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There is experimental and clinical data to indicate the contribution of immune-escape mechanisms in relapsed/refractory pediatric leukemia. Studies have shown the accumulation of mutations that translate to peptides containing tumor-specific epitopes (neoantigens). The effectiveness of neoantigen-based vaccines has been shown in several clinical trials in adults. Though the initial results are encouraging, this knowledge must be developed to account for the uniqueness of pediatric cancer biology. We have completed the initial proof-of-concept analysis on a high-risk pediatric leukemia specimen and identified usable neoantigen sequences. We describe this approach, including the bioinformatics method and experimental model to verify their function that can be further broadened for personalized neoantigen prediction and testing for the generation of anticancer vaccines against high-risk pediatric leukemias.

Overcoming replicative senescence is an essential step during oncogenesis, and the reactivation of TERT through promoter mutations is a common mechanism. TERT promoter mutations are acquired in about 75% of melanomas but are not sufficient to maintain telomeres, suggesting that additional mutations are required. We identified a cluster of variants in the promoter of ACD encoding the shelterin component TPP1. ACD promoter variants are present in about 5% of cutaneous melanoma and co-occur with TERT promoter mutations. The two most common somatic variants create or modify binding sites for E-twenty-six (ETS) transcription factors, similar to mutations in the TERT promoter. The variants increase the expression of TPP1 and function together with TERT to synergistically lengthen telomeres. Our findings suggest that TPP1 promoter variants collaborate with TERT activation to enhance telomere maintenance and immortalization in melanoma.

Cancer heterogeneity is a result of genetic mutations within the cancer cells. Their proliferation is not only driven by autocrine functions but also under the influence of cancer microenvironment, which consists of normal stromal cells such as infiltrating immune cells, cancer-associated fibroblasts, endothelial cells, pericytes, vascular and lymphatic channels. The relationship between cancer cells and cancer microenvironment is a critical one and we are just on the verge to understand it on a molecular level. Cancer microenvironment may serve as a selective force to modulate cancer cells to allow them to evolve into more aggressive clones with ability to invade the lymphatic or vascular channels to spread to regional lymph nodes and distant sites. It is important to understand these steps of cancer evolution within the cancer microenvironment towards invasion so that therapeutic strategies can be developed to control or stop these processes.

PURPOSE: Somatic variants in tumor necrosis factor receptor-associated factor 7 (TRAF7) cause meningioma, while germline variants have recently been identified in seven patients with developmental delay and cardiac, facial, and digital anomalies. We aimed to define the clinical and mutational spectrum associated with TRAF7 germline variants in a large series of patients, and to determine the molecular effects of the variants through transcriptomic analysis of patient fibroblasts.METHODS: We performed exome, targeted capture, and Sanger sequencing of patients with undiagnosed developmental disorders, in multiple independent diagnostic or research centers. Phenotypic and mutational comparisons were facilitated through data exchange platforms. Whole-transcriptome sequencing was performed on RNA from patient- and control-derived fibroblasts.RESULTS: We identified heterozygous missense variants in TRAF7 as the cause of a developmental delay-malformation syndrome in 45 patients. Major features include a recognizable facial gestalt (characterized in particular by blepharophimosis), short neck, pectus carinatum, digital deviations, and patent ductus arteriosus. Almost all variants occur in the WD40 repeats and most are recurrent. Several differentially expressed genes were identified in patient fibroblasts.CONCLUSION: We provide the first large-scale analysis of the clinical and mutational spectrum associated with the TRAF7 developmental syndrome, and we shed light on its molecular etiology through transcriptome studies.

BACKGROUND High-grade gliomas (HGGs) are the most common fatal intrinsic brain tumors in pediatric patients. H3K27-altered diffuse midline gliomas (H3K27-DMGs), a subgroup of HGGs defined by a histone 3 position 27 alteration, are especially aggressive and result in the poorest patient outcomes. Despite in-depth genomic characterization, the 5-year survival rate has yet to improve beyond 2% following diagnosis. A common feature of H3K27-DMGs is infiltration of microglia, macrophages, other myeloid cells, collectively referred to as GAMs, and a small population of T-cells. The contribution of non-tumor cells in the tumor microenvironment (TME) can both promote and or inhibit tumor growth, thus representing an opportunity in the pursuit of novel therapeutics. Using bioinformatic analysis on a human H3K37-DMG single cell-RNA sequencing dataset, we reveal several cell-to-cell communication signaling networks, mediated by ligand and receptor pairs, between GAMs and tumor cells, respectively. HYPOTHESIS Microglial-derived growth factors activate oncogenic signaling pathways via paracrine signaling axes, thus promoting H3K27-DMG tumor cell proliferation and growth. METHODS I will validate these findings and test their therapeutic potential using co-culture studies, CRISPR and shRNA gene silencing, and phospho-proteomics technology. RELEVANCE This research provides further insights on the contribution of non-tumor cells in the TME towards H3K27-DMG cell proliferation and growth and could potentially inform future therapy paradigms.

Pediatric high-grade glioma (pHGG) is a highly malignant and poorly understood cancer driven by diverse genetic and epigenetic mechanisms. Here, we use comparative RNA sequencing, outlier analysis, and spectral clustering approaches to analyze transcriptomic data of 1,543 pediatric brain tumor specimens from the UCSC Treehouse Childhood Cancer Initiative (Treehouse) and Open Pediatric Brain Tumor Atlas (OpenPBTA) to identify subpopulations of pHGG patients with characteristic gene expression profiles. We find that approximately half (45%) of pHGG tumors from OpenPBTA exist in three subgroups defined by high outlier-level expression either of: mitochondrially-encoded 12S and 16S rRNAs; genes enriched in the HSF1-mediated heat shock response and activation pathways; or six C/D box snoRNA (SNORD) genes originating from the paternally-expressed SNORD116 locus involved in Prader-Willi syndrome, a complex neurodevelopmental disorder. Interestingly, the same set of HSF1-dependent pathway genes is also significantly upregulated in a subset (~11%) of pHGG tumors from Treehouse, validating this finding in two independent compendia with different transcript isolation strategies (Treehouse, polyA selection; OpenPBTA, ribodepletion). Our work identifies distinct classes of tumors with outlier-level expression of genes with previously unknown roles in pHGG and provides a framework for subtyping tumors by comparative transcriptomics that is adaptable to any cancer type. We are currently investigating the molecular roles of HSF1-response genes and the imprinted SNORD116 gene cluster in pHGG. Our ongoing research into the biomolecular signatures and mechanisms of the three major tumor classes of pHGG as defined in our study will contribute to a greater understanding of pHGG disease manifestation and progression, and will inform strategies of tailored therapeutic interventions for children with this devastating disease. Citation Format: Gina D. Mawla, A. Geoffrey Lyle, Ellen T. Kephart, Katrina Learned, Holly C. Beale, Joshua E. Goldford, Olena M. Vaske. Subtype classification of pediatric high-grade glioma tumors by comparative transcriptomics [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 LB059.

Cancer heterogeneity is a result of genetic mutations within the cancer cells. Their proliferation is not only driven by autocrine functions but also under the influence of cancer microenvironment, which consists of normal stromal cells such as infiltrating immune cells, cancer-associated fibroblasts, endothelial cells, pericytes, vascular and lymphatic channels. The relationship between cancer cells and cancer microenvironment is a critical one and we are just on the verge to understand it on a molecular level. Cancer microenvironment may serve as a selective force to modulate cancer cells to allow them to evolve into more aggressive clones with ability to invade the lymphatic or vascular channels to spread to regional lymph nodes and distant sites. It is important to understand these steps of cancer evolution within the cancer microenvironment towards invasion so that therapeutic strategies can be developed to control or stop these processes.

Background The reproducibility of gene expression measured by RNA sequencing (RNA-Seq) is dependent on the sequencing depth. While unmapped or non-exonic reads do not contribute to gene expression quantification, duplicate reads contribute to the quantification but are not informative for reproducibility. We show that mapped, exonic, non-duplicate (MEND) reads are a useful measure of reproducibility of RNA-Seq datasets used for gene expression analysis. Findings In bulk RNA-Seq datasets from 2,179 tumors in 48 cohorts, the fraction of reads that contribute to the reproducibility of gene expression analysis varies greatly. Unmapped reads constitute 1–77% of all reads (median [IQR], 3% [3–6%]); duplicate reads constitute 3–100% of mapped reads (median [IQR], 27% [13–43%]); and non-exonic reads constitute 4–97% of mapped, non-duplicate reads (median [IQR], 25% [16–37%]). MEND reads constitute 0–79% of total reads (median [IQR], 50% [30–61%]). Conclusions Because not all reads in an RNA-Seq dataset are informative for reproducibility of gene expression measurements and the fraction of reads that are informative varies, we propose reporting a dataset's sequencing depth in MEND reads, which definitively inform the reproducibility of gene expression, rather than total, mapped, or exonic reads. We provide a Docker image containing (i) the existing required tools (RSeQC, sambamba, and samblaster) and (ii) a custom script to calculate MEND reads from RNA-Seq data files. We recommend that all RNA-Seq gene expression experiments, sensitivity studies, and depth recommendations use MEND units for sequencing depth.

Diffuse midline gliomas (DMGs) bearing driver mutations of histone 3 lysine 27 (H3K27M) are incurable brain tumors with unique epigenomes. Here, we generated a syngeneic H3K27M mouse model to study the amino acid metabolic dependencies of these tumors. H3K27M mutant cells were highly dependent on methionine. Interrogating the methionine cycle dependency through a short-interfering RNA screen identified the enzyme methionine adenosyltransferase 2A (MAT2A) as a critical vulnerability in these tumors. This vulnerability was not mediated through the canonical mechanism of MTAP deletion; instead, DMG cells have lower levels of MAT2A protein, which is mediated by negative feedback induced by the metabolite decarboxylated S-adenosyl methionine. Depletion of residual MAT2A induces global depletion of H3K36me3, a chromatin mark of transcriptional elongation perturbing oncogenic and developmental transcriptional programs. Moreover, methionine-restricted diets extended survival in multiple models of DMG in vivo. Collectively, our results suggest that MAT2A presents an exploitable therapeutic vulnerability in H3K27M gliomas.

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.

Li Fraumeni syndrome (LFS) is a hereditary cancer predisposition syndrome caused by germline mutations in TP53. TP53 is the most common mutated gene in human cancer, occurring in 30–50% of glioblastomas (GBM). Here, we highlight a precision medicine platform to identify potential targets for a GBM patient with LFS. We used a comparative transcriptomics approach to identify genes that are uniquely overexpressed in the LFS GBM patient relative to a cancer compendium of 12,747 tumor RNA sequencing data sets, including 200 GBMs. STAT1 and STAT2 were identified as being significantly overexpressed in the LFS patient, indicating ruxolitinib, a Janus kinase 1 and 2 inhibitors, as a potential therapy. The LFS patient had the highest level of STAT1 and STAT2 expression in an institutional high-grade glioma cohort of 45 patients, further supporting the cancer compendium results. To empirically validate the comparative transcriptomics pipeline, we used a combination of adherent and organoid cell culture techniques, including ex vivo patient-derived organoids (PDOs) from four patient-derived cell lines, including the LFS patient. STAT1 and STAT2 expression levels in the four patient-derived cells correlated with levels identified in the respective parent tumors. In both adherent and organoid cultures, cells from the LFS patient were among the most sensitive to ruxolitinib compared to patient-derived cells with lower STAT1 and STAT2 expression levels. A spheroid-based drug screening assay (3D-PREDICT) was performed and used to identify further therapeutic targets. Two targeted therapies were selected for the patient of interest and resulted in radiographic disease stability. This manuscript supports the use of comparative transcriptomics to identify personalized therapeutic targets in a functional precision medicine platform for malignant brain tumors.

Sclerosing epithelioid fibrosarcoma (SEF) is a rare and aggressive soft-tissue sarcoma thought to originate in fibroblasts of the tissues comprising tendons, ligaments, and muscles. Minimally responsive to conventional cytotoxic chemotherapies, >50% of SEF patients experience local recurrence and/or metastatic disease. SEF is most commonly discovered in middle-aged and elderly adults, but also rarely in children. A common gene fusion occurring between the EWSR1 and CREB3L1 genes has been observed in 80%–90% of SEF cases. We describe here the youngest SEF patient reported to date (a 3-yr-old Caucasian male) who presented with numerous bony and lung metastases. Additionally, we perform a comprehensive literature review of all SEF-related articles published since the disease was first characterized. Finally, we describe the generation of an SEF primary cell line, the first such culture to be reported. The patient described here experienced persistent disease progression despite aggressive treatment including multiple resections, radiotherapy, and numerous chemotherapies and targeted therapeutics. Untreated and locally recurrent tumor and metastatic tissue were sequenced by whole-genome, whole-exome, and deep-transcriptome next-generation sequencing with comparison to a patient-matched normal blood sample. Consistent across all sequencing analyses was the disease-defining EWSR1–CREB3L1 fusion as a single feature consensus. We provide an analysis of our genomic findings and discuss potential therapeutic strategies for SEF.

Epitopes are peptides that present on the surface of the cell and can be recognized by immune cells to initiate the immune response. Identification of neoepitopes – tumor-specific, MHC-bound epitopes recognized specifically by T-cells – is valuable for predicting response to immunotherapies, including checkpoint blockade therapies. Tumors with more neoepitopes tend to be more responsive to immune checkpoint therapies compared to tumors with fewer neoepitopes. ProTECT is a previously published computational method that uses Illumina whole genome and transcriptome sequencing data from tumor and matched normal tissues to identify neoepitopes. Tumor and normal whole genome sequencing data are used to infer a patient's HLA haplotypes, as well as annotate variants as either somatic or germline. While whole genome sequencing is comprehensive, it is quite costly and not available for many samples. Here we adapt ProTECT to use only tumor RNA sequencing data and HLA haplotype information available to the clinician to identify neoepitopes in a tumor sample. Prior to running ProTECT, we use the computational tools Opossum and Platypus for variant calling instead of Radia (which is designed for variant calling using both RNA and DNA sequencing data as input). To determine which variants are somatic and therefore could represent tumor neoepitopes, variants found in RNA are compared to a panel of normals, for example the Genome Aggregation Database (gnomAD; containing variants from 125,748 exome sequences and 15,708 whole-genome sequences). With the resulting somatic variants and the HLA type, ProTECT proceeds as usual, with translation of variants into proteins, MHC:Peptide binding predictions and neoepitope ranking. We find that high quality neoepitopes are identifiable using an RNA-only approach, when genomic data is absent. Future work will validate the sensitivity of our method by benchmarking it against the original ProTECT predictions in the TCGA Prostate Adenocarcinoma cohort. Citation Format: Drew Thompson, Olena M. Vaske, Arjun Rao, Holly C. Beale. Detecting neoepitopes from tumor RNA sequencing datasets [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 176.

Wilms tumor is the most common childhood kidney cancer. 15% of patients with Wilms tumor have germline pathogenic variants in genes or regions such as WT1 or the 11p15 region. Variants in these regions can include structural or copy number alterations or alterations in methylation. In the majority of cases of Wilms tumor no known pathogenic variant could be found using the state-of-the-art technologies, including comprehensive approaches such as Illumina whole exome sequencing. One explanation for this is that such technologies have difficulties in detecting structural variants (SVs) in areas associated with repeat or low complexity sequence. In addition, Illumina technology does not immediately support direct methylation detection. Therefore, we hypothesized that analysis of bilateral Wilms tumor of unknown etiology using long-read sequencing could reveal molecular events of potential clinical interest. We performed in-depth genomic analysis on a whole blood DNA sample from a patient with a bilateral Wilms tumor. This patient had no significant family history of cancer, and previously tested negative for Beckwith-Wiedemann syndrome by methylation testing of the 11p15 region; clinical exome sequencing of the patient's germline detected no variants associated with Wilms tumors. We sequenced the genome at 40x depth using PromethION Nanopore sequencing. 29180 SVs (deletions or insertions larger than 30 base pairs) were detected using Sniffles and 26480 were detected with SVIM. Only SVs that were detected by both methods were considered for downstream analysis. Variants were annotated and filtered using a short-read catalog of SVs (gnomAD-SV), a long-read catalog, the Database of Genomic Variants catalog, and by comparison to 11 in-house genomes. We focused on SVs, copy number variants, and methylation events affecting genes previously associated with Wilms tumor. Our long-read sequencing approach detected compound heterozygotes using phased variant calls. A heterozygous missense mutation was identified in haplotype one, while a 300 base pair insertion in an ALU element was present in haplotype two. These two compound heterozygous variants overlap an exon of the OVCH2 gene, and the ALU element was not detected by the prior Illumina analysis. Additionally, we determined the frequency of methylation in CpG sites genomewide using nanopolish. Using a normal blood sample from an unrelated individual as a control, we searched for extreme differences across large and gene promoter regions. Hypermethylation in the promoter regions of genes in the 11p15.5 locus was observed in the patient as compared to the control. Hypomethylation in this region is associated with Beckwith-Wiedemann syndrome. In conclusion, nanopore technology is able to detect variants missed by Illumina sequencing, and has the potential to yield new findings of interest in a case of a child with suspected cancer predisposition syndrome. Citation Format: Allison R. Cheney, Jean Monlong, Holly C. Beale, Hugh Olsen, Ellen Towle Kephart, Katrina Learned, Shanna White, Julian A. Martinez-Agosto, Noah Federman, Mark Akeson, Miten Jain, Vivian Y. Chang, Olena M. Vaske. Long-read sequencing characterization of a patient with bilateral Wilms tumor of unknown etiology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 261.

Introduction: Leukemia is the most common cancer in children, accounting for approximately one third of all malignancies that occur in the pediatric age group. Acute Lymphoblastic Leukemia (ALL) and Acute Myeloid Leukemia (AML) account for most leukemia diagnosed in this age group. While known markers for poor prognosis include higher age, higher white blood cell count at diagnosis and certain translocations, innovative approaches in tumor RNA sequencing (RNA-Seq) data analysis can discover novel prognostic factors that could be exploited for future therapeutic development in fusion-negative ALL and AML. Methods: To reveal gene expression signatures among fusion-negative leukemias, we used a novel unsupervised analysis model called Hydra. Hydra uses a Dirichlet process mixture model to detect multimodally expressed genes to use in characterizing clusters within cancer cohorts. This approach can detect subtle yet robust differences in gene expression without the reliance on reference normal RNA-Seq datasets. The Hydra model reveals clusters of the cancer cohort, and differences among these clusters can be investigated by finding enriched pathways via Gene Set Enrichment Analysis (GSEA). The cluster-specific enriched pathways can be used in conjunction with survival data to determine how certain pathways are associated with outcome. This analysis used publicly available data from the National Cancer Institute (NCI) Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database that was uniformly processed by the Treehouse Childhood Cancer Initiative. Results: First, 202 fusion-negative AML and fusion-negative B-cell precursor ALL samples were run through Hydra and five clusters were identified. These clusters had different enriched pathways, such as high mitochondrial activity, high cell proliferation, and high cell signaling. Though these are characteristics of all cancer cells, each cluster demonstrated that one pathway was most distinctive of those samples. Most clusters were differentiated by disease, however, one cluster with enriched heme metabolism and immunoglobulin pathways contained almost equal amounts of AML and ALL samples, suggesting that specific cohorts of AML and ALL patients had increased inflammatory response. Another cluster contained 72 AML samples and 4 ALL samples. The four ALL samples in this cluster showed lowered expression of CD19, a B-cell lineage immune marker, and elevated expression of CD14, a myeloid lineage immune marker. These ALL patients exhibited genomic characteristics of AML, which may suggest a more specialized treatment regimen. Discussion: Despite extensive characterization of pediatric high-risk leukemias using genomic approaches, there is ample opportunity to study RNA-Seq-derived gene expression profiles to help accurately diagnose and treat pediatric patients. Citation Format: Sneha S. Jariwala, Alfred Geoffrey Lyle, Jacob Pfeil, Lauren Sanders, Holly C. Beale, Ellen T. Kephart, Katrina Learned, Allison Cheney, Olena M. Vaske. Molecular classification of pediatric high-risk leukemias using expression profiles of multimodally expressed genes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3033.

Synovial sarcoma (SS) is an aggressive soft-tissue malignancy, accounting for 10% of all soft-tissue sarcomas. These tumors can occur at any age but most often affect young adults and adolescents, developing deep in the distal extremities. The prognosis of SS tumors is poor, with a 5-year survival rate of 36-76%, a high rate of metastasis and few treatments. The purpose of this study was to identify novel overexpressed oncogenes that could serve as druggable targets for treating synovial sarcoma patients. We compared the RNA-Seq expression profiles of a cohort of 36 synovial sarcomas to our compendium of RNA-Seq expression data from 12,236 tumor samples (treehousegenomics.ucsc.edu) from pediatric and adult cancer patients. In comparing gene expression in the synovial sarcoma cohort samples against the compendium samples, gene expression outliers were defined as having expression above the gene-specific outlier threshold as defined by the Tukey's outlier method. Among the overexpression outliers, pathway enrichment analysis was used to identify common and druggable pathways, with implications for potential therapeutics for patients with SS. Our analysis identified the overexpression of members of the Sonic Hedgehog pathway in the majority of synovial sarcoma samples. For example, GLI1 expression exceeded the outlier threshold in 35 out of 36 samples. This pathway can be targeted by available small molecule inhibitors. Ongoing work focuses on evaluating the role of Sonic Hedgehog signaling in the pathogenesis of SS using pharmacological inhibition, CRISPRi studies in cell line models of the disease and nanopore sequencing. We currently have 4 patient-derived synovial sarcoma cell lines (HSSY-II, SYO-1, YAMATO, and ASKA) that we can grow in both adherent conditions and in 3D cell culture as sarcospheres. We detected the expression of the SYT-SSX fusion transcript in each of the cell lines by RT-PCR to confirm the cell lines maintained expression of the pathogenic fusion. This work has implications for using comparative tumor RNA-seq derived gene expression data for nominating novel druggable targets specific to synovial sarcoma tumors. Citation Format: Yvonne A. Vasquez, Jacob Pfeil, Letitia Mueller, Holly Beale, Alfred G. Lyle, Lauren Sanders, Katrina Learned, Ellen Kephart, Anouk van den Bout, Allison Cheney, Sahar Hosseinzadeh, Isabel Bjork, Sofie R. Salama, Olena Vaske. Identifying potential druggable targets for synovial sarcoma using comparative RNA-seq analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3035.

This cohort study evaluates the feasibility and utility of incorporating comparative gene expression information into the precision medicine framework for difficult-to-treat pediatric and young adult patients with cancer., Key Points Question Is it feasible and useful to compare the tumor RNA sequencing data of a child or young adult with the tumor RNA sequencing data of thousands of other patients (of all ages) in a research setting? Findings Among 144 tumor samples from children and young adults, comparative RNA sequencing analysis, conducted across 4 precision medicine studies in the United States and Canada, was feasible and potentially useful for 99 of 144 pediatric and young adult cancer samples. In contrast, DNA mutation information was potentially useful for only 34 of 74 samples. Meaning This study’s findings suggest that open sharing and combined analysis of tumor RNA sequencing data from pediatric and young adult patients treated on different clinical trials may represent a feasible approach and may produce useful clinical and biological information for individual patients., Importance Pediatric cancers are epigenetic diseases; therefore, considering tumor gene expression information is necessary for a complete understanding of the tumorigenic processes. Objective To evaluate the feasibility and utility of incorporating comparative gene expression information into the precision medicine framework for difficult-to-treat pediatric and young adult patients with cancer. Design, Setting, and Participants This cohort study was conducted as a consortium between the University of California, Santa Cruz (UCSC) Treehouse Childhood Cancer Initiative and clinical genomic trials. RNA sequencing (RNA-Seq) data were obtained from the following 4 clinical sites and analyzed at UCSC: British Columbia Children’s Hospital (n = 31), Lucile Packard Children’s Hospital at Stanford University (n = 80), CHOC Children’s Hospital and Hyundai Cancer Institute (n = 46), and the Pacific Pediatric Neuro-Oncology Consortium (n = 24). The study dates were January 1, 2016, to March 22, 2017. Exposures Participants underwent tumor RNA-Seq profiling as part of 4 separate clinical trials at partner hospitals. The UCSC either downloaded RNA-Seq data from a partner institution for analysis in the cloud or provided a Docker pipeline that performed the same analysis at a partner institution. The UCSC then compared each participant’s tumor RNA-Seq profile with more than 11 000 uniformly analyzed tumor profiles from pediatric and young adult patients with cancer, downloaded from public data repositories. These comparisons were used to identify genes and pathways that are significantly overexpressed in each patient’s tumor. Results of the UCSC analysis were presented to clinical partners. Main Outcomes and Measures Feasibility of a third-party institution (UCSC Treehouse Childhood Cancer Initiative) to obtain tumor RNA-Seq data from patients, conduct comparative analysis, and present analysis results to clinicians; and proportion of patients for whom comparative tumor gene expression analysis provided useful clinical and biological information. Results Among 144 samples from children and young adults (median age at diagnosis, 9 years; range, 0-26 years; 72 of 118 [61.0%] male [26 patients sex unknown]) with a relapsed, refractory, or rare cancer treated on precision medicine protocols, RNA-Seq–derived gene expression was potentially useful for 99 of 144 samples (68.8%) compared with DNA mutation information that was potentially useful for only 34 of 74 samples (45.9%). Conclusions and Relevance This study’s findings suggest that tumor RNA-Seq comparisons may be feasible and highlight the potential clinical utility of incorporating such comparisons into the clinical genomic interpretation framework for difficult-to-treat pediatric and young adult patients with cancer. The study also highlights for the first time to date the potential clinical utility of harmonized publicly available genomic data sets.

Genomic data offer valuable insights that can be used to help find treatments and cures for disease. Precision medicine, defined by the NIH as “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person,” is gaining acceptance among physicians, who are beginning to integrate patient-centric data analysis into clinical decision-making. Although precision medicine makes use of various types of data, this piece focuses on molecular characterization data specifically, as the discoveries yielded from these data can advance thinking around clinical care for cancer patients. Our pediatrics genomics team at the University of California Santa Cruz Genomics Institute is uniquely situated to discuss the use of shared genomic data for clinical benefit because our collaborations with hospital partners in the United States and internationally rely on big-data comparative genomic analysis. Using shared data, Treehouse Childhood Cancer Initiative develops methods for comparative analysis of tumor RNA sequencing profiles from single patients for the purposes of identifying overexpressed oncogenes that could be targeted by therapies in the clinic. To enable and improve this analysis, we continuously increase the size of our data compendium by adding public pediatric tumor RNA sequencing data sets. We developed an approach for assessing the quality of shared RNA sequencing data to ensure the integrity of the data. In this approach we calculate the number of mapped exonic nonduplicate (MEND) reads, applying a 10 million MEND read minimum threshold for inclusion in our comparative analysis. In collaboration with Stanford University and Lucile Packard Children's Hospital Stanford, our team at Treehouse Childhood Cancer Initiative explores the value to researchers everywhere of shared genomic data for clinical utility and the challenges of data sharing that threaten to impede otherwise rapid advances in precision medicine. This Perspective offers recommendations for maximizing the use of genomic data to make discoveries that will benefit patients.

BackgroundThe accuracy of gene expression as measured by RNA sequencing (RNA-Seq) is dependent on the amount of sequencing performed. However, some types of reads are not informative for determining this accuracy. Unmapped and non-exonic reads do not contribute to gene expression quantification. Duplicate reads can be the product of high gene expression or technical errors.FindingsWe surveyed bulk RNA-Seq datasets from 2179 tumors in 48 cohorts to determine the fractions of uninformative reads. Total sequence depth was 0.2-668 million reads (median (med.) 61 million; interquartile range (IQR) 53 million). Unmapped reads constitute 1-77% of all reads (med. 3%; IQR 3%); duplicate reads constitute 3-100% of mapped reads (med. 27%; IQR 30%); and non-exonic reads constitute 4-97% of mapped, non-duplicate reads (med. 25%; IQR 21%). Informative reads--Mapped, Exonic, Non-duplicate (MEND) reads--constitute 0-79% of total reads (med. 50%; IQR 31%). Further, we find that MEND read counts have a 0.22 Pearson correlation to the number of genes expressed above 1 Transcript Per Million, while total reads have a correlation of −0.05.ConclusionsSince the fraction of uninformative reads vary, we propose using only definitively informative reads, MEND reads, for the purposes of asserting the accuracy of gene expression measured in a bulk RNA-Seq experiment. We provide a Docker image containing 1) the existing required tools (RSeQC, sambamba and samblaster) and 2) a custom script. We recommend that all results, sensitivity studies and depth recommendations use MEND units.

Diffuse pediatric gliomas harboring a Histone H3 K27M mutation are significantly more aggressive than H3-wild type gliomas and demonstrate global hypomethylation at the K27 residue(1). As a result, these tumors show global aberrant gene expression, resulting in a primitive, stem-like proliferative cell population(2). Posterior fossa (PF) ependymomas, on the other hand, harbor few significantly recurrent somatic mutations, but PF-A and PF-B subgroups have been defined on the basis of epigenetic differences(3). Compared to PF-B, the PF-A subgroup demonstrates H3K27 hypomethylation, aberrant gene expression and aggressive tumor growth(4,5). We recently identified a set of long non-coding RNA (lncRNA) that are transiently expressed in early brain development(6), and hypothesized that H3K27M gliomas and PF-A ependymomas may share methylation-related dysregulation of long non-coding RNA (lncRNA) networks responsible for maintaining normal differentiation programs. Here we describe a network of regulatory lncRNA with increased expression in both H3K27M gliomas and PF-A ependymomas, as compared to H3-WT gliomas and PF-B ependymomas. We demonstrate that increased expression of this lncRNA network correlates with the over-expression of signaling pathways involved in maintaining a non-differentiated, proliferative phenotype and driving tumorigenesis. We hypothesize that in both H3K27M gliomas and PF-A ependymomas, aberrant global methylation may be driving lncRNA to activate and maintain stem-like states in early neural development, suggesting similarities in epigenetically driven, developmental origins for both tumor types. References: 1. Chan KM, Fang D, Gan H, et al. Genes Dev. 2013;27(9):985–90; 2. Filbin MG, Tirosh I, Hovestadt V, et al. Science. 2018;360(6386):331–5; 3. Witt H, Mack SC, Ryzhova M, et al. Cancer cell. 2011;20(2):143–57; 4. Bayliss J, Mukherjee P, Lu C, et al. Sci. Transl. Med. 2016;8(366):366ra161; 5. Mack SC, Witt H, Piro RM, et al. Nature. 2014;506(7489):445; 6. Field AR, Jacobs FM, Fiddes IT, et al. bioRxiv. 2017:232553.

Last month, in a conference call held by the U.S. Department of Health and Human Services and National Institutes of Health (NIH), it was revealed that a large focus of President Trump's pledge to fund childhood cancer research will be genomic data sharing. Although the United States has only 5% of the world's pediatric cancer cases, it has disproportionately more resources and access to genomic information compared to low-income countries. We hope that the spotlight on genomic data sharing in the United States will galvanize the world's pediatric cancer community to elevate genomic data sharing to a level where its full potential can finally be realized. Pediatric cancers are rare, affecting 50 to 200 children per million a year worldwide. Thus, with 16 different major types and many subtypes, no cancer center encounters large cohorts of patients with the same diagnosis. To advance their understanding of particular cancer subtypes, pediatric oncologists must have access to data from similar cases at other centers. Because subtypes of pediatric cancer are rare, assembling large cohorts is a limiting factor in clinical trials as well. Here, too, data sharing is the first critical step. Typically, pediatric cancers don't have the number of mutations that make immunotherapies effective, and only a few subtypes have recurrent mutations that can be used to develop gene-targeted therapies. However, the abnormal expression level of genes gives a vivid picture of genetic misregulation, and just sharing this information would be a huge step forward. Using gene expression and mutation data, analysis of genetic misregulation in different pediatric cancer subtypes could point the way to new treatments. A major challenge in genomic data sharing is the patient's young age, which frequently precludes an opportunity for informed consent. Compounding this, the rarity of subtypes requires the aggregation of patients from multiple jurisdictions, raising barriers to assembling large representative data sets. A greater percentage of children than adults with cancer participate in research studies, and children often participate in multiple studies. However, this means that data collected on individual children may be found at multiple institutions, creating difficulties if there are no standards for data sharing. To enable effective sharing of genomic and clinical data, the Global Alliance for Genomics and Health has developed the Key Implications for Data Sharing (KIDS) framework for pediatric genomics. The recommendations include involving children in the data-sharing decision-making process and imposing an ethical obligation on data generators to provide children and parents with the opportunity to share genomic and clinical information with researchers. Although KIDS guidelines are not legally binding, they could inform policy development worldwide. To advance the sharing culture, along with the NIH, pediatric cancer foundations such as the St. Baldrick's Foundation and Alex's Lemonade Stand Foundation have incorporated genomic data-sharing requirements into their grants processes. Researchers and clinicians around the world have created dozens of pediatric cancer genomic databases and portals, but pulling these together into a larger network is problematic, especially for patients with data at more than one institution, as patient identifiers are stripped from shared data. However, initiatives like the Children's Oncology Group's Project Every Child and the European Network for Cancer Research in Children and Adolescents' Unified Patient Identity may resolve this issue. We urge the creators of pediatric cancer genomic resources to collaborate and build a real-time federated data-sharing system, and hope that the new U.S. initiative will inspire other countries to link databases rather than just create new siloed regional resources. The great advances in information technology and life sciences in the last decades have given us a new opportunity to save our children from the scourge of cancer. We must resolve to use them.

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.

SUMMARY Accelerating cures for children with cancer remains an immediate challenge as a result of extensive oncogenic heterogeneity between and within histologies, distinct molecular mechanisms evolving between diagnosis and relapsed disease, and limited therapeutic options. To systematically prioritize and rationally test novel agents in preclinical murine models, researchers within the Pediatric Preclinical Testing Consortium are continuously developing patient-derived xenografts (PDXs)—many of which are refractory to current standard-of-care treatments—from high-risk childhood cancers. Here, we genomically characterize 261 PDX models from 37 unique pediatric cancers; demonstrate faithful recapitulation of histologies and subtypes; and refine our understanding of relapsed disease. In addition, we use expression signatures to classify tumors for TP53 and NF1 pathway inactivation. We anticipate that these data will serve as a resource for pediatric oncology drug development and will guide rational clinical trial design for children with cancer., Graphical Abstract, In Brief Rokita et. al provide an extensively annotated genomic dataset of somatic oncogenic regulation across 37 distinct pediatric malignancies. The 261 patient-derived xenograft models are available to the scientific community, and the genomic annotations will enable rational preclinical agent prioritization and acceleration of therapeutic targets for early-phase pediatric oncology clinical trials.

Introduction: There is strong experimental and clinical data to indicate the critical involvement of immune evasion in relapsed leukemia in children. A well-defined characteristic of refractory leukemia is the accumulation of genetic aberrations and mutations that may act as drivers or passengers in the process of tumor recurrence. Many of these mutations get translated into proteins that contain tumor-specific immune-stimulatory epitopes (neoantigens) that can elicit host antitumor immune responses. Although, in general, the mutation rate is lower in pediatric tumors, recent studies have shown that almost 90% of pediatric leukemias carry potentially actionable neoepitopes. In this study, we describe the results from a comprehensive experimental approach of neoantigen prediction coupled with antigen processing and HLA-binding prediction algorithms with in vitro validation assays for the generation of neoantigen vaccines against high-risk leukemias in children. Methods: DNA and RNA from leukemia cells and matched fibroblasts were obtained. Raw reads were aligned to human reference genome and somatic variants (SNVs) were called using Strelka v1.0.1441. RNA-seq data from leukemic cells were used to predict neoantigen expression levels resulting from SNVs using STAR (2.4.1)12 and Cufflinks v2.2.1. Normalized expression data were then cross-referenced with the list of SNVs to identify leukemia-specific mutant proteins. HLA typing for each sample was carried out from RNA-seq data using seq2HLA v2.2. Using the patient's HLA phenotype, we then used NetMHCons v1.1 to predict short peptides derived from leukemia-specific mutant proteins that will bind to autologous HLA Class I molecules. These 8/9-mers were filtered to predict a high likelihood of proteasomal or immune-proteasomal processing and transporter associated with antigen processing (TAP) using NetChop v3.1 and the immune epitope database (IEDB), respectively. The peptides identified were rank-ordered based on the composite immunogenicity score derived from MHC class I binding affinities, proteasomal processing and TCR binding predictions and synthesized accordingly. Peripheral blood derived dendritic cells (DCs) and CD8+ T-cells were isolated and expanded in culture with relevant cytokines. The DCs were pulsed with peptides and then co-cultured with CD8+ T-cells. After five days, the primed CD8+ T-Cells were separated, washed and exposed to the patient's leukemic cells at varying ratios and the leukemia specific CD8+ T-cell activation was quantified by IFN gamma secretion using ELISpot assays. Results: In the leukemia specimen studied, approximately 5% of all on-target germline mutations were found only in leukemic cells. Tumor mutational burden was, on average, 0.34 mut/Mb. Analysis of the highest ranking synthetic peptides (approximately 10 per leukemia sample) showed leukemia-specific activation of patient's T-cells as measured by the mean number of spots observed in ELISpot assays. For example, in patient one (15 year old male, high-risk ALL, one year off therapy), 14 individual short sequences were identified and corresponding peptides were synthesized. Among these, three peptides were not soluble and three peptides showed significant activity above controls. Maximum leukemia specific T-cell activation was noted with peptide #7 QQSALVLL (mean 135 ELISpots compared to 72 in controls, p Discussion: Completed data, including the vaccine peptide sequences and corresponding activities showed the feasibility of identifying pediatric leukemia neoantigen sequences in personalized mutational landscapes of these patients. In addition, we have provided an in vitro experimental approach to validate the potential of such vaccines in future clinical studies and this methodology can also be used to identify agents for effective combinations such as immune checkpoint inhibitors. A clinical trial using these strategies is in development for the treatment of high-risk leukemia in children. Disclosures No relevant conflicts of interest to declare.

Genomic characterization is often used for the identification of therapeutic targets in tumors. Recently, comparative transcriptomics has begun to be utilized for this purpose. In this pilot, we compare the transcriptome of a patient with recurrent high grade glioma (HGG) to our cohort to identify potential therapies. We reviewed transcriptomic profiles from patients who had resection of HGG at our institution over the past year as well as the UCSC cancer compendium. Briefly, tumor RNA was extracted from embedded tumor tissue sections with tumor cellularity higher than 20%. RNA libraries were sequenced to obtain approximately 65 million reads on an Illumina HiSeq 4000 System utilizing patterned flow cell technology. The RNA profile of a 24 male with Li-Fraumeni syndrome and recurrent HGG with leptomeningeal spread underwent comparative transcriptomics to identify targets. A Bayesian statistical framework for gene expression outlier detection was used. These comparisons allowed for the identification of genes and pathways that are significantly overexpressed. Our internal HGG cohort consisted of 44 adult patients and was evenly distributed among the 4 HGG Verhaak subtypes. Our patient of interest had druggable outlier expression in HDAC1, STAT1 and STAT2 in comparison to our internal cohort indicating vorinostat and ruxolitinib as potential therapies, respectively. We then compared our patient of interest to 12,747 patients in the cancer compendium and STAT2 expression was high but not an outlier. In comparison to 738 glioma samples, STAT1 and STAT2 were outliers but not HDAC1 again indicating ruxolitinib as a potential targeted therapy. The patient did not have outlier expression in notch transcriptional targets or immune checkpoint biomarkers when compared to all cohorts. In conclusion, comparative Transcriptomics can identify therapeutic targets in a patient with recurrent HGG even in small cohorts. In our pilot, we identified ruxolitinib as a potential candidate to treat leptomeningeal recurrence.

Pediatric diffuse midline gliomas are lethal cancers, the majority of which harbor the H3 p.K27M mutations. Although it has potential implications on the treatment of diffuse midline glioma as a disease driver; the timing, cell type of origin, and effect of the H3 p.K27M mutation on early embryonic brain development is poorly understood. The purpose of our study is to elucidate the molecular mechanisms by which the histone H3 p.K27M mutation drives tumorigenesis of pediatric diffuse midline gliomas using the analysis of genomic datasets. Here, we performed differential RNA sequencing gene expression analysis of a cohort of H3K27M and H3 wild type (WT) pediatric diffuse midline gliomas, revealing that genes in the epithelial-mesenchymal transition (EMT) pathway were significantly differentially expressed between the mutant and WT tumors. Several EMTs are required for normal brain development. Overall, pre-EMT genes, including the master regulator of EMT SNAI1, were overexpressed in H3K27M tumors compared to the WT tumors, while post-EMT genes were underexpressed. We hypothesized that the H3 p.K27M mutation may lead to gliomagenesis by inducing a stall in the EMT in early brain development. To test this hypothesis, we examined published single-cell RNA sequencing data from pediatric diffuse midline gliomas alongside similar data from organoid models of neural development, collected from multiple developmental timepoints. This analysis revealed transcriptional similarities between H3K27M and pre-EMT neural stem cells. Currently, we are investigating the expression of EMT markers in H3K27M and WT pediatric glioma primary cell lines, using Western blotting, RT-PCR, and CRISPRi screening. In conclusion, we observed aberrant expression of genes involved in EMT in H3K27M pediatric gliomas. Our observations are consistent with a model in which the p.H3K27M mutation is associated with a pre-EMT cell phenotype, potentially due to an arrest in the EMT pathway or de-differentiation of mature astrocytes. Citation Format: ALLISON R. CHENEY, Lauren M. Sanders, Lucas Seninge, Holly C. Beale, Ellen Towle Kephart, Jacob Pfeil, Katrina Learned, A. Geoffrey Lyle, Isabel Bjork, David Haussler, Sofie R. Salama, Olena M. Vaske. H3K27M gliomas are characterized by a stall in the epithelial-mesenchymal transition [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6154.

Here we describe the utility of comparative RNA sequencing (RNA-seq) analysis in identifying cancer driver pathways and relevant therapeutics in childhood cancer, and we introduce a novel system for prioritizing gene targets based on analytical and published evidence. The purpose of our study was to evaluate the clinical utility of comparative N-of-1 gene expression analysis in identifying therapeutic options for pediatric patients with relapsed or recurrent cancers. The comparative analysis framework and large cancer background cohorts were developed at the Treehouse Childhood Cancer Initiative at UC Santa Cruz. We employed this analysis in a pilot study of 26 patients at the Lucile Packard Children’s Hospital. We analyzed RNA-seq data from 30 biopsied samples from 26 patient donors, including 16 sarcomas, 5 CNS tumors, 3 hematopoietic cancers, 1 liver, and 1 colon cancer. We compared gene expression from each child’s tumor biopsy to a background cohort of RNA-seq data from over 11,000 cancer patients, and also to a smaller cohort defined by molecular and histopathologic similarity to the child’s tumor biopsy. This comparison yielded outlier gene activations in the child’s biopsy compared to those in the background cohorts, reflecting cancer driver pathways in the child’s tumor that are actionable. We stratified each of the resulting therapeutic leads into 5 baskets: RTK activation, JAK/STAT signaling, PI3K/AKT/mTOR signaling, Cell Cycle activation, or Other. Because 27 of the 30 samples had more than one lead, we developed a novel scoring system to prioritize each sample’s therapeutic gene targets based on the analytical strength of the gene expression analysis result, and on published literature evidence for each gene as a biomarker indicative of drug response. We presented the results of our analysis in genomic consensus meetings at Stanford and surveyed the responses of clinicians and families on the utility of our analysis for treatment decisions. Here we report our experience with the method and highlight case studies in which this analysis informed treatment decisions. Citation Format: Lauren M. Sanders, A. Geoffrey Lyle, Holly C. Beale, Ellen Towle Kephart, Katrina Learned, Jennifer Peralez, Norman Lacayo, Arun Rangaswami, Sheri L. Spunt, Isabel Bjork, David Haussler, Sofie R. Salama, Olena M. Vaske. Comparative gene expression analysis for identification and prioritization of therapeutic targets in a cohort of childhood 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 A44.

The purpose of our study was to elucidate the molecular mechanisms by which the histone H3 K27M mutation drives tumorigenesis of pediatric gliomas. Though it has potential implications on the treatment of diffuse midline glioma as a disease driver, the timing, cell type of origin, and effect of the H3K27M mutation on early embryonic brain development are not fully characterized. Here, we performed differential expression analysis on a cohort of H3K27M and H3WT pediatric gliomas, revealing that genes in the epithelial-mesenchymal transition (EMT) pathway were significantly differentially expressed. SNAI1, the EMT master regulator, was significantly overexpressed in the H3K27M tumor cohort. Overall, pre-EMT genes were overexpressed in H3K27M tumors while post-EMT genes were underexpressed. We hypothesized that H3K27M may lead to gliomagenesis by stalling an EMT in early brain development and employed single-cell and bulk RNA sequencing data from cerebral organoids at multiple developmental timepoints to test this hypothesis. We observed that a long noncoding RNA (lncRNA) signature identified as transiently expressed in early brain development was preferentially expressed in H3K27M tumors. Cell type-specific lncRNA signatures had higher expression in H3K27M tumors for pre-EMT cell types, and higher expression in H3WT tumors for post-EMT cell types. Finally, t-SNE clustering of single-cell glioma RNA sequencing data with single-cell organoid data revealed transcriptional similarities between H3K27M and pre-EMT neural stem cells. In conclusion, we observed aberrant activity of the EMT in H3K27M gliomas. Our data suggest that the H3K27M mutation is associated with a pre-EMT cell phenotype, and that this mutation may cause EMT arrest or de-differentiation. Citation Format: Allison R. Cheney, Lauren M. Sanders, Lucas Seninge, Holly C. Beale, Ellen Towle Kephart, Jacob Pfeil, Katrina Learned, A. Geoffrey Lyle, Isabel Bjork, David Haussler, Sofie R. Salama, Olena M. Vaske. Candidate differentiation stall in epithelial mesenchymal transition in H3K27M diffuse midline glioma [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 B06.

Introduction: In children diagnosed with leukemia, relapse and its associated morbidity and mortality remain the most dreaded consequences of the disease. Therefore, the discovery and implementation of novel and broadly applicable therapeutic strategies for these patients are urgently needed. Currently, a number of precision therapeutic approaches have been formulated where molecular analyses of the malignant cells have been used to inform, often multiple, probable targets and potential therapeutic agents. However, a common drawback of this approach has been the uncertainty involved in selecting the drug with the most and clinically relevant cytotoxic potential. In vitro xenograft approaches, although can provide key information on drug activity and side effects, are time consuming and impractical and cumbersome in most cases. We have recently demonstrated the ability of a bone marrow stromal derived cell line to sustain the growth and survival of patient leukemic cells in culture that has allowed in vitro evaluations of drug response.This methodology was combined with a previously validated molecular pathway analysis program to identify effective agents or combinations for a subsequent informed precision clinical trial. Methods: Gene expression profiles from refractory pediatric leukemic cells were analyzed against similar data from more than 12, 000 tumors and outlier analyses were carried out to generate a list of overexpressed genes. This information was computed to identify hypothetically activated pathways, druggable targets and potential agents from a panel of FDA approved drugs. A bone marrow stromal cell line was established and characterized that has been shown to support leukemia cell proliferation in vitro. Briefly, stromal cells were co-cultured with leukemic cells at pre-determined ratios with and without the drugs identified in the genomic analysis. After four days in culture, leukemic cells were re-suspended and analyzed for proliferation. Target modulation and activated cell death pathways were queried by Western blot analyses. Results: Multiple targets and potential agents for effective therapeutics were identified against an initial set of relapsed leukemia specimens. For example, in patient # P700491 (pre B-ALL) gene expression data sets revealed clustering within the area of ALL and AML in the reference cancer genomics data. Comparative tumor RNA seq outlier analysis showed molecular abnormalities in BTK, JAK3 and PIK3CD, corresponding to molecular categories of RTK, JAK-SAT and PI3K-AKT-mTOR pathways targetable by the drugs Ibrutinib, WHI-P131 and Idelalisib, respectively. However, in vitro studies showed significant cell killing with Idelalisib and not with the other two agents. Target modulation assays showed effective induction of apoptosis including PARP cleavage in Idelalisib treated leukemia cells compared to controls, indicating the feasibility of this approach to effectively identify potentially applicable agents for this individual patient. Conclusions: We demonstrate the ability of a newly cloned bone marrow stromal derived cell line to sustain the growth and survival of patient leukemic cells in culture that has allowed in vitro target modulation and target validation analyses for cytotoxicity. This methodology was combined with a previously demonstrated molecular pathway interrogation program to ascertain effective agents or combinations for an experimentally informed precision clinical trial. Importantly, our data showed that genomically identified actionable targets are not universally predictive of tumor response and an in vitro cytotoxicity analysis step may enhance the accuracy of this approach. We describe the practical advantages and versatility of this work-flow to inform the selection of agents in future umbrella trials. It is anticipated that the information obtained will lead to an applicable clinical trial the near future. Disclosures Narendran: Bayer: Honoraria, Other: CANTRK Advisory Board .

Diffuse intrinsic pontine gliomas (DIPGs) are incurable pediatric brain tumors with an aggressive onset. Apart from irradiation, there are currently no effective therapies available for DIPG patients, who have a median survival time of less than one year. DIPG cells possess a mutation in histone H3 (H3K27M) that results in a reduction of H3K27 trimethylation and activation of oncogenic signaling pathways. We show that the H3K27M mutation induces RAS pathway signaling which is augmented by additional RAS activators including PDGFRA. We observed that the H3K27M mutation leads to silencing of GTPase-activating proteins, namely RASAL1, which when ectopically expressed, reduced proliferation and RAS activation. An siRNA screen of RAS pathway effectors identified ERK5, but not ERK1/2, as important for DIPG growth. Suppression of ERK5, which is highly expressed in DIPG, decreased DIPG cell proliferation and induced apoptosis both in vitro and in vivo. Mechanistically, we show that ERK5 directly activates and stabilizes the proto-oncogene MYC. ERK5 overexpression fully rescued ERK5-depleted cells and partial rescue was achieved by expression of ERK5 mutants lacking kinase activity or the transactivation domain (ΔTAD). However, no rescue was achieved with kinase-dead, ΔTAD double mutants. Additionally, ERK5 knockdown or treatment with ERK5 inhibitors significantly increased survival of mice intracranially engrafted with DIPG cells. TG02, a pan-CDK and ERK5 inhibitor currently in phase II trials for various cancers, was the most effective treatment, extending median survival time nearly two-fold. Collectively, our data demonstrate DIPG reliance on RAS and MYC activities, and in so doing reveal novel therapeutic targets for treating these tumors.