Abstract B05: Preclinical evaluation of genome-informed therapy for osteosarcoma using patient-derived xenografts

Abstract

Abstract Osteosarcoma (OS) patients who relapse after initial therapy or present with metastatic disease have an extremely poor prognosis. Chemotherapy regimens for these patients have limited efficacy and significant toxicities. In clinical practice, treatment is rarely informed by the specific genetic events in individual tumors. It is now well established that OS is characterized by numerous copy-number alterations (CNAs) and structural variations (SVs) in cancer-relevant genes. In contrast, recurrent point mutations are not seen. Thus, OS is a “C-class” (copy number driven) rather than an “M-class” (mutation driven) cancer. However, while a great deal of effort has been directed toward the identification of point mutations in druggable cancer genes, much less effort has gone into determining whether copy number alterations can be used to select therapies for aggressive cancers such as OS. The genomic heterogeneity of OS suggests that there may be different oncogenic drivers in subsets of patients. Thus, a systematic effort to identify targetable, patient-specific key driver genes (likely CNAs) is required. We established a clinically annotated patient-derived tumor xenograft (PDTX) bank of over 20 OS samples obtained at diagnosis, after surgical resection and from metastasis, thus representing the full spectrum of disease. Comparison between PDTXs and matched primary tumor demonstrated high correlation in copy number (by WGS) and gene expression (by RNAseq), suggesting that PDTXs are faithful preclinical models for OS. To identify recurrent CNAs, we analyzed this WGS dataset together with a public dataset of an additional 18 WGS samples. With this combined dataset of 42 samples, we searched for recurrent CNAs across a cancer gene list (1256 genes) generated by combining data from COSMIC and CIVIC. We identified 188 cancer genes amplified at least 4-fold in at least 2 samples. We then used a publicly available resource to identify genes considered “actionable” or “druggable” in cancer. The two most frequently amplified genes in OS are CCNE1 (16/42 cases) and MYC (13/42 cases). Other frequent alterations were those in the PI3K pathway (PTEN loss and/or AKT amplification), AURKB amplification and VEGFA amplification. Importantly, all of these CNAs were reflected in at least one PDTX models. We hypothesized that in OS some of these CNAs are key cancer drivers that can be targeted for cancer treatment. To test this hypothesis, we rank-ordered the CNAs in 9 PDTXs by the amplitude of the copy number gain. We used this simple heuristic to identify candidate drivers for individual samples. We then identified 6 drugs that could be used to target specific amplified genes and tested these drugs in corresponding CNA-matched PDTX. In 9/9 cases we saw significant growth inhibition. These results support the hypothesis that specific genes within CNA serve as oncogenic drivers in OS and thus outline a feasible approach to personalized, genome-informed therapy for this disease. Importantly, the drugs tested were not effective for PDTXs that did not carry the CNA. However, in all cases tested we saw only tumor stasis with a single agent. Therefore, combination therapies will be needed to induce adequate tumor cell kill in OS. Citation Format: Leanne Sayles, Marcus Breese, Amanda Koehne, Leung Stan, Marina Neyssa, Spunt Sheri, Lee Alex, Aviv Spillinger, Steve Dubois, Rafi Avedian, Doug Hawkins, Mohler David, Alejandro Sweet-Cordero. Preclinical evaluation of genome-informed therapy for osteosarcoma using patient-derived xenografts [abstract]. In: Proceedings of the AACR International Conference held in cooperation with the Latin American Cooperative Oncology Group (LACOG) on Translational Cancer Medicine; May 4-6, 2017; São Paulo, Brazil. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(1_Suppl):Abstract nr B05.