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Most circulating tumor DNA (ctDNA) assays are designed to detect recurrent mutations. Pediatric sarcomas share few recurrent mutations but rather are characterized by translocations and copy-number changes. We applied Cancer Personalized Profiling by deep Sequencing (CAPP-Seq) for detection of translocations found in the most common pediatric sarcomas. We also applied ichorCNA to the combined off-target reads from our hybrid capture to simultaneously detect copy-number alterations (CNA). We analyzed 64 prospectively collected plasma samples from 17 patients with pediatric sarcoma. Translocations were detected in the pretreatment plasma of 13 patients and were confirmed by tumor sequencing in 12 patients. Two of these patients had evidence of complex chromosomal rearrangements in their ctDNA. We also detected copy-number changes in the pretreatment plasma of 7 patients. We found that ctDNA levels correlated with metastatic status and clinical response. Furthermore, we detected rising ctDNA levels before relapse was clinically apparent, demonstrating the high sensitivity of our assay. This assay can be utilized for simultaneous detection of translocations and CNAs in the plasma of patients with pediatric sarcoma. While we describe our experience in pediatric sarcomas, this approach can be applied to other tumors that are driven by structural variants.

Osteosarcoma is a highly aggressive cancer for which treatment has remained essentially unchanged for more than 30 years. Osteosarcoma is characterized by widespread and recurrent somatic copy-number alterations (SCNA) and structural rearrangements. In contrast, few recurrent point mutations in protein-coding genes have been identified, suggesting that genes within SCNAs are key oncogenic drivers in this disease. SCNAs and structural rearrangements are highly heterogeneous across osteosarcoma cases, suggesting the need for a genome-informed approach to targeted therapy. To identify patient-specific candidate drivers, we used a simple heuristic based on degree and rank order of copy-number amplification (identified by whole-genome sequencing) and changes in gene expression as identified by RNA sequencing. Using patient-derived tumor xenografts, we demonstrate that targeting of patient-specific SCNAs leads to significant decrease in tumor burden, providing a road map for genome-informed treatment of osteosarcoma. Significance: Osteosarcoma is treated with a chemotherapy regimen established 30 years ago. Although osteosarcoma is genomically complex, we hypothesized that tumor-specific dependencies could be identified within SCNAs. Using patient-derived tumor xenografts, we found a high degree of response for “genome-matched” therapies, demonstrating the utility of a targeted genome-informed approach. This article is highlighted in the In This Issue feature, p. 1

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.

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.

Osteosarcoma (OS) is a highly malignant cancer for which no targeted therapies are currently available. Current treatment modalities are limited to intensive, highly toxic chemotherapy and surgical resection. OS is characterized by wide spread copy number alterations and structural rearrangements. In contrast, no recurrent point mutations in protein-coding genes have been identified, suggesting that copy number alterations (CNAs) are key oncogenic drivers in this disease. However, as copy number alterations are highly heterogeneous, it is likely that each tumor has a distinct set of oncogenic drivers, making a unified treatment approach difficult to define. To identify candidate patient-specific drivers, we used a simple heuristic based on degree of amplification (as assessed by Whole Genome Sequencing) and changes in gene expression (as assessed by RNA sequencing). Using patient-derived tumor xenografts (PDTXs), we assessed if individual OS tumors respond to targeted therapy selected based on this approach. We rank-ordered CNAs in 9 PDTXs by the amplitude of the copy number gain and identified 5 pathways for targeted therapy including CCNE1, MYC, CDK4, PTEN/AKT and AURKB. Next, we prioritized drug choices to those that are in clinical trials and that are readily available and identified 5 drug matches for 9 PDTXs. We used the CDK2 inhibitor Dinaciclib for CCNE1 amplification and observed TGI of 85.5% and 67.8% for 2 different CCNE1 amplified PDTXs tested. CDK9 inhibitor AT7519 was used to treat 2 different MYC amplified PDTXs resulting in TGI of 104% and 83.9%. CDK4 amplified PDTXs were treated with CDK4/6 inhibitor, Palbociclib, resulting in TGI of 82.7%. AKT1 inhibitor MK-2206 was used to treat either AKT1 gains or PTEN loss resulting in TGI of 65.6% and 60.8% respectively. AURKB inhibitor AZD-1152 for AURKB amplified PDTXs in combination with cisplatin resulting in TGI 85.8%. These results support the hypothesis that specific genes within CNA regions serve as oncogenic drivers and that these represent therapeutic opportunities in OS. Our studies provide a roadmap for personalized genome-informed therapy of osteosarcoma, a cancer in which no new therapies have been identified in over 30 years. Citation Format: Leanne C. Sayles, Marcus Breese, Amanda L. Koehne, Stanley Leung, Aviv Spillinger, Alex Lee, Avanthi Shah, Krystal Straessler, Sheri Spunt, Neyssa Marina, Damon Jacobson, Raffi S. Avedian, David G. Mohler, Steven DuBois, Douglas S. Hawkins, E. Alejandro Sweet-Cordero. Tumor-specific copy number alterations uncover therapeutic opportunities in osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1948. doi:10.1158/1538-7445.AM2017-1948