A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma

Pediatric high-grade glioma (pHGG) is an incurable central nervous system malignancy that is a leading cause of pediatric cancer death. While pHGG shares many similarities to adult glioma, it is increasingly recognized as a molecularly distinct, yet highly heterogeneous disease. In this study, we longitudinally profiled a molecularly diverse cohort of 16 pHGG patients before and after standard therapy through single-nucleus RNA and ATAC sequencing, whole-genome sequencing, and CODEX spatial proteomics to capture the evolution of the tumor microenvironment during progression following treatment. We found that the canonical neoplastic cell phenotypes of adult glioblastoma are insufficient to capture the range of tumor cell states in a pediatric cohort and observed differential tumor-myeloid interactions between malignant cell states. We identified key transcriptional regulators of pHGG cell states and did not observe the marked proneural to mesenchymal shift characteristic of adult glioblastoma. We showed that essential neuromodulators and the interferon response are upregulated post-therapy along with an increase in non-neoplastic oligodendrocytes. Through in vitro pharmacological perturbation, we demonstrated novel malignant cell-intrinsic targets. This multiomic atlas of longitudinal pHGG captures the key features of therapy response that support distinction from its adult counterpart and suggests therapeutic strategies which are targeted to pediatric gliomas.

Recent Developments in Blood Biomarkers in Neuro-oncology

PURPOSE OF REVIEW

Given the invasive and high-risk nature of brain surgery, the need for non-invasive biomarkers obtained from the peripheral blood is greatest in tumors of the central nervous system (CNS). In this comprehensive review, we highlight recent advances in blood biomarker development for adult and pediatric brain tumors.

RECENT FINDINGS

We summarize recent blood biomarker development for CNS tumors across multiple key analytes, including peripheral blood mononuclear cells, cell-free DNA, cell-free RNA, proteomics, circulating tumor cells, and tumor-educated platelets. We also discuss methods for enhancing blood biomarker detection through transient opening of the blood-brain barrier. Although blood-based biomarkers are not yet used in routine neuro-oncology practice, this field is advancing rapidly and holds great promise for improved and non-invasive management of patients with brain tumors. Prospective and adequately powered studies are needed to confirm the clinical utility of any blood biomarker prior to widespread clinical implementation.

OpenPBTA: The Open Pediatric Brain Tumor Atlas

Pediatric brain and spinal cancers are collectively the leading disease-related cause of death in children; thus, we urgently need curative therapeutic strategies for these tumors. To accelerate such discoveries, the Children's Brain Tumor Network (CBTN) and Pacific Pediatric Neuro-Oncology Consortium (PNOC) created a systematic process for tumor biobanking, model generation, and sequencing with immediate access to harmonized data. We leverage these data to establish OpenPBTA, an open collaborative project with over 40 scalable analysis modules that genomically characterize 1,074 pediatric brain tumors. Transcriptomic classification reveals universal TP53 dysregulation in mismatch repair-deficient hypermutant high-grade gliomas and TP53 loss as a significant marker for poor overall survival in ependymomas and H3 K28-mutant diffuse midline gliomas. Already being actively applied to other pediatric cancers and PNOC molecular tumor board decision-making, OpenPBTA is an invaluable resource to the pediatric oncology community.

Abstract 3566: Expansion of the Pediatric Brain Tumor Atlas: Children's Brain Tumor Network, Kids First Data Resource and Childhood Cancer Data Initiative Open Science effort

Pediatric central nervous system (CNS) cancers are the leading disease-related cause of death in children and there is urgent need for curative therapeutic strategies for these tumors. To address the urgency, Children’s Brain Tumor Network (CBTN) has advanced an open science model to accelerate the research discovery for pediatric brain tumors. In first phase of Open Pediatric Brain Tumor Atlas (OpenPBTA) effort CBTN together with Pacific Pediatric Neuro-Oncology Consortium (PNOC) with support of Gabriella Miller Kids First Data Resource Center (KFDRC) created and comprehensively characterized over 1000 clinically annotated pediatric brain tumors.

In the second phase of the OpenPBTA effort, through resource awards and collaboration across KFDRC, the NCI Childhood Cancer Data Initiative (CCDI), NCI’s Clinical Proteomic Tumor Analysis Consortium (CPTAC), NCI Center for Cancer Research and additional partnered institutions and foundations, CBTN has expanded OpenPBTA to support high throughput molecular characterization for an additional 1900 pediatric brain tumor patients and their families. This includes the processing and characterization of over 8000 specimens across >50 brain tumor diagnoses. The cohort expansion builds on >1000 previously characterized samples with a portfolio of multimodal data including whole genome sequencing, RNA sequencing, miRNA sequencing, methylation sequencing, proteomics, lipidomics and/or metabolomics. Molecular data is linked to patient longitudinal clinical data, imaging data (MRIs and radiology reports), histology slide images, and pathology reports. To inform novel discovery and clinical implementation of genomic approaches for diagnostic/therapeutic purposes, the data is deposited the cloud-based research environment of the NCI’s CCDI and the KFDRC to provide near real-time integration, dissemination, processing, and sharing of associated petabyte-scale harmonized data. The approach leverages the DRC platform’s cloud-based computational environment in CAVATICA. Processed annotations are facilitated via CAVATICA-enabled shareable pipelines and can be explored through PedcBioPortal, a data visualization/analysis application further integrating additional public and deposited datasets. This expansion phase of OpenPBTA is released with no embargo period and provides one of the largest deeply characterized cohorts of pediatric brain tumor samples and associated clinical data for >3000 pediatric brain tumor patients. CBTN’s open-science, rapid-release model aims to advance novel biomarkers and therapeutic exploratory research, supporting new clinical trial development and accelerated discovery on behalf of changing the outcome for kids with brain tumors.

Citation Format: Mateusz P. Koptyra, Komal Rahti, Yuankun Zhu, Bailey Farrow, Daniel Miller, Adam Kraya, Yiran Guo, Peter Madsen, Nicholas Van Kuren, Xiaoyan Huang, Miguel A. Brown, Jennifer L. Mason, Meen Chul Kim, Allison P. Heath, Brian M. Ennis, Bo Zhang, Jena V. Lilly, Jo Lynne Rokita, Christopher Friedman, Ximena P. Cuellar, Catherine A. Sullivan, Noel Coleman, Trang Duros, Thinh Q. Nguyen, Emmett C. Drake, Zeinab Helili, Beth A. Frenkel, Gerri R. Trooskin, Ariana Familiar, Karthik Viswanathan, Christopher M. Beck, Madison L. Hollawell, Valerie P. Baubet, Cassie Kline, Mariarita Santi, Tatiana S. Patton, Stephanie Stefankiewicz, Arya Kamnaa, Ryan A. Velasco, Dani Cardona, Phillip J. Storm, Adam C. Resnick, o/b/o Children's Brain Tumor Network. Expansion of the Pediatric Brain Tumor Atlas: Children's Brain Tumor Network, Kids First Data Resource and Childhood Cancer Data Initiative Open Science effort. [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 3566.

Informatics Methods and Infrastructure Needed to Study Factors Associated with High Incidence of Pediatric Brain and Central Nervous System Tumors in Kentucky

Pediatric brain and central nervous system tumors (PBCNSTs) are the most common solid tumors and are the leading cause of disease-related death in US children. PBCNST incidence rates in Kentucky are significantly higher than in the United States as a whole, and are even higher among Kentucky's Appalachian children. To understand and eventually eliminate such disparities, population-based research is needed to gain a thorough understanding of the epidemiology and etiology of the disease. This multi-institutional population-based retrospective cohort study is designed to identify factors associated with the high incidence of PBCNST in Kentucky, leveraging the infrastructure provided by the Kentucky Cancer Registry, its Virtual Tissue Repository (VTR), and the National Institutes of Health Gabriella Miller Kids First Data Resource Center (DRC). Spatiotemporal scan statistics have been used to explore geographic patterns of risk measured by standardized incidence ratios (SIRs) with 95% confidence intervals. The VTR is being used to collect biospecimens for the population-based cohort of PBCNST tissues that are being sequenced by Center for Data Driven Discovery in Biomedicine (D3b) at the Children's Hospital of Philadelphia (CHOP) with support from the Kids First DRC. After adjusting for demographic factors, we assess their potential relationship to environmental factors. We have identified regions in north-central and eastern Appalachian Kentucky where children experienced a significant increased risk of developing PBCNST from 1995-2017 (SIR, 1.48; 95% CI, 1.34-1.62). The VTR has been successful in the collection of a population-based cohort of 215 PBCNST specimens. Timely establishment of legal agreements for data sharing and tissue acquisition proved to be challenging which has been somewhat mitigated by the adoption of national agreement templates. Coronavirus disease 2019 (COVID-19) severely limited the generation of sequencing results due to laboratory shutdowns. However, tissue specimens processed before the shutdown indicated that punches were inferior to scrolls for generating enough quality material for DNA and RNA extraction. Informatics infrastructures that were developed have demonstrated the feasibility of our approach to generate and retrieve molecular results. Our study shows that population-based studies using historical tissue specimens are feasible and practical, but require significant investments in technical infrastructures.

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

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

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 (>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 (>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.