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• W2886036362 abstract "Osteosarcoma (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 pre-clinical proof of principle for development of a targeted therapy “basket” trial for OS. Citation Format: Leanne Sayles, Marcus Breeese, Amanda Koehne, Bogdan Tanasa, Stanley Leung, Alex Lee, Avanthi Shah, krystal Straessler, Kim Hazard, Mi-Ok Kim, Alejandro Sweet-Cordero. Genome-informed therapy for osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2629." @default.
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• W2886036362 date "2018-07-01" @default.
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• W2886036362 title "Abstract 2629: Genome-informed therapy for osteosarcoma" @default.
• W2886036362 doi "https://doi.org/10.1158/1538-7445.am2018-2629" @default.
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