Abstract 3233: Modeling evolution of resistance in patient-derived xenografts: resistance to the BRAF inhibitor PLX4720.

A major hurdle for targeted cancer therapies is the development of resistance, with many agents showing promising initial results but not providing significant overall survival benefits. To address resistance we need to know the genetic and epigenetic alterations that drive resistance. This knowledge will contribute to modified treatment protocols, new targets, and predictive biomarkers. We are working on a system to model evolution of tumor resistance in a the patient-derived xenograft (PDX) mouse system. Compared to xenografts, PDXs are closer to the tumor biology of the patient, having a higher degree of molecular subtypes and intratumor heterogeneity, and a mixture of human and mouse stroma. In this study, we implanted 1-3mm chunks from a primary colorectal cancer tumor carrying the BRAF V600>E mutation into immunosuppressed NOD/SCID CB.17 mice. Once the tumors were established (100-150mmˆ3 tumor burden), the mice were stratified into two groups, control and fed chow containing the BRAF inhibitor PLX4720, 417 mg/kg (Scientific Diets). The tumors in most of the PDXs in the group fed PLX4720 chow regressed and became very small by day 77. In several cases PDXs that were allowed to develop beyond day 77 became resistant to PLX4720 treatment. To identify mechanisms of PLX4720 resistance we sequenced DNA and RNA from two resistant PDXs, one untreated control PDX, and a sample of the original patient tumor. We used the Ion AmpliSeq Comprehensive Cancer Panel from Life Technologies to sequence exons from 409 cancer related genes on the Ion Torrent PGM. Additionally, we performed SOLiD 5500 paired-end (50x25 nt) next generation sequencing (NGS) of the whole transcriptome of these samples. Since the stromal component of the PDXs is a mixture of cells of human and mouse origin, and sequence reads of mouse origin could contribute to false positive mutation calls or skew expression analysis of the resistant data, we needed to develop a method for filtering mouse reads out of our sequencing data. To this end, we have developed and applied a read filtering protocol that sorts reads that align to the human genome into three groups, better in human, better in mouse, or ambiguous. 97.7% of the reads from human tissue were defined as better in human with the remaining 2.3% being ambiguous, or better in mouse. PDX derived reads had between 8% and 13% of reads being better in mouse. Only reads defined as better in human were used for expression analysis and SNP calling in this work. In one of the two resistant tumors analyzed this method has identified a candidate resistance mutation, NRAS G13>D. The NRAS mutation is seen in both the RNA-seq and DNA-seq data, and is not seen in the original patient tumor, the control untreated PDX, or in the second resistant tumor. Based on these findings, we feel that PDX provide a powerful model system for examining the evolution of resistance to targeted agents. Citation Format: Brian P. James, Robert J. Lemos, Feng Tian, Thomas C. Motter, Amin Momin, Nastaran D. Neishaboori, Galina M. Kiriakova, Scott Kopetz, Garth Powis. Modeling evolution of resistance in patient-derived xenografts: resistance to the BRAF inhibitor PLX4720. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3233. doi:10.1158/1538-7445.AM2013-3233