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While oncogenes promote cancer cell growth, unrestrained proliferation represents a significant stressor to cellular homeostasis networks such as the DNA damage response (DDR). To enable oncogene tolerance, many cancers disable tumor suppressive DDR signaling through genetic loss of DDR pathways and downstream effectors (e.g., ATM or p53 tumor suppressor mutations). Whether and how oncogenes can help “self-tolerize” by creating analogous functional deficiencies in physiologic DDR networks is not known. Here we focus on Ewing sarcoma, a FET fusion oncoprotein (EWS-FLI1) driven pediatric bone tumor, as a model for the class of FET rearranged cancers. Native FET protein family members are among the earliest factors recruited to DNA double-strand breaks (DSBs) during the DDR, though the function of both native FET proteins and FET fusion oncoproteins in DNA repair remains to be defined. Using preclinical mechanistic studies of the DDR and clinical genomic datasets from patient tumors, we discover that the EWS-FLI1 fusion oncoprotein is recruited to DNA DSBs and interferes with native FET (EWS) protein function in activating the DNA damage sensor ATM. As a consequence of FET fusion-mediated interference with the DDR, we establish functional ATM deficiency as the principal DNA repair defect in Ewing sarcoma and the compensatory ATR signaling axis as a collateral dependency and therapeutic target in multiple FET rearranged cancers. More generally, we find that aberrant recruitment of a fusion oncoprotein to sites of DNA damage can disrupt physiologic DSB repair, revealing a mechanism for how growth-promoting oncogenes can also create a functional deficiency within tumor suppressive DDR networks.

Models to study metastatic disease in rare cancers are needed to advance preclinical therapeutics and to gain insight into disease biology, especially for highly aggressive cancers with a propensity for metastatic spread. Osteosarcoma is a rare cancer with a complex genomic landscape in which outcomes for patients with metastatic disease are poor. As osteosarcoma genomes are highly heterogeneous, a large panel of models is needed to fully elucidate key aspects of disease biology and to recapitulate clinically-relevant phenotypes. We describe the development and characterization of osteosarcoma patient-derived xenografts (PDXs) and a panel of PDX-derived cell lines. Matched patient samples, PDXs, and PDX-derived cell lines were comprehensively evaluated using whole genome sequencing and RNA sequencing. PDXs and PDX-derived cell lines largely maintained the expression profiles of the patient from which they were derived despite the emergence of whole-genome duplication (WGD) in a subset of cell lines. These cell line models were heterogeneous in their metastatic capacity and their tissue tropism as observed in both intravenous and orthotopic models. As proof-of-concept study, we used one of these models to test the preclinical effectiveness of a CDK inhibitor on the growth of metastatic tumors in an orthotopic amputation model. Single-agent dinaciclib was effective at dramatically reducing the metastatic burden in this model.Graphical Abstract

For many pediatric cancer patients, commonly used gene-panel sequencing tests yield few actionable results, partly due to the complex genomic alterations present. We hypothesized that an unbiased approach, combining whole-genome (WGS) and RNA sequencing (RNAseq), could overcome this and lead to a more comprehensive understanding of these diseases. While prior studies have evaluated WGS and RNAseq in pediatric cancers, few focused primarily on metastatic or relapsed disease. We also placed special focus on longitudinal profiling of patients, including with additional deep sequencing, to capture tumor evolution at the primary and metastatic sites, and to quantify the utility of resampling. We assembled a cohort of 191 high-risk pediatric oncology patients, including solid tumors, CNS tumors, and leukemias/lymphomas. We have representation of patients with relapsed/refractory disease (68), metastatic disease at diagnosis (10), rare diagnoses (19), prior cancer history, and estimated overall survival Multiple sampling from the same patient identified drastic spatial and temporal differences in the genomes and transcriptomes of these tumors. Using the Jaccard index as a measure of concordance between samples shows dynamic changes between samples collected at different time points across multiple modalities (range 0-1, 1 is identical); SNVs ranged from 0.01-0.79, SVs 0.01-0.73, major CNAs 0.07-0.99, minor CNAs 0.38-0.99, up expression outliers 0.12-0.56, down expression outliers 0.04-0.54, and fusions 0-1. Potentially biologically significant differences in therapy-induced mutations by platinum agents were also observed, highlighting the impact of therapy on tumor evolution. Clonal architectures were extracted from deep resequencing and show extensive spatial, temporal, and metastatic heterogeneity in these rare and highly aggressive malignancies that is not captured by WGS alone. Identifying clinically relevant evolution remains a challenge in most patients, but our results suggest that resampling of pediatric tumors at relapse or metastasis will be important for the effectiveness of targeted therapies in the future. Citation Format: Henry J. Martell, Avanthi T. Shah, Alex G. Lee, Bogdan Tanasa, Stanley G. Leung, Aviv Spillinger, Heng-Yi Liu, Inge Behroozfard, Phuong Dinh, María V. Pons Ventura, Florette K. Hazard, Arun Rangaswami, Sheri L. Spunt, Norman J. Lacayo, Tabitha Cooney, Jennifer G. Michlitsch, Anurag K. Agrawal, Marcus R. Breese, Alejandro Sweet-Cordero. Longitudinal profiling of high-risk pediatric malignancies using a multiomics approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1509.

We have leveraged long-read and spatial sequencing modalities to identify patient-specific oncogenic alterations for treatment of pediatric osteosarcomas. Osteosarcoma (OS) is the most common primary bone malignancy in children and young adults, with over 500 cases identified each year in the United States. OS is archetypal of cancers driven by aneuploidy and structural rearrangement rather than point mutations. These structural variants (SVs) can alter gene expression stoichiometrically, but the functional consequences of many SVs stem from their effect on multidimensional genome organization. SVs can enable enhancer hijacking, alter boundaries of topologically associated domains (TADs), and move gene loci to different regulatory compartments affecting transcription. SVs can also form extrachromosomal DNA amplicons (ecDNA), which can be megabases in size and can incorporate both genes and regulatory elements to result in substantial increases in gene transcription and intratumor heterogeneity. Complex SVs may have profound implications for prognosis and treatment in OS and other cancers. By incorporating long-read optical genome mapping (OGM) and chromatin conformation capture sequencing (HiC), our goal is to detect complex tumor-specific SVs that will inform and refine pediatric OS subtypes, revealing new tumor-specific chemotherapy treatment options. We have generated a unique panel of 11 OS patient-derived xenograft (PDX) cell lines which have been previously characterized regarding response to targeted therapies using whole genome (WGS), RNA (RNA-seq), and chromatin accessibility (ATAC-seq) sequencing. To understand the complex genomic reorganization that occurs in OS, we have integrated OGM and WGS data for six cell lines, and OGM, WGS, and HiC data for two. SVs were detected using OGM, HiC, and WGS modalities, and we observed 59-61% concordance between SVs called using OGM and HiC, versus 22-45% when comparing with WGS calls. PDX lines assayed using OGM exhibit between 5,135 and 7,514 SVs each, and translocation numbers ranged from 212 to 1,422. These lines exhibit between dozens of potential ecDNA amplicons, including one amplicon which may explain that line’s specific and exceptionally high expression of YAP1 and BIRC2 transcripts. HiC interaction maps for two PDX lines reveal genomic compartments and TAD boundaries in detail, with 3,713 unique TAD boundaries identified between them using 50kb genomic bins. We observe that 60% of these boundaries are consistent between these lines, and 27% exhibit differences that suggest boundary loss or gain. These changing boundaries are associated with numerous SVs and/or copy number discrepancies, and with genomic regions containing genes with dysregulated RNA transcript levels. Incorporating OGM and HiC modalities adds substantially to our ability to detect oncogenic SVs and the genes they affect. Citation Format: Andrew S. Clugston, Megan Ostrowski, Coco Wu, Leanne Sayles, Stanley G. Leung, Vijay Ramani, E. Alejandro Sweet-Cordero, Marcus R. Breese. Patient-specific mapping of oncogenic structural changes in pediatric osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 214.

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.

Overlapping myelodysplastic/myeloproliferative neoplasms (MDS/MPN) are clonal hematopoietic disorders with features of myelodysplasia and myeloproliferation. The only well-characterized MDS/MPN in children is juvenile myelomonocytic leukemia, an aggressive disorder of infants and toddlers. The biochemical hallmark of this disease is hyperactivation of the Ras/MAPK signaling pathway caused by mutations in Ras pathway genes in more than 90% of patients. Translocations involving receptor tyrosine kinases have been identified in rare cases. Here, we report a 2-year-old patient who presented with MDS/MPN driven by a cytogenetically cryptic NUP98-NSD1 fusion, a translocation thought to exclusively occur in patients with acute myeloid leukemia.

The use of sequencing-based assays for clinical management of pediatric cancer patients has become increasingly common. However, for many pediatric patients, gene panel based sequencing tests yield few actionable results. Given the complex genomic alterations present in many pediatric cancers, especially high-risk solid tumors, we hypothesized that an unbiased approach might reveal more actionable findings and lead to a more comprehensive understanding of these diseases. To accomplish this, we integrated whole-genome sequencing (WGS) with RNAseq in the analysis of a pediatric oncology cohort, with a focus on longitudinal cases to capture potential tumor evolution in metastatic or treated cases. Our cohort consists of 269 high-risk pediatric oncology patients, including patients with relapsed/refractory disease, metastatic disease at diagnosis, prior cancer history, a rare diagnosis, or an estimated overall survival Our results show that the integration of WGS and RNAseq can provide more and higher-quality actionable information than either modality alone, whilst also capturing the majority of actionable variants detected by panel sequencing. RNAseq identified not only druggable fusions and expression outliers, but also many rare and novel fusions. WGS provided fusion validation but highlighted the limitations of WGS alone in identifying fusions resulting from complex SVs. Conversely, WGS was adept at capturing genome-wide patterns of CNAs and loss of heterozygosity that are missed by gene-centric panels. Further RNAseq integration enabled prioritization of expressed SNVs as well as CNAs and SVs that significantly alter gene expression. We also used WGS to extract mutational signatures and tracked their evolution across longitudinal samples. We found potentially biologically significant differences in therapy-induced mutations caused by platinum and alkylating agents. Our unbiased approach has enabled further discovery that advances our understanding of these rare and highly aggressive malignancies. Citation Format: Henry J. Martell, Avanthi Tayi Shah, Alex G. Lee, Bogdan Tanasa, Stanley G. Leung, Aviv Spillinger, Heng-Yi Liu, Inge Behroozfard, Phuong Dinh, Maria V. Pons Ventura, Florette K. Hazard, Arun Rangaswami, Sheri L. Spunt, Norman J. Lacayo, Tabitha Cooney, Jennifer G. Michlitsch, Anurag K. Agrawal, Marcus R. Breese, E. Alejandro Sweet-Cordero. Integrative analysis of whole-genome and RNA sequencing in high-risk pediatric malignancies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 54.

Precision oncology has primarily relied on coding mutations as biomarkers of response to therapies. While transcriptome analysis can provide valuable information, incorporation into workflows has been difficult. For example, the relative rather than absolute gene expression level needs to be considered, requiring differential expression analysis across samples. However, expression programs related to the cell-of-origin and tumor microenvironment effects confound the search for cancer-specific expression changes. To address these challenges, we developed an unsupervised clustering approach for discovering differential pathway expression within cancer cohorts using gene expression measurements. The hydra approach uses a Dirichlet process mixture model to automatically detect multimodally distributed genes and expression signatures without the need for matched normal tissue. We demonstrate that the hydra approach is more sensitive than widely-used gene set enrichment approaches for detecting multimodal expression signatures. Application of the hydra analysis framework to small blue round cell tumors (including rhabdomyosarcoma, synovial sarcoma, neuroblastoma, Ewing sarcoma, and osteosarcoma) identified expression signatures associated with changes in the tumor microenvironment. The hydra approach also identified an association between ATRX deletions and elevated immune marker expression in high-risk neuroblastoma. Notably, hydra analysis of all small blue round cell tumors revealed similar subtypes, characterized by changes to infiltrating immune and stromal expression signatures., Author summary Pediatric cancers generally have few somatic mutations. To increase the number of actionable treatment leads, precision pediatric oncology initiatives also analyze tumor gene expression patterns. However, currently available approaches for gene expression data analysis in the clinical setting often use arbitrary thresholds for assessing overexpression and assume gene expression is normally distributed. These methods also rely on reference distributions of related cancer types or normal samples for assessing expression distributions. Often adequate normal samples are not available, and comparing matched cancer cohorts without accounting for subtype expression overestimates the uncertainty in the analysis. We developed a computational framework to automatically detect multimodal expression distributions within well-defined disease populations. Our analysis of small blue round cell tumors (including rhabdomyosarcoma, synovial sarcoma, neuroblastoma, Ewing sarcoma and osteosarcoma) discovered a significant number of multimodally expressed genes. Multimodally expressed genes were associated with proliferative signaling, extracellular matrix organization, and immune signaling pathways across cancer types. Expression signatures correlated with differences in patient outcomes for MYCN non-amplified neuroblastoma, osteosarcoma, and synovial sarcoma. The low mutation rate in pediatric cancers has led some to suggest that pediatric cancers are less immunogenic. However, our analysis suggests that immune infiltration can be identified across small blue round cell tumors. Thus, further research into modulating immune cells for patient benefit may be warranted.

The transcription factor CREB (cAMP Response Element Binding Protein) is overexpressed in the majority of acute myeloid leukemia (AML) patients, and this is associated with a worse prognosis. Previous work revealed that CREB overexpression augmented AML cell growth, while CREB knockdown disrupted key AML cell functions in vitro. In contrast, CREB knockdown had no effect on long-term hematopoietic stem cell activity in mouse transduction/transplantation assays. Together, these studies position CREB as a promising drug target for AML. To test this concept, a small molecule inhibitor of CREB, XX-650-23, was developed. This molecule blocks a critical interaction between CREB and its required co-activator CBP (CREB Binding Protein), leading to disruption of CREB-driven gene expression. Inhibition of CBP-CREB interaction induced apoptosis and cell cycle arrest in AML cells, and prolonged survival in vivo in mice injected with human AML cells. XX-650-23 had little toxicity on normal human hematopoietic cells and tissues in mice. To understand the mechanism of XX-650-23, we performed RNA-seq, ChIP-seq and Cytometry Time of Flight with human AML cells. Our results demonstrate that small molecule inhibition of CBP-CREB interaction mostly affects apoptotic, cell cycle, and survival pathways, which may represent a novel approach for AML therapy.

Targeted gene panel sequencing has become increasingly common in the management of pediatric cancer patients. For some patients, these cancer gene panel tests have identified clinically actionable findings, but for many pediatric patients, no actionable alterations are identified. This is in part due to the low mutational burden of pediatric malignancies; thus, an unbiased approach may shed light on potentially actionable findings. To accomplish this, we examined the feasibility and utility of whole-genome sequencing (WGS) and RNA sequencing (RNAseq) in the management of high-risk pediatric oncology patients. We describe our experience with a cohort of over 100 high-risk pediatric oncology patients, with a combination of solid tumors, brain tumors, and hematologic malignancies. The majority of patients were deemed high-risk due to relapsed/refractory disease. A second group of patients was defined as high-risk at time of initial diagnosis due to the presence of metastatic disease, an estimated overall survival of less than 50%, a rare tumor, an undifferentiated tumor, or prior history of another malignancy. When possible, multiple samples from an individual patient were collected (i.e., specimens at biopsy, resection, relapse, and/or from metastatic sites) to allow for evaluation of inter- and intratumoral heterogeneity. Close to 200 tumor samples were available for analysis using WGS and/or RNAseq analysis. Somatic DNA samples were sequenced to an average depth of 60X and germline samples to 30X. WGS samples were analyzed for SNVs, structural rearrangements (SVs), copy-number alterations (CNAs), and mutational signatures. RNAseq was performed to a depth of at least 20 million paired-end reads for each sample. These samples were analyzed to identify known and novel gene-fusions, measure allele specific expression of SNVs, and perform gene-expression outlier analysis. Expression of variants (SNV/SV) identified using WGS were confirmed using RNAseq. For gene expression outliers detected using RNAseq, the WGS data were used to predict possible mechanisms for the aberrant expression (such as CNA, gene fusions, or promoter hijacking). This analysis suggests that WGS and RNAseq analysis is feasible in a clinical setting and can reliably identify variants reported on gene panel tests. Furthermore, the use of WGS/RNAseq results in additional clinically informative findings while also enabling novel research to further advance our understanding of these rare and highly aggressive pediatric malignancies. Citation Format: Avanthi T. Shah, Marcus R. Breese, Alex G. Lee, Henry J. Martell, Bogdan Tanasa, Stanley G. Leung, Aviv Spillingeer, Heng-Yi Liu, Inge Behroozfard, Phuong Dinh, Florette K. Hazard, Soo-Jin Cho, Arun Rangaswami, Norman J. Lacayo, Sheri L. Spunt, Tabitha Cooney, Jennifer G. Michlitsch, Anurag K. Agarwaal, Alejandro Sweet-Cordero. Integrative analysis of whole-genome and RNA sequencing in high-risk pediatric malignancies [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B20.

Pediatric cancers have a very different genomic profile from adult cancers. For example, single-nucleotide variants (SNVs) are common drivers in many adult cancers but are not as prevalent in many pediatric cancers. In particular, a large subset of solid tumors is driven by copy number alterations and structural variations (SV), including translocation-induced gene fusions. These SVs can be difficult to profile using commercial sequencing panels or DNA-only sequencing. However, by integrating the results from RNAseq and whole-genome sequencing (WGS), we can start to better understand the mechanisms behind these rare malignancies. The primary results of WGS analysis are SNVs, SVs, or CNAs. Each of these somatic classes of variation can be further refined using genome annotation tools and databases to prioritize variants and identify likely drivers. However, if one looks at DNA data alone, it is impossible to validate these predictions. We may identify a known oncogenic SNV, but due to a complex rearrangement, that particular SNV may not be expressed. By including RNA in the analysis, we now have the ability to assess how functional these variants truly are. With SNVs, we examine the expression of a variant in RNA, including a comparison of the allele frequencies. For both somatic and germline variants, we use RNAseq to identify allele-specific expression patterns. We also use RNAseq to confirm the expression of predicted gene fusions, and the functional significance of copy number gains or losses, even at modest levels. In tumor profiling, RNAseq is primarily used for the identification of gene fusions and gene expression outliers. At the present, both of these techniques produce a high degree of false positives. However, due to the potential for complex rearrangements, RNAseq can be used to identify gene fusions that may be missed by DNA specific methods. For example, RNAseq can effectively “rescue” the results of WGS that may have identified individual (non-viable) SVs but missed the overall combination of rearrangements that would result in a viable fusion. In a single-patient analysis, outlier expression is quite difficult. Each gene can have a wide range of “normal” expression, which is tissue specific. However, gene expression outliers can be validated with WGS analysis (CNA, SV, promoter hijacking, or SNVs in transcription factor binding sites) to prioritize outlier genes based upon those that can be mechanistically explained with a somatic (DNA) variant. Here we will describe the techniques and analysis pipelines used for the integrated analysis of RNA and DNA in a cohort of rare and high-risk pediatric cancer patients. RNAseq can provide a functional output whereas WGS can be used to provide a potential mechanism. Importantly, using both techniques lets us capture signal that may be otherwise missed with only one method. Together, we believe that the integration of RNA and DNA produces a more comprehensive analysis to better understand the mechanisms of each individual cancer. Citation Format: Marcus R. Breese, Alex G. Lee, Avanthi T. Shah, Henry J. Martell, Alejandro Sweet-Cordero. Methods for integrated analysis of RNA and DNA sequencing in pediatric cancers [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B03.

Osteosarcoma (OS) is a highly aggressive cancer that has had no new treatments options in over 30 years. OS is a heterogeneous disease that is characterized by widespread and recurrent somatic copy-number alterations (SCNAs) with relatively few recurrent point mutations. Our laboratory has recently published that SCNAs contain key oncogenic drivers that can be used to identify patient-specific candidates for targeted therapies (Sayles, Breese, et al., Cancer Discovery Jan. 2019). Using patient-derived tumor xenografts (PDX), we demonstrated that targeting of patient-specific oncogenes within SCNAs leads to significant decrease in tumor burden. However, no single-agent therapy was able to regress tumors completely, suggesting that combination therapies would be required for disease management. In order to assess the applicability of our PDX models to the patient tumor and the stability of the oncogenes within SCNAs, we performed whole-genome sequencing (WGS). We observed that SCNAs are highly stable across samples from the same patient in addition to multiple PDX passages and PDX-derived cell lines, highlighting the equivalence between the PDX models and their derived cell lines to the human disease. This allows us to use the PDX cell lines as a surrogate for the identification of combination drug therapies that may be of benefit in OS. Currently, we have generated 6 PDX cell lines that encompass the most common SCNAs observed in patients, including MYC, CCNE1, and CDK4 gain and alterations in the PI3K/PTEN pathway. We have performed a single-agent drug screen with 38 agents and have identified several efficacious compounds, including HDAC inhibitors and cell cycle and Wee1 inhibitors. We also observed a differential response between PDX cell lines to various chemotherapeutics, including gemcitabine, paclitaxel, and SN-38. We are currently testing combination drug therapies in vitro and will validate using our PDX xenografts in vivo. While these experiments are still ongoing, we can report that MYC-driven OS PDX xenografts show a striking resensitization to cisplatin after AURKB inhibitor (barasertib) pretreatment. We have 2 aggressive PDX models with high MYC amplification generated from metastatic lesions. These PDX models are resistant to cisplatin, which is part of the standard of care. We treated these PDX with barasertib and then with cisplatin for two cycles. This resulted in a decrease in tumor volume for the combination therapy compared to vehicle or either single agent alone. Additionally, we observed retention of the platinum adduct 24 hrs after cisplatin dosing only when tumors were pretreated with barasertib. Further work is needed to assess the mechanism of this synergy and whether it can be of use in other SCNA-driven OS and to identify other possible combination therapies that could be of importance in this disease. Citation Format: Leanne C. Sayles, Marcus R. Breese, Henry Martell, Alex G. Lee, Stanley Leung, Avanthi T. Shah, E. Alejandro Sweet-Cordero. Targeted drug therapies for osteosarcoma [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr A45.

Gliomatosis peritonei is a rare pathologic finding that is associated with ovarian teratomas and malignant mixed germ cell tumors. The occurrence of gliomatosis as a mature glial implant can impart an improved prognosis to patients with immature ovarian teratoma, making prompt and accurate diagnosis important. We describe a case of recurrent immature teratoma in a 10-yr-old female patient, in which comparative analysis of the RNA sequencing gene expression data from the patient's tumor was used effectively to aid in the diagnosis of gliomatosis peritonei.

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

Chromosomal translocation that results in fusion of the genes encoding RNA-binding protein EWS and transcription factor FLI1 (EWS-FLI1) is pathognomonic for Ewing sarcoma. EWS-FLI1 alters gene expression through mechanisms that are not completely understood. We performed RNA sequencing (RNAseq) analysis on primary pediatric human mesenchymal progenitor cells (pMPCs) expressing EWS-FLI1 in order to identify gene targets of this oncoprotein. We determined that long noncoding RNA-277 (Ewing sarcoma-associated transcript 1 [EWSAT1]) is upregulated by EWS-FLI1 in pMPCs. Inhibition of EWSAT1 expression diminished the ability of Ewing sarcoma cell lines to proliferate and form colonies in soft agar, whereas EWSAT1 inhibition had no effect on other cell types tested. Expression of EWS-FLI1 and EWSAT1 repressed gene expression, and a substantial fraction of targets that were repressed by EWS-FLI1 were also repressed by EWSAT1. Analysis of RNAseq data from primary human Ewing sarcoma further supported a role for EWSAT1 in mediating gene repression. We identified heterogeneous nuclear ribonucleoprotein (HNRNPK) as an RNA-binding protein that interacts with EWSAT1 and found a marked overlap in HNRNPK-repressed genes and those repressed by EWS-FLI1 and EWSAT1, suggesting that HNRNPK participates in EWSAT1-mediated gene repression. Together, our data reveal that EWSAT1 is a downstream target of EWS-FLI1 that facilitates the development of Ewing sarcoma via the repression of target genes.

Clinical use of gene-panel based sequencing has become increasingly common in the management of pediatric cancer patients. For many patients, gene-panel tests have identified clinically actionable findings. However, highly targeted approaches will miss unanticipated (but potentially clinically meaningful) or novel alterations. In diseases with unknown or complex etiologies, including many pediatric high-risk and solid tumors, an unbiased approach may yield more actionable findings. To accomplish this, we examined the feasibility and utility of whole genome sequencing (WGS) and RNA sequencing (RNAseq) in the management of high-risk pediatric oncology patients. Here we describe our experience with an expanded cohort of over 100 high-risk pediatric oncology patients, with a combination of solid tumors, brain tumors, and leukemia/lymphomas represented. The majority of patients were deemed high-risk due to relapsed/refractory disease. An additional group of patients were defined as high-risk at time of initial diagnosis due to metastatic disease, a rare tumor, prior history of another cancer type, an undifferentiated tumor, or less than 50% estimated overall survival. WGS (tumor/germline) and RNAseq were used to characterize available samples and compared to results from panel testing for each patient (performed as part of their clinical evaluation). When possible, multiple samples from an individual patient were collected (i.e. specimens obtained at biopsy, resection, relapse, and/or from metastatic sites). Somatic DNA samples were sequenced to an average depth of at least 60X and germline samples to at least 30X. RNAseq was performed to a depth of at least 20 million paired-end reads for each sample. WGS samples were analyzed for single nucleotide variants (SNVs), structural rearrangements (SV), and copy-number alterations (CNA). RNAseq samples were analyzed to identify known and novel gene-fusions, to measure allele specific expression of SNVs, and to perform gene-expression outlier analysis. Expression of variants (SNV/SV) identified using WGS were confirmed using RNAseq. For gene expression outliers detected using RNAseq, the WGS data was used to predict possible mechanisms for the aberrant expression (such as CNA, gene fusions, or promoter hijacking). This analysis suggests that WGS and RNAseq analysis is feasible in a clinical setting and can reliably identify variants reported on gene panel tests. However, the use of WGS/RNAseq resulted in additional clinically informative findings while also enabling novel research to further advance our understanding of these rare and highly aggressive pediatric malignancies. Citation Format: Marcus R. Breese, Avanthi T. Shah, Alex G. Lee, Bogdan Tanasa, Stanley G. Leung, Aviv Spillinger, Heng-Yi Liu, Inge Behroozfard, Phuong Dinh, Florette K. Hazard, Arun Rangaswami, Sheri L. Spunt, Norman J. Lacayo, Tabitha Cooney, Jennifer G. Michlitsch, Anurag K. Agrawal, E. Alejandro Sweet-Cordero. Integrative analysis of whole-genome and RNA sequencing in high-risk pediatric malignancies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3665.

Osteosarcoma (OS) is a highly aggressive cancer that has had no new treatments options in over 30 years. OS is a heterogeneous disease which is characterized by widespread and recurrent somatic copy-number alterations (SCNAs) with relatively few recurrent point mutations. We have previously reported that SCNAs contain key oncogenic drivers that can be used to identify patient-specific candidates for targeted therapies (Sayles and Breese, et al. Cancer Discovery 2018). Using patient-derived tumor xenografts (PDX), we demonstrated that targeting of patient-specific oncogenes within SCNAs leads to significant decrease in tumor burden. However, no single agent therapy was able to regress tumors completely suggesting that combination therapies would be required for disease management. In order to assess the applicability of OS PDX models to the patient tumor and the stability of the oncogenes within SCNAs, we preformed whole genome sequencing (WGS). We observed that SCNAs are highly stable across samples from the same patient in addition to multiple PDX passages and PDX derived cells lines, highlighting the equivalence between the PDX models and their derived cell lines to the human disease. This allows us to use the PDX cell lines as a surrogate for the identification of combination drug therapies that may be of benefit in OS. Currently, we have generated six PDX cell lines that encompass the most common SCNAs observed in patients including MYC, CCNE1 and CDK4 gain and alterations in the PI3K/PTEN pathway. We have performed single agent drug screens in these cell lines and have identified heterogeneous responses as would be anticipated by the genomic diversity observed in OS. We are currently testing combination drug therapies and will validate using the PDX xenografts in vivo. We have found that MYC driven OS PDX cell lines and PDX xenografts show a striking re-sensitization to cisplatin after AURKB inhibitor (barasertib) pretreatment. We have two PDX and derived cell lines that were generated from highly aggressive metastatic disease. Both of these PDX have high MYC amplification and were resistant to cisplatin, which is part of the standard of care. We pretreated the PDX cell lines for 24hrs with barasertib then added cisplatin and saw a synergistic effect in vitro. Further studies in the PDX model demonstrated a decrease in tumor volume for the combination therapy compared to vehicle or either single agent alone. Additionally, we observed retention of the platinum adduct 24 hrs after cisplatin dosing only when tumors were pretreated with barasertib. Further work is needed to assess the mechanism of this synergy and whether it can be of use in other SCNA driven OS and to identify other possible combination therapies that could be of importance in this disease. Citation Format: Leanne C. Sayles, Amanda Koehne, Kieren Marini, Alex G. Lee, Stanley G. Leung, Avanthi T. Shah, Marcus R. Breese, E. Alejandro Sweet-Cordero. Targeted drug therapies for osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2880.

DDX3X encodes a DEAD-box family RNA helicase (DDX3) commonly mutated in medulloblastoma, a highly aggressive cerebellar tumor affecting both children and adults. Despite being implicated in several facets of RNA metabolism, the nature and scope of DDX3's interactions with RNA remain unclear. Here, we show DDX3 collaborates extensively with the translation initiation machinery through direct binding to 5'UTRs of nearly all coding RNAs, specific sites on the 18S rRNA, and multiple components of the translation initiation complex. Impairment of translation initiation is also evident in primary medulloblastomas harboring mutations in DDX3X, further highlighting DDX3's role in this process. Arsenite-induced stress shifts DDX3 binding from the 5'UTR into the coding region of mRNAs concomitant with a general reduction of translation, and both the shift of DDX3 on mRNA and decreased translation are blunted by expression of a catalytically-impaired, medulloblastoma-associated DDX3R534H variant. Furthermore, despite the global repression of translation induced by arsenite, translation is preserved on select genes involved in chromatin organization in DDX3R534H-expressing cells. Thus, DDX3 interacts extensively with RNA and ribosomal machinery to help remodel the translation landscape in response to stress, while cancer-related DDX3 variants adapt this response to selectively preserve translation.

Clinical use of gene-panel based tumor sequencing has expanded exponentially over the past few years. While in some cases this molecular testing identifies clinically actionable findings, these highly targeted approaches may miss unanticipated, clinically meaningful or novel alterations. In cancers with poorly understood etiologies, including many pediatric solid or high-risk tumors, an unbiased approach may prove more useful. We sought to explore the feasibility and utility of whole-genome sequencing (WGS) and RNA sequencing (RNA-seq) in comparison to commercially available targeted gene-panel testing in pediatric oncology. Herein we describe our experience with an initial cohort of 58 high-risk pediatric oncology patients (37 solid tumors, 11 brain tumors, and 10 leukemia/lymphomas). The majority of patients (n=40) had relapsed/refractory disease. An additional eighteen patients were defined as high-risk at time of initial diagnosis due to metastatic disease, a rare tumor, prior history of another cancer type, an undifferentiated tumor, or less than 50% survival. A total of 102 samples were obtained from these 58 patients, with 70 samples originating at the primary sites of disease and 32 samples from metastatic sites. Thirty-one samples were chemotherapy/radiation therapy naïve. A combination of WGS and RNA-seq were used to characterize available samples and compared to results from panel testing for that patient (performed as part of their clinical evaluation). Where possible, fresh frozen tissue (FFT) samples were obtained during clinically indicated surgical procedures. When FFT was unavailable, formalin-fixed, paraffin-embedded (FFPE) samples were used. When possible, multiple samples from an individual patient were collected (i.e., specimens obtained at biopsy, resection, relapse, and/or from metastatic sites). Germline DNA was isolated from peripheral blood, with the exception of leukemia patients where saliva was used. Somatic DNA samples were sequenced to an average depth of at least 60X and germline samples to at least 30X. Somatic RNA-seq was performed to a depth of at least 20 million paired-end reads for each sample. In-house as well as published tools and algorithms were used to analyze DNA samples for single-nucleotide variants (SNVs), structural rearrangements, and copy-number alterations. RNA samples were analyzed to identify known and novel gene fusions, to measure allele specific expression of SNVs, and to perform gene-expression outlier analysis. Consistent with previous observations, the mutational burden across pediatric cancers was low. While common mutations were identified, there was a long tail of mutations that occurred at a low frequency. As anticipated, samples obtained post-chemotherapy had a higher mutational burden than treatment-naïve samples. TP53 was the most commonly mutated gene, but we also identified SNVs in other genes commonly mutated in cancer, such as ASXL1, NOTCH2, and RB1. Other novel recurring variants were discovered, further analysis of which is ongoing. Canonical gene fusions were detected in 8/8 patients as well as potentially novel fusions, confirmation of which is also ongoing. In nearly all patients, variants identified by gene panels were also identified through WGS/RNA-seq analysis; however, in 2 instances, variants reported by gene panel testing were reclassified as germline using our tumor/normal WGS analysis. These results indicate that integrated WGS and RNA-seq analysis is feasible in the clinical setting and can reliably identify variants reported on commercially available gene panel testing. However, this approach also resulted in additional clinically relevant findings and allows for novel discovery that will further advance our understanding of these rare and highly aggressive pediatric malignancies. Citation Format: Marcus R. Breese, Avanthi T. Shah, Bogdan Tanasa, Alex G. Lee, Stanley G. Leung, Aviv Spillinger, Heng-Yi Liu, Florette K. Hazard, Alejandro Sweet-Cordero. Integrative analysis of whole-genome and RNA sequencing in high-risk pediatric malignancies [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 B25.

A promising tool for noninvasive disease monitoring is analysis of circulating tumor DNA (ctDNA). Healthy individuals carry 1-10 ng/ml of cell-free DNA (cfDNA) in the blood; in oncology patients, ctDNA, which is released from tumor cells, comprises a fraction of the cfDNA and carries tumor-specific alterations, such as mutations, translocations, and copy number alterations. Most ctDNA assays lack robust translocation detection capabilities, since they are designed for adult cancers, which are commonly characterized by mutations and copy number alterations. Even assays that are designed specifically for translocation detection have inherent limitations. They are often PCR-based with laborious methods. First, the patient’s primary tumor sample is sequenced to determine the unique sequence across the translocation breakpoint. This is followed by design of patient-specific primers that can only be used for that individual patient. We sought to design an off-the-shelf, broadly applicable ctDNA assay for translocation detection across pediatric Ewing sarcoma (ES), osteosarcoma (OS), rhabdomyosarcoma (RMS), and synovial sarcoma (SS). Recent work by our collaborators at Stanford University led to the development of CAncer Personalized Profiling by deep Sequencing (CAPP-Seq), a method capable of ultraspecific and ultrasensitive detection of ctDNA. Utilizing COSMIC and TCGA data, recent sequencing publications defining the landscape of pediatric sarcomas, and our own in-house sequencing data, we designed a pediatric sarcoma CAPP-Seq selector. This selector is comprised of biotinylated oligonucleotides that tile across the introns where translocation breakpoints occur in these pediatric sarcomas. The selector is applied to a sequencing library prepared from patient cfDNA to enrich for the genomic regions of interest via hybrid capture. The resulting enriched library undergoes next-generation sequencing to allow for detection and quantification of circulating tumor DNA. We have isolated cfDNA from pediatric sarcoma patients and found that their cfDNA levels are higher than levels found in adult oncology patients and healthy individuals, likely due to a large fraction of contributing ctDNA. We have applied our selector to pretreatment plasma samples from 5 EWS patients, 2 OS patients, 4 RMS patients, and 1 SS patient. We detected translocations in 10/12 of these samples. Tumor was available for 7/12 of these patients, and we were able to confirm our plasma results by whole-genome sequencing of the tumor, as a validation of our findings. Additionally, we have applied our selector to serial plasma samples collected over the course of treatment and found that ctDNA levels correlate with clinical status. We have detected translocations at allelic frequencies Citation Format: Avanthi Tayi Shah, Tej D. Azad, Jake J. Chabon, Marcus Breese, Bogdan Tanasa, Aviv Spillinger, Stanley G. Leung, Maximilian Diehn, Ash A. Alizadeh, E. Alejandro Sweet-Cordero. Quantitating circulating tumor DNA in translocation-positive sarcoma patients using CAPP-Seq [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 B49.

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.

Several recent studies (including BASIC3, iCAT, INFORM, PEDS-MIONCOSEQ) have used whole exome sequencing (WES) and RNA-seq in order to identify targetable chromosomal alterations in a large variety of pediatric cancers. Few studies have attempted to evaluate whether a more comprehensive approach including WGS and RNA-seq could be used to identify novel events relevant to the pathogenesis of advanced pediatric cancer. We analyzed a total of 59 patients (37 solid tumors, 11 brain tumors, and 10 leukemia/lymphomas) to determine the feasibility of using whole-genome sequencing (WGS) technology in conjunction with RNA-seq in order to identify actionable/druggable alterations in the pediatric cancer genomes. WGS analysis has been performed on 75 samples, that were collected from 45 patients, either at diagnosis or at relapse. For WGS analysis of germline-tumor pairs, after performing the sequence alignment with BWA-MEM to gender-specific hg38 genomes, we have used and verified a set of computational methods: 1) MuTect2 for SNV calling, 2) cn.mops for CNV calling, 3) DELLY and LUMPY for SV calling. Here we present our findings on the sets of SNV, CNV, SV, and gene fusions that we have identified by WGSA and RNA-seq, respectively, with a particular emphasis on the druggable alterations, and on the tumor response in the murine PDX models of the pediatric cancers. Consistent with previous observations, the mutational burden across pediatric cancers was low. While common mutations were identified, there was a long-tail of mutations that occurred at a low frequency. As anticipated, samples obtained post-chemotherapy had a higher mutational burden than treatment naive samples. TP53 was the most commonly mutated gene, but we also identified SNVs in other genes commonly mutated in cancer, such as ASXL1, NOTCH2, and RB1. Other novel recurring variants were discovered, further analysis of which is ongoing. Our results indicate that integrated WGS and RNA-seq analysis is feasible in the clinical setting and can reliably identify variants reported on commercially available gene panel testing. However, this approach also resulted in additional clinically relevant findings and allows for novel discovery that will further advance our understanding of these rare and highly aggressive pediatric malignancies. Citation Format: Bogdan Tanasa, Alex Lee, Marcus Breese, Avanthi Shah, Stan Leung, Heng-Yi Liu, Aviv Spillinger, Kimberly Hazard, Arun Rangaswami, Sheri Spunt, Norm Lacayo, Tabitha Cooney, Eric Alejandro Sweet-Cordero. Whole genome sequence analysis informs precision medicine of pediatric cancers [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 2075.

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.

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

Early metastasis to the lungs is a cardinal feature of osteosarcoma (OS), and complications from metastatic disease remain the most common cause of cancer-related death. Despite the prevalence of metastasis in OS, the pathogenesis is poorly understood. We have established a collection of 16 patient-derived xenografts (PDX) from human OS tumors, both from the primary site as well as metastasis. Our collection includes 9 diagnostic biopsies from primary site tumors, 2 primary tumor resections, 3 lung metastases, and 1 ascites fluid metastasis. Gene expression analysis of an initial set of 5 PDX models (3 metastases, 2 primaries) has been completed. A more extensive analysis of all 16 models by RNAseq and WGS is currently underway. Preliminary gene expression analysis identified a significant number of genes differentially expressed between metastatic samples and non-metastatic samples. This list included genes associated with cell adhesion and motility such as MEGF10, genes associated with endochondral ossification and bone remodeling such as RANKL, and genes associated with deposition of extracellular matrix (ECM) such as COL21A. Another candidate gene, ENPP1, is responsible for mineralization of the ECM and has been implicated in breast cancer metastasis to bone. We have validated differential expression of a number of these genes in independent samples of metastatic OS. We are currently using small hairpin RNA (shRNA), CRISPR, and overexpression vectors to knockdown, silence, and overexpress ENPP1 and other candidate genes in OS cell lines. Using in vitro migration and invasion assays as well as intravenous injection and orthotopic mouse models, we are characterizing the contribution of candidate genes to the metastatic propensity of OS. Citation Format: Amanda L. Koehne, Leanne C. Sayles, Marcus R. Breese, Dedeepya Vaka, Alejandro Sweet-Cordero. Characterization of the genomic landscape of osteosarcoma metastasis. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Pediatric Cancer Research: From Mechanisms and Models to Treatment and Survivorship; 2015 Nov 9-12; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(5 Suppl):Abstract nr A35.

Osteosarcoma (OS) is an aggressive pediatric bone malignancy that affects 400 children per year in the United States. OS is characterized by genomic instability and numerous copy number alterations (CNA). We hypothesized that CNA may be drivers of OS and that targeting cancer genes with CNAs may be a novel approach for treatment of OS. We have established a robust approach for generation of patient-derived xenografts (PDX) from patients with OS. To date, 15 PDX have been established from OS patients. Using whole-genome sequencing (WGS), we have identified possible target CNAs for individual patients and are currently testing them in their corresponding PDX. In two patients, an amplification in c-myc suggested possible susceptibility to the BRD4 inhibitor JQ1 or the CDK9 inhibitor AT7519. In a third patient sample, amplification of Cyclin D and Cyclin E in the setting of wild-type Rb suggested responsiveness to a CDK inhibitor. A fourth patient had a FOXM1 amplification which suggests a vulnerability to Palbociclib, a CDK4/6 specific inhibitor. This patient sample also had an Aurora kinase B amplification, suggesting susceptibility to inhibition of this kinase as a therapeutic approach. We treated the corresponding PDX with the drug predicted to target the patient sample based on CNA. In all cases, treatment of the PDX with the drugs predicted show a significant reduction in tumor growth compared to vehicle alone or to the drugs predicted for the other patient CNAs. As a follow up we are currently submitting several more patient samples and paired PDX for WGS as well as RNAseq to determine other potential targeted therapeutics based on CNA. In summary, our work suggests that WGS can be used to identify potential novel therapies for patients with OS. Further work will be needed to determine whether response in PDX models correlates with clinical response in patients. Citation Format: Leanne Sayles, Marcus Breese, E. Alejandro Sweet-Cordero. Genomic analysis of osteosarcoma for identification of targeted therapies. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Pediatric Cancer Research: From Mechanisms and Models to Treatment and Survivorship; 2015 Nov 9-12; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(5 Suppl):Abstract nr B28.

Osteosarcoma (OS) is an aggressive bone malignancy affecting approximately 400 pediatric patients in the United States annually. Compared with other pediatric cancers, OS has a low 5-year overall survival rate. There are few treatment options for patients that progress on standard therapy, making it important to identify new therapeutic targets for these high-risk patients. At the genomic level, OS is characterized by significant genomic instability, resulting in numerous copy number alterations (CNA) and structural variations (SV). Unfortunately, many of the CNAs and SV events are non-recurrent, making each disease highly patient-specific. We hypothesized that CNAs may be drivers of OS and that we could use patient-specific CNA profiles to identify actionable targets in OS. In order to test this in a preclinical setting, we have developed a robust program for generating and maintaining patient-derived xenografts (PDX) from patients with OS. In a pilot study of 3 patients, we used a combination of tumor/normal whole-genome sequencing (WGS) and commercial gene panel testing to identify potentially druggable targets using CNA. For samples tested with WGS, gene-level CNA was assessed for a number of clinically actionable genes. For each gene, CNA was determined using the normalized ratio of sequencing reads mapped to the gene in the tumor versus the normal sample. The degree of CNA was used to help prioritize potential targets. For the commercially tested samples, genes were either reported as amplified or not. Using these results to inform target selection, we treated each PDX with a drug matched to its corresponding CNA predicted target. In each sample, we saw a significant reduction in the growth rate of the PDX compared to vehicle or a non-matched drug. This suggests that using the patient-specific CNAs to identify drug targets may be an effective strategy in the treatment of OS. Citation Format: Marcus R. Breese, Leanne C. Sayles, Alejandro Sweet-Cordero. Using copy number alterations to identify targeted therapies in a preclinical model of osteosarcoma. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr 07.

Osteosarcoma (OS) is an aggressive pediatric bone malignancy that affects 400 children per year in the United States. It has one of the lowest 5 yr. survival rates of any pediatric cancer. OS is characterized by genomic instability and numerous copy number alterations (CNA). We hypothesized that CNA may be drivers of OS and that targeting cancer genes with CNAs may be a novel approach for treatment of OS. We have established a robust approach for generation of patient-derived xenografts (PDX) from patients with OS. To date, 12 PDX have been established from OS patients. Using whole-genome sequencing (WGS), we have identified possible target CNAs for individual patients and are currently testing them in their corresponding PDX. In one patient, an amplification in c-myc suggested possible susceptibility to the bromodomain inhibitor JQ1. In a second patient sample, amplification of Cyclin D1 in the setting of p16 loss and wild-type Rb suggested responsiveness to a CDK4/6 specific inhibitor. This patient sample also has an Aurora kinase B amplification, suggesting susceptibility to inhibition of this kinase as a therapeutic approach. We treated the corresponding PDX with the drug predicted to target the patient sample based on CNA. In one case, JQ1 treatment inhibited tumor growth in the PDX generated from the patient sample with c-myc amplification. In the second case, Aurora kinase B inhibition arrested tumor growth in the PDX harboring the Aurora kinase B amplification. We are currently testing whether CDK4/6 inhibition is sufficient to inhibit tumor growth as predicted by WGS. As a follow up we are currently submitting several more patient samples and paired PDX for WGS as well as RNAseq to determine other potential targeted therapeutics based on CNA. In summary, our work suggests that WGS can be used to identify potential novel therapies for patients with OS. Further work will be needed to determine whether response in PDX models correlates with clinical response in patients. Citation Format: Leanne C. Sayles, Marcus Breese, Alejandro Sweet-Cordero. Copy number alterations identify targeted therapies in preclinical models of osteosarcoma. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 502. doi:10.1158/1538-7445.AM2015-502

Ewing's sarcoma is a highly aggressive tumor characterized by a translocation between members of the FET family of RNA binding proteins and one of several ETS transcription factors, with the most common translocation being EWS-FLI1. Like many oncogenic translocations, EWS-FLI1 leads to changes in gene expression through mechanisms that are not completely understood. We performed RNA sequencing analysis on human mesenchymal progenitor cells (MPCs) expressing EWS-FLI1, which are thought to be the cell of origin of Ewing's sarcoma. This analysis identified lnc277 as a previously uncharacterized long non-coding RNA upregulated by EWS-FLI1 in MPCs. Expression of lnc277 in Ewing's sarcoma cell lines requires EWS-FLI1. In addition, inhibiting the expression of lnc277 diminished the ability of Ewing's sarcoma cell lines to proliferate and form soft agar colonies. Using RNA sequencing and shRNA knockdown, we defined the transcriptional changes induced by EWS-FLI1 and lnc277. This analysis revealed that both EWS-FLI1 and lnc277 repress far more genes that they induce and that a large fraction of EWS-FLI1 repressed targets are also modulated by lnc277. Thus, lnc277 is an oncogenic long non-coding RNA downstream of EWS-FLI1 that facilitates the formation of Ewing's sarcoma via the repression of target genes. Citation Format: Michelle Marques, David Simpson, Ron Chen, Dedeepya Vaka, Marcus Breese, Allayne Brunner, Rob West, Alejandro Sweet-Cordero. The long noncoding RNA lnc277 mediates a repressive gene signature in Ewing's sarcoma. [abstract]. In: Proceedings of the AACR Special Conference on Pediatric Cancer at the Crossroads: Translating Discovery into Improved Outcomes; Nov 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2013;74(20 Suppl):Abstract nr A31.

Introduction Chromosomal rearrangements involving the MLL gene occur in both primary and treatment-related leukemias and convey a poor prognosis. Infants with acute lymphoblastic leukemia (ALL) containing an MLL translocation have a 5-year event free survival of 35% as compared to 69% for infants with germline MLL (Kang et al., Blood 2012). While animal models of MLL-AF9 translocations typically found in adult AML have improved our understanding of the role of MLL translocations in leukemia pathogenesis, modeling the MLL-AF4 translocation commonly found in infant ALL has proven difficult. We hypothesized that recent advances in genome engineering would facilitate induction of specific MLL translocations in primary hematopoietic stem cells to recapitulate the initiating event that leads to infant leukemia. A better understanding of the pathogenesis of the MLL-AF4 translocation will allow for the development of targeted therapies to improve outcome in MLL-rearranged infant leukemia. Methods Transcription activator-like effector nucleases (TALENs) were designed to recognize a patient-specific translocation site within the break point cluster region of the MLL gene and the AF4 gene, respectively. These TALEN pairs were then co-expressed in either K562 cells or primary human CD34+ cells isolated from umbilical cord blood to induce patient-specific double strand breaks. Traditional PCR, nested PCR, and high throughput next generation sequencing were used to detect MLL-AF4 translocations, reciprocal AF4-MLL translocations, as well as other MLL translocations. Clonal analysis was performed to determine the translocation efficiency resulting from two site-specific double strand breaks. Primary cells were maintained in long-term culture to assess for potential survival advantage conferred by the translocations. Finally, primary human CD34+ cells with an induced MLL-AF4translocation were transplanted into NSG mice to assess for leukemic potential. Results We successfully generated TALENs that induce a patient-specific double strand break within the breakpoint cluster regions of the endogenous MLL and AF4 genes. Co-expression of the MLL and AF4 TALENs in K562 cells as well as in primary human hematopoietic stem cells isolated from umbilical cord blood resulted in de novo MLL-AF4 translocations as well as the reciprocal AF4-MLL translocation. The MLL-AF4 translocation efficiency was appreciably higher in K562 cells (10-4) compared to primary hematopoietic stem cells (10-5). Long-term culture of the primary human hematopoietic cells showed an increase in the frequency of the MLL-AF4 translocation-positive cells, suggesting a survival advantage for the cells containing the translocation. These cells were subsequently transplanted into NSG mice to assess their ability to induce leukemia. These studies are currently ongoing. Conclusions Advances in genome engineering have provided the tools necessary to study leukemia pathogenesis in a prospective manner. We have designed an experimental system to recapitulate the process of leukemogenesis. TALENs are effective to induce a specific MLL translocation in primary human hematopoietic stem cells with minimal off target effects, under the control of the endogenous promoter, and in the presence of the reciprocal translocation. This system will allow us to prospectively investigate the downstream effects of this initiating event on gene expression, epigenetic regulation, and genome stability in order to understand the key steps critical for the pathogenesis of MLL-rearranged leukemias. Disclosures: No relevant conflicts of interest to declare.

Background Alternative splicing increases proteome diversity by expressing multiple gene isoforms that often differ in function. Identifying alternative splicing events from RNA-seq experiments is important for understanding the diversity of transcripts and for investigating the regulation of splicing. Results We developed Alt Event Finder, a tool for identifying novel splicing events by using transcript annotation derived from genome-guided construction tools, such as Cufflinks and Scripture. With a proper combination of alignment and transcript reconstruction tools, Alt Event Finder is capable of identifying novel splicing events in the human genome. We further applied Alt Event Finder on a set of RNA-seq data from rat liver tissues, and identified dozens of novel cassette exon events whose splicing patterns changed after extensive alcohol exposure. Conclusions Alt Event Finder is capable of identifying de novo splicing events from data-driven transcript annotation, and is a useful tool for studying splicing regulation.