xenografts (PDX) characterized at the molecular level, and a pre-clinical model of colon cancer metastasis to evaluate drug-response and tumor progression.
Experimental design: We derived cells from 32 primary colorectal carcinomas and eight liver metastases and generated PDX annotated for their clinical data, gene expression, mutational and histopathological traits. Six models were injected orthotopically into the cecum wall of NOD-SCID mice. Three of them were treated with chemotherapy (oxaliplatin) and three with API2 to target AKT activity. Tumor growth and metastasis progression were analyzed by Positron Emission Tomography (PET).
Results: Patient-derived cells generated tumor xenografts that recapitulated the same histopathological and genetic features as the original patients carcinomas. We show an 87.5% tumor take rate that is one of the highest described for implanted cells derived from colorectal cancer patients. Cecal injection generated primary carcinomas and distant metastases. Oxaliplatin treatment prevented metastasis and API2 reduced tumor growth as evaluated by PET.
Conclusion: Our improved protocol for cancer cell engraftment has allowed us to build a rapidly expanding collection of colorectal PDX, annotated for their clinical data, gene expression, mutational and histopathological statuses. We have also established a mouse model for metastatic colon cancer with patient-derived cells in order to monitor tumor growth, metastasis evolution and response to treatment by PET. Our PDX models could become the best pre-clinical approach through which to validate new biomarkers or investigate the metastatic potential and drug-response of individual patients.
Clinical Cancer Research , résumé, 2013