Abstract PR-4: From mice to men: Guiding cancer treatment through Personalized Tumorgraft™ models results in prolonged clinical responses in patients with refractory advanced cancers and discovery of novel predictive biomarkers (2009)

Abstract Personalizing cancer treatment, finding the right drug for a patient, is a promising strategy to improve cancer outcome. Thus far, however, most strategies have focused on discovering biomarkers of efficacy for selected drugs (finding patients for drugs) but have not provided a more universal, patient-centered approach (finding drugs for patients). We aimed to personalize cancer treatment by generating individual Personalized Tumorgrafts™ generated from the patient's own tumor. Here we present results from 10 patients diagnosed with advanced, standard of care refractory cancers, from whom we generated a Personalized Tumorgraft using either primary tumor material (6 patients) or a tumor biopsy (4 patients). Tumor fragments were implanted in nude mice and propagated as tumor fragments to generate cohorts of homogeneously growing tumors suitable for drug treatments. A total of 159 different anticancer agents alone or in combination spanning all currently known classes of anticancer agents and mechanisms of action were evaluated. From this, the most effective tailor made treatment was selected for application to clinical care. Overall, 16 Tumorgraft recommended treatments have been administered to 10 patients which resulted in a 100 % correlation of both positive and negative predictive values. Of the 8 patients treated with a Tumorgraft recommended drug regimen, all achieved long-lasting partial or complete responses including two patients with 36 + months survival. Biological studies in these clinically validated Tumorgraft models, for which there is unlimited tumor material, offer the unique opportunity to discover new biomarkers. In this endeavor, global sequence analysis was performed on the Tumorgraft obtained from a gemcitabine-resistant pancreatic cancer patient who responded dramatically to DNA damaging agents. This analysis led to the discovery of a new biomarker, a novel mutation in the PALB2 gene. Functional analysis shows that this mutation impairs BRCA1/BRCA2 binding conferring DNA repair incompetence to the tumor. Likewise, gene expression analysis of the Personalized Tumorgraft generated from a colorectal cancer patient with extreme sensitivity to irinotecan showed a robust gene expression profile characteristic of high intratumoral retention of the active metabolite SN38. In summary, we demonstrate that generation of Personalized Tumorgrafts from cancer patients is feasible, and that these models can be used for extensive personalized drug screening studies leading to the selection of potentially clinically effective agents. Moreover, there is a striking correlation between Tumorgraft response in mice and clinical activity in the patients administered the Tumorgraft recommended treatments thereby demonstrating the predictive nature of the Personalized Tumorgraft models and supporting the benefits of this attractive platform in drug development through the discovery new biomarkers and the understanding of a drug's mechanism of action. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):PR-4.