Abstract PR05: Genomic analysis of osteosarcoma reveals opportunities for targeted therapy
Authors: Sayles Leanne , Breese Marcus , Koehne Amanda , Straessler Krystal , Leung Stanley , Spillinger Aviv , Hawkins Doug , Dubois Steven , Lee Alex , Tanasa Bogdan , Miok Kim , Shah Avanthi , Spunt Sheri , Marina Neyssa , Hazard Kim , Sweet-Cordero Alejandro 
Published: February 2019

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. Thus, new therapeutic approaches are urgently needed. 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, little is known with regards to 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 16 OS samples obtained at diagnosis, after surgical resection, and from metastasis, thus representing the full spectrum of disease. Comparison between PDTXs with a corresponding matched primary tumor demonstrated high correlation in copy number (by WGS for 12 samples) and gene expression (by RNAseq for 13 samples), suggesting that PDTXs are faithful preclinical models for OS. To identify recurrent CNAs, we analyzed this WGS dataset together with a public dataset of OS WGS samples. With this combined dataset of 69 samples from 52 patients, we searched for recurrent CNAs across an actionable cancer gene list and identified genes amplified at least 4-fold in at least 2 samples. The two most frequently amplified genes in OS are CCNE1 and MYC. Other frequent alterations were those in the PI3K pathway (PTEN loss and/or AKT amplification), AURKB amplification, CDK4 amplification, and VEGFA amplification. Importantly, all of these CNAs were reflected in at least one PDTX model. 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 all cases, we saw significant growth inhibition in matched PDTXs whereas the effect was minimal in PDTXs treated with unmatched therapies. 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. This work could serve as the necessary preclinical proof of principle for development of a targeted therapy basket trial for OS.
In parallel to these studies and in order to further define the evolutionary trajectory of OS, we have carried out a comprehensive analysis of both spatial and temporal changes that occur in OS samples from the same patient. This has allowed us to begin defining the role of whole-genome duplication events and chromothripsis as well as loss of heterozygosity in the evolution of OS. We are directing our current efforts towards merging this evolutionary analysis with knowledge of possible targetable events to further identify key vulnerabilities that could be exploited for therapeutic benefit.
Citation Format: Leanne Sayles, Marcus Breese, Amanda Koehne, Krystal Straessler, Stanley Leung, Aviv Spillinger, Doug Hawkins, Steven Dubois, Alex Lee, Bogdan Tanasa, Kim Miok, Avanthi Shah, Sheri Spunt, Neyssa Marina, Kim Hazard, Alejandro Sweet-Cordero. Genomic analysis of osteosarcoma reveals opportunities for targeted therapy [abstract]. In: Proceedings of the AACR Special Conference: Pediatric Cancer Research: From Basic Science to the Clinic; 2017 Dec 3-6; Atlanta, Georgia. Philadelphia (PA): AACR; Cancer Res 2018;78(19 Suppl):Abstract nr PR05.