Brain Tumor Tissue Consortium Research Articles

Abstract 6586: Updates to UALCAN, a comprehensive cancer proteogenomic data analysis platform for discovery research

Abstract Background: Recent advances in high throughput technologies and initiation of multiple consortium driven projects have led to generation of high volume of molecular data related to thousands of cancer patients. These high throughput data are extremely useful for novel biomarker identification, therapeutic target identification in tumor subclasses and allows numerous hypothesis driven cancer research projects. However, the sheer volume of data and diverse data formats presents tremendous challenge for researchers with no programming experience to access and analyze comprehensively. These factors prompted us to develop UALCAN (University of ALabama CANcer portal, Yes! You All Can) for comprehensive cancer data analysis in a user-friendly manner. UALCAN enables cancer researchers/clinicians in tumor subgroup based gene expression, protein expression and survival analyses. UALCAN is extremely popular among cancer researchers round the world with well over a “MILLION” site visits and cited over 3400 times in research articles. UALCAN integrates The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC), as well as gene expression data from Children Brain Tumor Tissue Consortium (CBTTC). Users can also analyze non-coding RNA (miRNA and lncRNA) expression data from The Cancer Genome Atlas (TCGA) and the epigenetic data though the promoter DNA methylation analysis form the TCGA data. Results: UALCAN now enables user to study expression profile of ~10000 proteins in 14 CPTAC cancers and expression pattern and survival impact of 20,500 protein-coding, ~17,000 lncRNA and 1800 miRNA in 33 TCGA cancers. It also facilitates analysis of gene expression pattern in pediatric brain cancer. User-friendly graphical user interface of UALCAN facilitates a) analyzing protein/non-coding RNA expression in tumor subgroups based on race, stage, age and molecular types; b) identifying top differentially expressed lncRNA/miRNA in specific cancer subtype; c) listing potential gene targets of non-coding RNA; d) performing pan-cancer analysis and e) determining impact of gene expression on patient’s overall survival. Conclusions: UALCAN is freely available at http://ualcan.path.uab.edu (Google: UALCAN) This dynamic data portal provides constant updates that empower cancer researchers in studying gene and protein level expression and identifying tumor subgroup specific non-coding RNA biomarkers. UALCAN serves a one-stop platform for access, study, analyze and leverage large cancer datasets. Citation Format: Darshan Shimoga Chandrashekar, Sooryanarayana Varambally, Santhosh Kumar Karthikeyan, Praveen Kumar Korla, Henalben Patel, Mohammad Athar, Upender Manne, George J. Netto, Ahmedur Rahman Shovon, Sidharth Kumar, Zhaohui S. Qin, Chad J. Crieghton. Updates to UALCAN, a comprehensive cancer proteogenomic data analysis platform for discovery research [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 6586.

Global molecular alterations involving recurrence or progression of pediatric brain tumors.

BackgroundWe aimed to identify molecular changes in recurrent or progressive pediatric brain tumors, as compared to the corresponding initial tumors from the same patients, using genomic, transcriptomic, and proteomic data from a unique and large cohort of 55 patients and 63 recurrent or progressive tumors from the Children's Brain Tumor Tissue Consortium, representing various histologic types.MethodsWe carried out paired analyses for each gene between recurrent/progressive and initial tumor groups, using RNA-sequencing and mass spectrometry-based proteomic data. By whole-genome sequencing (WGS) analysis, we also examined somatic DNA events for a set of cancer-associated genes.ResultsOf 44 patients examined by WGS, 35 involved at least one cancer-associated gene with a somatic alteration event in a recurrent or progressive tumor that was not present in the initial tumor, including genes NF1, CDKN2A, CCND2, EGFR, and MYCN. By paired analysis, 68 mRNA transcripts were differentially expressed in recurrent/progressive tumors with p<0.001, and these genes could predict patient outcomes in an independent set of pediatric brain tumors. Gene transcript-level associations with recurrence or progression were enriched for protein-level associations. There was a significant overlap in results from pediatric brain tumors and results from adult brain tumors from The Cancer Genome Atlas. Unsupervised analysis defined five subsets of recurrent or progressive tumors, with differences in gene expression and overall patient survival.ConclusionsOur study uncovers genes showing consistent expression differences in recurrent or progressive tumors. These genes may provide molecular clues as to processes or pathways underlying more aggressive pediatric brain tumors.

IMMU-14. COMPUTATIONAL DECONVOLUTION OF TUMOR-INFILTRATING IMMUNE COMPONENTS IN PEDIATRIC NERVOUS SYSTEM TUMORS

IntroductionIn the last decade, checkpoint inhibitor-based immunotherapy has been a groundbreaking development in the treatment of cancer. However, only a subset of patients treated with immune checkpoint inhibitors show long-lasting clinical benefit. Studies showed the tumor immune microenvironment (TME) as a particularly important factor influencing treatment response, critical for the design of other or combinatorial immunotherapy treatment strategies. Extensive research has been performed in the adult cancer field to unravel its immunogenomic aspects. However, in pediatric cancer this insight into tumor-infiltrating immune components is still lacking. This study aims to provide insight into the landscape of the immune microenvironment in pediatric primary nervous system tumors. MethodsBulk RNA-seq data of 936 pediatric primary solid tumors acquired from multiple international initiatives including Therapeutically Applicable Research To Generate Effective Treatments (TARGET), the International Cancer Genome Consortium (ICGC) and the Children’s Brain Tumor Tissue Consortium (CBTTC) were included in this study. We applied computational tumor immune microenvironment deconvolution, repurposed RNA-seq data to recover infiltrating T- and B-cell clonotypes and studied checkpoint gene expression across pediatric neural tumors. ResultsAmong pediatric neural tumors, embryonal tumors with multilayered rosettes (ETMR) and medulloblastomas (MB) were least immune infiltrated. Neuroblastomas (NBL) had the highest T-cell infiltration among pediatric cancers, while atypical teratoid/rhabdoid tumors (ATRT) had the highest levels of CD8 T cell infiltration among pediatric CNS tumors. While tumor mutational burden (TMB) was associated with immune cell infiltration in adult lung cancers and melanomas, we found no significant associations in pediatric cancers. The majority of NBL samples expressed LAG3, but ~10% of samples had elevated levels of TIM3 gene expression, suggesting a distinct mode of immunosuppression in this subset.

A pediatric brain tumor atlas of genes deregulated by somatic genomic rearrangement

The global impact of somatic structural variants (SSVs) on gene expression in pediatric brain tumors has not been thoroughly characterised. Here, using whole-genome and RNA sequencing from 854 tumors of more than 30 different types from the Children’s Brain Tumor Tissue Consortium, we report the altered expression of hundreds of genes in association with the presence of nearby SSV breakpoints. SSV-mediated expression changes involve gene fusions, altered cis-regulation, or gene disruption. SSVs considerably extend the numbers of patients with tumors somatically altered for critical pathways, including receptor tyrosine kinases (KRAS, MET, EGFR, NF1), Rb pathway (CDK4), TERT, MYC family (MYC, MYCN, MYB), and HIPPO (NF2). Compared to initial tumors, progressive or recurrent tumors involve a distinct set of SSV-gene associations. High overall SSV burden associates with TP53 mutations, histone H3.3 gene H3F3C mutations, and the transcription of DNA damage response genes. Compared to adult cancers, pediatric brain tumors would involve a different set of genes with SSV-altered cis-regulation. Our comprehensive and pan-histology genomic analyses reveal SSVs to play a major role in shaping the transcriptome of pediatric brain tumors.

Systematic identification of non-coding somatic single nucleotide variants associated with altered transcription and DNA methylation in adult and pediatric cancers.

Whole-genome sequencing combined with transcriptomics can reveal impactful non-coding single nucleotide variants (SNVs) in cancer. Here, we developed an integrative analytical approach that, as a first step, identifies genes altered in expression or DNA methylation in association with nearby somatic SNVs, in contrast to alternative approaches that first identify mutational hotspots. Using genomic datasets from the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium and the Children's Brain Tumor Tissue Consortium (CBTTC), we identified hundreds of genes and associated CpG islands for which the nearby presence of a non-coding somatic SNV recurrently associated with altered expression or DNA methylation, respectively. Genomic regions upstream or downstream of genes, gene introns and gene untranslated regions were all involved. The PCAWG adult cancer cohort yielded different significant SNV-expression associations from the CBTTC pediatric brain tumor cohort. The SNV-expression associations involved a wide range of cancer types and histologies, as well as potential gain or loss of transcription factor binding sites. Notable genes with SNV-associated increased expression include TERT, COPS3, POLE2 and HDAC2—involving multiple cancer types—MYC, BCL2, PIM1 and IGLL5—involving lymphomas—and CYHR1—involving pediatric low-grade gliomas. Non-coding somatic SNVs show a major role in shaping the cancer transcriptome, not limited to mutational hotspots.

The spectrum of mitochondrial DNA (mtDNA) mutations in pediatric CNS tumors.

BackgroundWe previously established the landscape of mitochondrial DNA (mtDNA) mutations in 23 subtypes of pediatric malignancies, characterized mtDNA mutation profiles among these subtypes, and provided statistically significant evidence for a contributory role of mtDNA mutations to pediatric malignancies.MethodsTo further delineate the spectrum of mtDNA mutations in pediatric central nervous system (CNS) tumors, we analyzed 545 tumor-normal paired whole-genome sequencing datasets from the Children’s Brain Tumor Tissue Consortium.ResultsGermline mtDNA variants were used to determine the haplogroup, and maternal ancestry, which was not significantly different among tumor types. Among 166 (30.5%) tumors we detected 220 somatic mtDNA mutations, primarily missense mutations (36.8%), as well as 22 loss-of-function mutations. Different pediatric CNS tumor subtypes had distinct mtDNA mutation profiles. The number of mtDNA mutations per tumor ranged from 0.20 (dysembryoplastic neuroepithelial tumor [DNET]) to 0.75 (meningiomas). The average heteroplasmy was 10.7%, ranging from 4.6% in atypical teratoid/rhabdoid tumor (AT/RT) to 26% in diffuse intrinsic pontine glioma. High-grade gliomas had a significant higher number of mtDNA mutations per sample than low-grade gliomas (0.6 vs 0.27) (P = .004), with almost twice as many missense mtDNA mutations per sample (0.24 vs 0.11), and higher average heteroplasmy levels (16% vs 10%). Recurrent mtDNA mutations may represent hotspots which may serve as biologic markers of disease.ConclusionsOur findings demonstrate varying contributions of mtDNA mutations in different subtypes of CNS tumors. Sequencing the mtDNA genome may ultimately be used to characterize CNS tumors at diagnosis and monitor disease progression.

IMMU-30. UPREGULATED T CELL AND INTERFERON-Γ-RELATED GENE EXPRESSION IS ASSOCIATED WITH INCREASED SURVIVAL IN RECURRENT PEDIATRIC HIGH-GRADE GLIOMA

Recurrent pediatric high-grade glioma (pHGG) is the leading cause of cancer-related mortality in children. Immunotherapy is a successful treatment approach for a growing number of cancers and is being investigated as a treatment strategy for pHGG. Immunotherapy has shown the most benefit in tumors with increased infiltrating T cells at baseline. Our recently published results revealed that neoadjuvant checkpoint inhibition in recurrent adult glioblastoma was associated with upregulation of a T cell and interferon-γ-related gene expression signature (Tcell-IFNγGES) and was correlated with a significantly extended overall survival (OS). In this study, we examined the immune landscape in recurrent pHGG and the association of Tcell-IFNγGES in the tumor with survival. We analyzed tumor RNAseq data collected at time of recurrence from a historical cohort of 42 pHGG patients from the Children’s Brain Tumor Tissue Consortium. We found a significant transcriptional enrichment of Tcell-IFNγGES in 54% of the tumors. The survival of patients with high Tcell-IFNγGES was observed to be significantly higher than patients with low Tcell-IFNγGES, (log-rank p=0.05). The 3-year OS for patients with low versus high Tcell-IFNγGE was 28.5% (95%, CI:13.7%-59.5%) compared to 50.2% (95%, CI:33.1%-76.1%). When patients were stratified by age, gender and race, low Tcell-IFNγGES was found to be a poor OS prognostic factor (hazard ratio=2.4 (1.14–5.14), p=0.02). This indicates a strong relationship of decreased Tcell-IFNγGES and increased risk of death. Future investigations are necessary to validate these findings, and to explore the value of Tcell-IFNγGES as a predictive biomarker for response to immunotherapy in pHGG.

TBIO-12. THE SPECTRUM OF MITOCHONDRIAl DNA (mtDNA) MUTATIONS IN PEDIATRIC CENTRAL NERVOUS SYSTEM (CNS) TUMORS

To explore the role of mitochondrial DNA mutations in pediatric CNS tumors, we analyzed 749 tumor-normal paired whole genome sequencing data sets from the Children’s Brain Tumor Tissue Consortium (CBTTC). We detected 307 somatic mtDNA mutations in 222 CNS tumors (29.6%). Most frequently observed were missense mutations (38.1%). We also detected 34 loss-of-function mutations. Different pediatric CNS tumor subtypes have distinct mtDNA mutation profiles. For categorical comparisons, we analyzed subtypes with at least 15 samples. The highest number of mtDNA mutations per tumor sample was in meningiomas (0.85), while atypical teratoid rhabdoid tumors (ATRTs) had the lowest number per sample (0.18). High-grade gliomas had a higher number of mtDNA mutations per sample than low-grade gliomas (0.56 vs. 0.31) (p = 0.0011), with almost twice as many missense mtDNA mutations per sample (0.22 vs. 0.13) (p < 0.001), and higher average heteroplasmy levels (11% vs. 9%). The average heteroplasmy was 10.1%, ranging from 15.6% in medulloblastoma to 6.36% in schwannoma suggesting that these are clonal alterations and not artifacts. Intriguingly, the two chordoma patients in the CBTTC database had an identical heteroplasmic m.10971G>A MT-ND4 nonsense mutation. Similarly, our patient with recurrent gliofibroma harbored the same somatic MT-ND4 synonymous variant (m.10700A>G) detected at 53% heteroplasmy in the initial tumor, 79% in the first recurrence, and 97% in the second recurrence. Although the functional consequences of these alterations are not yet understood, our findings suggest that sequencing the mtDNA genome may be used to characterize CNS tumors at diagnosis and monitor disease progression.

RARE-57. PEDIATRIC CHORDOMA: WHOLE EXOME SEQUENCING OF 11 PEDIATRIC CHORDOMA SAMPLES

Chordoma is a rare tumor and while SMARCB1 alterations have been observed in poorly differentiated chordomas, conventional chordomas are not well understood. We interrogated nuclear and mitochondrial genomes of 11 chordoma samples from 7 children. Frozen tumor tissue DNA was extracted and whole exome libraries generated using Agilent SureSelect Human All Exon V6 kit plus mtDNA genome capture kit. Libraries were sequenced using Illumina Nextseq 500. MuTect2, VarDict and LUBA variant callers were used with allele frequency cutoff 2%. Potential germline variants were filtered bioinformatically. In total, 656±74 high-confidence somatic variants, including 368±43 nonsynonymous variants per sample were detected. Of 2,607 combined unique nonsynonymous variants, 95% were missense. Remaining high impact variants were frameshift (37%), stop gain (39%), splice acceptor/donor (22%), start and stop loss (2%). Of the unique nonsynonymous variants, 137 fall within Cosmic Cancer Census Genes, including high impact variants in SETD2, MLLT4. No previously reported TBXT, CDKN2A, PI3K, LYST mutations identified. Tumor Mutation Burden/Megabase was 10±1. The mitochondrial analysis revealed heteroplasmic m.11727C>T MT-ND4 missense variants in three tumors resected at different time points from the same patient, and another heteroplasmic m.1023C>T rRNA mutation from the primary and recurrent tumors of another patient. Intriguingly, two Children’s Brain Tumor Tissue Consortium patients with chordoma had identical heteroplasmic m.10971G>A MT-ND4 nonsense mutations. Pediatric chordomas appear to lack somatic nuclear mutations. Observing recurrent mitochondrial mutations across multiple tumors from the same and/or different patients is striking, suggesting they may be implicated in tumorigenesis and be potential diagnostic markers.

YAP1-FAM118B Fusion Defines a Rare Subset of Childhood and Young Adulthood Meningiomas.

Meningiomas are a central nervous system tumor primarily afflicting adults, with <1% of cases diagnosed during childhood or adolescence. Somatic variation in NF2 may be found in ∼50% of meningiomas, with other genetic drivers (eg, SMO, AKT1, TRAF7) contributing to NF2 wild-type tumors. NF2 is an upstream negative regulator of YAP signaling and loss of the NF2 protein product, Merlin, results in YAP overexpression and target gene transcription. This mechanism of dysregulation is described in NF2-driven meningiomas, but further work is necessary to understand the NF2-independent mechanism of tumorigenesis. Amid our institutional patient-centric comprehensive molecular profiling study, we identified an individual with meningioma harboring a YAP1-FAM118B fusion, previously reported only in supratentorial ependymoma. The tumor histopathology was remarkable, characterized by prominent islands of calcifying fibrous nodules within an overall collagen-rich matrix. To gain insight into this finding, we subsequently evaluated the genetic landscape of 11 additional pediatric and adolescent/young adulthood meningioma patients within the Children's Brain Tumor Tissue Consortium. A second individual harboring a YAP1-FAM118B gene fusion was identified within this database. Transcriptomic profiling suggested that YAP1-fusion meningiomas are biologically distinct from NF2-driven meningiomas. Similar to other meningiomas, however, YAP1-fusion meningiomas demonstrated overexpression of EGFR and MET. DNA methylation profiling further distinguished YAP1-fusion meningiomas from those observed in ependymomas. In summary, we expand the genetic spectrum of somatic alteration associated with NF2 wild-type meningioma to include the YAP1-FAM118B fusion and provide support for aberrant signaling pathways potentially targetable by therapeutic intervention.

Abstract PR06: The immunogenomic landscape of pediatric primary solid tumors

Abstract Introduction: Immune checkpoint inhibition is a novel approach of restimulating immune cells to overcome immunosuppressive microenvironment in tumors and has shown significant clinical benefit in 20-40% of adult patients. Although this success in adult cancers has resulted in a plethora of immunogenomic efforts to delineate mechanisms of response, such studies in pediatric cancers are lacking. The main objective of this study is to uncover the overall characteristics of immune microenvironment in pediatric solid tumors. Methods: We leveraged transcriptomes of 1,268 pediatric primary solid tumors acquired from multiple international initiatives, including Therapeutically Applicable Research to Generate Effective Treatments (TARGET, n = 269), International Cancer Genome Consortium (ICGC, n = 216) and Children Brain Tumor Tissue Consortium (CBTTC, n = 803). We compared our results with those of 7 adult cancer types from The Cancer Genome Atlas (TCGA, n = 2720). We applied methods of immune deconvolution, repurposed RNAseq data to recover infiltrating T- and B-cell clonotypes and studied checkpoint gene expression in pediatric tumors. In collaboration with Gabriela Miller’s Kids First Data Resource Centre, all analyses were performed and shared on CAVATICA computational platform (cavatica.sbgenomics.com). Results: Embryonal tumors with multilayered rosettes (ETMR) and medulloblastomas (MB) harbored the lowest levels of immune infiltration in our pediatric cohort. Immune deconvolution analysis revealed that neuroblastomas (NBL) had the highest T-cell infiltration amongst pediatric cancers. We found atypical teratoid/rhabdoid tumors (ATRT) had highest levels of CD8+ T cells among pediatric CNS tumors. While tumor mutational burden (TMB) was associated with immune cell infiltration in adult lung cancers and melanomas, we found no significant association in pediatric cancers. We found specific genetic alterations such as BRAF, H3F3A, and CTNNB1 had significant impact on the composition of the immune microenvironment. Analysis of T-cell repertoire revealed an inverse correlation between clonal diversity and TMB, suggesting a T-cell clonal expansion in high TMB samples. Finally, while the majority of NBL samples expressed LAG3, ~10% of samples had elevated levels of TIM3 gene, suggesting a distinct mode of immunosuppression in this subset. 2% of pediatric CNS tumors, mostly consisted of ATRTs, harbored high expression of PRF1 and GZMA genes suggestive of functionally capable immune cells in these cases. Conclusions: We report characteristics of the tumor microenvironment in pediatric tumors at primary diagnosis. We found that specific gene mutations, rather than mutational load, shape the composition of immune cell types. Furthermore, hypermutant samples exhibit evidence of clonal T-cell expansion. Our results suggest immune activity in 2% of CNS tumors and uncover a subtype of NBL expressing TIM3 checkpoint gene, calling for investigations to evaluate the effectiveness of immunotherapy. This abstract is also being presented as Poster A74. Citation Format: Arash Nabbi, Pengbo Sun, Sudhaman Sumedha, Kelsey Zhu, S.Y. Cindy Yang, Joseph N. Paulson, Marcel Kool, Komal Rathi, Karthik Kalletla, Pichai Raman, Yuankun Zhu, Adam C. Resnick, David T.W. Jones, Natalie Jäger, Stefan M. Pfister, Trevor J. Pugh. The immunogenomic landscape of pediatric primary solid tumors [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 PR06.

Development of cancer prognostic signature based on pan-cancer proteomics

ABSTRACT Utilizing genomic data to predict cancer prognosis was insufficient. Proteomics can improve our understanding of the etiology and progression of cancer and improve the assessment of cancer prognosis. And the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has generated extensive proteomics data of the vast majority of tumors. Based on CPTAC, we can perform a proteomic pan-carcinoma analysis. We collected the proteomics data and clinical features of cancer patients from CPTAC. Then, we screened 69 differentially expressed proteins (DEPs) with R software in five cancers: hepatocellular carcinoma (HCC), children’s brain tumor tissue consortium (CBTTC), clear cell renal cell carcinoma (CCRC), lung adenocarcinoma (LUAD) and uterine corpus endometrial carcinoma (UCEC). GO and KEGG analysis were performed to clarify the function of these proteins. We also identified their interactions. The DEPs-based prognostic model for predicting over survival was identified by least absolute shrinkage and selection operator (LASSO)-Cox regression model in training cohort. Then, we used the time-dependent receiver operating characteristics analysis to evaluate the ability of the prognostic model to predict overall survival and validated it in validation cohort. The results showed that the DEPs-based prognostic model could accurately and effectively predict the survival rate of most cancers.

PDTM-16. PEDIATRIC HIGH GRADE GLIOMA RESOURCES FROM THE CHILDREN’S BRAIN TUMOR TISSUE CONSORTIUM (CBTTC) AND PEDIATRIC BRAIN TUMOR ATLAS (PBTA)

Abstract BACKGROUND Pediatric high grade glioma (pHGG) remains a fatal disease. Access to richly annotated biospecimens and patient derived tumor models will accelerate pHGG research and support translation of research discoveries. This work describes the pediatric high grade glioma set of the Children’s Brain Tumor Tissue Consortium (CBTTC) from the first release of the Pediatric Brain Tumor Atlas (PBTA). METHODS pHGG tumors with associated clinical data and imaging were prospectively collected through the CBTTC and analyzed as the Pediatric Brain Tumor Atlas (PBTA) with processed genomic data deposited into PedcBioPortal for broad access and visualization. Matched tumor was cultured to create high grade glioma cell lines analyzed by targeted and WGS and RNA-seq. A tissue microarray (TMA) of primary pHGG tumors was also created. RESULTS The pHGG set includes 87 collection events (73 patients, 60% at diagnosis, median age of 9 yrs, 55% female, 46% hemispheric). Operative reports, pathology reports and histology images are available for nearly all cases. Pre- and post-operative MRI images and reports are also available for a subset. Tumor WGS/RNAseq is available for 70 subjects. Analysis of somatic mutations and copy number alterations of known glioma genes were of expected distribution (36% H3.3, 47% TP53, 24% ATRX and 7% BRAFV600E variants). In our panel of pHGG, six patients (8 tumors) harbored germline mismatch repair mutations with tumor hyper-mutation. A pHGG TMA (n=77), includes 36 patient tumors with matched sequencing. At least one established glioma cell line was generated from 23 patients (32%). Unique reagents include those derived from a H3.3 G34R glioma and from tumors with mismatch repair deficiency. CONCLUSION The CBTTC and PBTA have created an openly available integrated resource of over 2,000 tumors, including a rich set of pHGG primary tumors, corresponding cell lines and archival fixed tissue to advance translational research for pHGG.

Pediatric high-grade glioma resources from the Children's Brain Tumor Tissue Consortium.

Pediatric high-grade glioma resources from the Children's Brain Tumor Tissue Consortium.

Abstract 3667: The Pediatric Brain Tumor Atlas - Transforming the landscape of research

Abstract The Pediatric Brain Tumor Atlas (PBTA) is a cloud-based, cross-platform, and data-rich collaborative effort to accelerate discoveries for therapeutic intervention in children diagnosed with brain tumors. Pediatric brain tumors are the leading cause of disease-related death in children and despite advances in therapy, morbidity and mortality rates remain poor. There have been large scale efforts to genomically profile these cancers in the past, however public access to the resulting datasets are limited at best. In contrast, the PBTA, created as a multi-center effort by Children’s Brain Tumor Tissue Consortium (CBTTC) and Pacific Pediatric Neuro-Oncology Consortium (PNOC), has a goal of characterizing over 1,600 pediatric brain tumor samples and making the data publicly available to cancer researchers world-wide. PBTA comprises comprehensive clinical data in addition to whole exome sequencing, whole genome sequencing (WGS), RNA sequencing (RNASeq), miRNA sequencing, and proteomics. To address the need to inform novel discovery and clinical implementation of genomic approaches for diagnostic/therapeutic purposes, PBTA utilizes a cloud-based scientific environment, the CAVATICA portal. CAVATICA provides near real-time integration, dissemination, processing, and sharing of associated PetaByte-sized data by leveraging Amazon Web Services and powerful genomic workflows. It also enables dbGaP approved users to access TCGA and other datasets hosted by NCI’s Cancer Genomics’ Cloud, allowing for cross-disease studies. While CAVATICA manages raw sequencing data, processed annotations and biospecimen querying is enabled for PBTA via PedcBioPortal, a data visualization/analysis application further integrating additional public and deposited datasets. PBTA data can further be accessed via the KidsFirst platform, which integrates both CAVATICA and PedcBioPortal, and allows for querying of cancer and non-cancer genomic data for subsequent analytics, visualization, and discovery. The 1st dataset release of PBTA occurred on September 10th, 2018. In this release there are over 30 different types of pediatric brain tumors representing over 1,000 subjects. This data is available on CAVATICA, KidsFirst, and PedcBioPortal and users can seamlessly move between applications. Data types include those for matched tumor/normal samples, such as WGS, RNASeq, proteomics, longitudinal clinical data, imaging data (MRIs and radiology reports), histology slide images, and pathology reports. CBTTC/PNOC promote real time data release with no embargo period, allowing PBTA to have is up-to-date data releases with no embargo. The combination of cloud-based analytic platforms such as KidsFirst/CAVATICA/PedcBioPortal with data from both genomics and clinical practice serves to define a new paradigm for pediatric cancer research and collaborative discovery. Citation Format: Yuankun Zhu, Yiran Guo, Allison P. Heath, Pichai Raman, Elizabeth Appert, Jennifer Mason, Bo Zhang, Karthik Kalletla, Miguel A. Brown, Natasha Singh, Bailey K. Farrow, Parimala Killada, Meen Chul Kim, Alex Felmeister, Mateusz P. Koptyra, Sabine Mueller, Michael Prados, Jena V. Lilly, Rishi Lulla, Adam C. Resnick, Javad Nazarian, Phillip B. Storm, Angela J. Waanders. The Pediatric Brain Tumor Atlas - Transforming the landscape of research [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 3667.

Abstract 2891: Landscape of infiltrating immune repertoire in pediatric solid tumors

Abstract Introduction: Immune repertoire is a highly diverse pool of B and T cell receptors (B/TCR) that determine boundaries of immune surveillance. Pre-existing immune clones within Tumor MicroEnvironment (TME) suggest existence of a functional antigen presenting machinery and recognizing T cells, which fail to eliminate tumor, likely due to immunosuppressive environment. Shifts in composition of immune repertoire upon immune checkpoint blockade have been reported in adult cancers and shown to be associated with clinical response. As immunotherapy is being introduced to pediatric oncology, there is a need to better understand immunogenomic aspects of TME in childhood cancers. Objective: We hypothesize that characteristics of TCRs in conjunction with gene expression profile of immune cells are key determinants of immune response in pediatric patients. Methods: We compiled a pan-pediatric cohort and associated RNAseq datasets through multiple research initiatives. Participating programs include NCI TARGET (n ~ 270), International Cancer Genome Consortium (ICGC, n ~ 250) and Children’s Brain Tumor Tissue Consortium (CBTTC, n ~ 790). As comparator, we analyzed 7 adult cancer types as well as data from constitutive mismatch repair deficiency (CMMRD) consortium. We devised a simple and reliable index to estimate immune diversity. We used CIBERSORT tool to infer immune fraction of TME and investigated immune-related gene expression. In partnership with Gabriela Miller’s Kids First Data Resource Centre, analyses were performed on CAVATICA computational platform. Results: While median number of RNAseq reads were comparable across TARGET, CBTTC and TCGA datasets (~ 67-90 million reads), ICGC dataset contained a median of ~ 208 million reads. However, number of reads mapped to immune loci were comparable across all datasets and appeared to be confounded by infiltration extent rather than technical discordance. Our preliminary results indicate Neuroblastoma harbored the highest median of inferred diversity across pediatric cancers (TRβ=59.38). Inferred immune content indicated a range of infiltration from 0.59 in Teratoma/Germinoma to 0.15 in Medulloblastoma. Immune checkpoint gene expression across pediatric cancers show overall downward trend compared to adult counterparts. Conclusions: Our comprehensive study will serve as a common ground for researchers to delineate immune component of pediatric tumor microenvironment. Covered in this study are common solid tumors as well as rare malignancies, characterization of which will aid rational design of immunotherapy-related clinical trials of pediatric cancers. Note: This abstract was not presented at the meeting. Citation Format: Arash Nabbi, Natalie Jäger, Sumedha Sudhaman, Pengbo Sun, S. Y. Cindy Yang, Kelsey Zhu, Marcel Kool, Komal Rathi, Karthik Kalletla, Pichai Raman, Yuankun Zhu, Joseph N. Paulson, David T. Jones, Uri Tabori, Adam C. Resnick, Stefan M. Pfister, Trevor J. Pugh. Landscape of infiltrating immune repertoire in pediatric solid tumors [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 2891.

Abstract 2081: Empowering rare disease cohort biomarker discovery via comparative assessments of gene expression analysis platforms for FFPE pediatric brain tumor specimens

Abstract The gene expression landscape for biomarker discovery is still limited for many pediatric brain tumors due to insufficient numbers of biorepository collected fresh frozen specimens. The majority of available tissue are formalin-fixed paraffin embedded (FFPE) pathology diagnostic specimens. These specimens, are often of limited quantity and contain compromised RNA material. A number of emerging commercial platforms are described as supporting quantitative expression analysis for low quantity and poor quality materials. Utilizing available platforms, we designed a study to evaluate RNA and miRNA levels in pediatric brain tumor FFPE specimens with limited/compromised access.Experiments were performed with specimens and/or data obtained from Brain Tumor Tissue Consortium (CBTTC) at Children's Hospital of Philadelphia (CHOP). The mRNA gene expression and miRNA target analysis were performed with FFPE material utilizing two commercial platforms: HTG EdgeSeq and Nanostring. The analysis included 5 specimens of low grade glioma or primitive neuroectodermal tumors for mRNA gene expression and 4 specimens of medulloblastoma for miRNA target analysis. FFPE specimens were processed according to manufacturer's protocols. The results were compared with the RNAseq or miRNA sequencing data derived from corresponding tumors' flash frozen specimens' RNA material. We evaluated requirements of each platform for data generation and established between platform analysis correlations. In performed tests, the HTG platform required lowest amounts of specimen's material. For the majority of analyzed genes (&amp;gt;700 genes), the gene expression profile was relatively similar between all three approaches, however each of the platform presented distinctive distribution profile for normalized data. The RNAseq mean read counts values were correlated highly with NanoString (0.81) and of lesser value with HTG (0.7) platform. The RNAseq presented significantly higher variance distribution than other platforms. The miRNA target analysis (&amp;gt;600 genes) distribution of normalized data revealed significantly lower dynamics for NanoString when compared with miRNAseq or HTG panel data. The miRNA mean read counts were highly correlated with HTG (0.77) and little with NanoString (0.22), while miRNASeq presented the highest variance distribution. In summary, we found a significant level of agreement between all three platforms tested for gene expression data generation. As for miRNA target analysis, the HTG platform presented significantly higher agreement with miRNAseq data. We conclude that tested technologies can support data generation from archived FFPE specimens, however, the platform selection process should involve pre-selection data quality analysis, as well as sample size requirements, gene cohort selection, and pricing evaluations. Citation Format: Mateusz P. Koptyra, Namrata Choudhari, Zhang Zhe, Mariarita Santi, Angela Waanders, Adam Resnick. Empowering rare disease cohort biomarker discovery via comparative assessments of gene expression analysis platforms for FFPE pediatric brain tumor specimens [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 2081.

Late Breaking Abstracts.

Late Breaking Abstracts.

Abstract 2593: Accelerating pediatric brain tumor research through team science solutions

Abstract Introduction: The Children’s Brain Tumor Tissue Consortium (CBTTC), an international repository of genomic and phenotypic data, has partnered with Blackfynn, Inc., to create a cloud-based data management platform to facilitate team-science across disciplines. Background: The CBTTC through the CHOP Department of Biomedical and Health Informatics (DBHi) has developed a network of informatics and data applications for researchers across the globe to work together and perform real-time analyses on existing clinical, phenotypic, and genomic data. Historically, rare disease datasets are siloed, locked in proprietary formats, segregated by data types, and hidden from the view of experts in the field. This has been a significant barrier to finding effective therapeutics for children with pediatric brain tumors. Blackfynn was founded by a group of multidisciplinary experts in neuroscience, neurology, medicine, software development, engineering, computer science and business with the goal to empower researchers to cure neurologic disease and provide solutions to these challenges. Description of Methods: The CBTTC and Blackfynn teamed up to provide a cloud-based, team-focused data management and analytics platform. The platform provides a commercial grade, scalable approach to upload, view, and integrate digital pathology images with relevant subject data such as MRIs, pathology reports and genomic information. Stakeholders can search integrated data without requiring users to change their current workflow or conform to imposed data standards. This platform is a simple, intuitive, end-to-end software platform for teams of scientists and pathologists to review, annotate and discuss cases, enabling rapid diagnostic consensus, quality control, and empowered discovery. Summary of Unpublished Results: The CBTTC/Blackfynn data platform enabled CBTTC members to engage in a cross-institutional collaboration to reach consensus on digital pathology data in ways that were previously not possible. We demonstrated that this solution removes existing barriers to collaborative efforts and provides a rich analytic and discovery platform bridging imaging with genomics and other data formats. The platform provides a new model for the scientific community to facilitate translation towards improved treatments for children diagnosed with brain tumors. Discussion and Future Direction: This pilot project will be scaled to other CBTTC sites for centralized review of pathology images to enable the research community to collaborative on specific projects. The next phase of platform development will include further integration CBTTC platforms fully integrating genomics data, and side-by-side viewing and analyses of MRI, pathology and clincal data to facilitate specific project work around large and complex research data types in a cloud environment. Citation Format: Amanda Christini, Angela J. Waanders, Joost B. Wagenaar, Alex S. Felmeister, Mariarita Santi, Nitin R. Wadhwani, Jennifer L. Mason, Mateusz P. Koptyra, Jena V. Lilly, Jeffrey W. Pennington, Rishi R. Lulla, Adam C. Resnick. Accelerating pediatric brain tumor research through team science solutions [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 2593. doi:10.1158/1538-7445.AM2017-2593

Abstract A051: Characterization of IDO1 and TDO2 in pediatric central nervous system tumors

Abstract Purpose: Indoleamine 2,3 dioxygenase 1 (IDO1) and tryptophan dioxygenase (TDO2) are tryptophan catabolic enzymes that have been implicated in facilitating immunosuppression in cancer. With respect to the central nervous system (CNS), both enzymes have been correlated with decreased overall survival in adult patients with glioma. Based on these observations, we questioned whether pediatric CNS tumors, which constitute the most common form of solid cancer in children, also possess expression and activity for these immunosuppressive mediators. Experimental Design: Purified RNA from pediatric patient tumor tissue was obtained from the Children's Brain Tumor Tissue Consortium (Philadelphia, PA) and utilized for qRT-PCR analysis of IDO1, TDO2, CD3e, IFNγ, and TGFβ1. Primary cell lines were propagated from fresh tumor tissue acquired by Dr. Rintaro Hashizume, Ph.D. (Northwestern University) and cultured for 48 hours alone or with a combination of 100 ng/mL IFNγ and 10, 50, 250 or 1000 nM L1MT, D1MT and BGB-5777; a novel pharmaceutical-grade IDO1 inhibitor (Beigene). Cell culture supernatants were collected at 48 hours for detection of tryptophan (Trp) and kynurenine (Kyn) levels by high pressure liquid chromatography. The cells were collected confirmed for IDO1 protein expression via western blot. Results: RT-PCR defined two populations of pediatric high grade glioma (HGG) based on high (&amp;gt;3 fold expression compared to average) versus low (&amp;lt;3 fold expression compared to average) IDO1-expressing tumors. In contrast, low grade glioma (LGG) and diffuse intrinsic pontine glioma (DIPG) universally expressed low IDO1 levels when compared to HGG. All patient tumors expressed TDO2 mRNA. All tumors were infiltrated by T cells, based on the ubiquitous presence of CD3ϵ mRNA. Primary human pediatric cell lines comprised of HGG and DIPG inducibly expressed IDO1 mRNA and protein after treatment IFNγ (P &amp;lt; 0.001). Unexpectedly, IFNγ treatment also led to increased TDO2 mRNA expression in DIPG cells. To determine whether these enzymes were functionally active, BGB-5777, in addition to historical IDO1 pathway modulators, L1-MT and D1-MT, were co-incubated with the pediatric cell lines plus IFNγ. At 250 nM, BGB-5777 significantly decreased the Kyn/Trp ratio in both HGG and DIPG cell lines (p&amp;lt;0.001), while treatment with L1-MT and D1-MT concentrations had no impact. Conclusion: These data show for the first time that, IDO1 is expressed in pediatric tumors and the novel blood brain barrier-penetrating IDO1 inhibitor, BGB-5777, is a highly potent inhibitor of enzymatic activity in this setting. Given that IDO1 inhibitors are already in multiple clinical trials for adults with brain cancer, these data suggest that BGB-5777 may be a valuable tool for inhibiting IDO1 in the setting of malignant pediatric brain cancer. Citation Format: Kristen Lauing, Rishi Lulla, Lijie Zhai, Rintaro Hashizume, Jason Fangusaro, Derek A. Wainwright. Characterization of IDO1 and TDO2 in pediatric central nervous system tumors [abstract]. In: Proceedings of the Second CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; 2016 Sept 25-28; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(11 Suppl):Abstract nr A051.