OpenPBTA: The Open Pediatric Brain Tumor Atlas

Shapiro, Joshua A.; Gaonkar, Krutika S.; Spielman, Scott R.; Savonen, Candace; Bethell, Chante; Jin, Run; Rathi, Komal S.; Zhu, Yuankun; Egolf, Laura E.; Farrow, Bailey; Miller, Dan; Yang, Yang; Koganti, Tejaswi; Noureen, Nighat; Koptyra, Mateusz; Duong, Nhat; Santi, Mariarita; Kim, Jung; Robins, Shannon; Storm, Phillip B.; Mack, Stephen C.; Lilly, Jena; Xie, Hongbo; Jain, Payal; Raman, Pichai; Rood, Brian R.; Lulla, Rishi; Nazarian, Javad; Kraya, Adam; Vaksman, Zalman; Heath, Allison P.; Kline, Cassie; Scolaro, Laura; Viaene, Angela N.; Huang, Xiaoyan; Way, Gregory P.; Foltz, Steven M.; Zhang, Bo; Poetsch, Anna R.; Mueller, Sabine; Ennis, Brian; Prados, Michael D.; Diskin, Sharon J.; Zheng, Siyuan; Guo, Yiran; Kannan, Shrivats; Waanders, Angela J.; Margol, Ashley; Kim, Meen Chul; Hanson, Derek; Kuren, Nicholas Van; Wong, Jessica; Kaufman, Rebecca; Coleman, Noel; Blackden, Christopher; Cole, Kristina A.; Mason, J. L.; Madsen, Peter J; Koschmann, Carl; Stewart, Douglas R.; Wafula, Eric; Brown, Miguel; Resnick, Adam; Greene, Casey S.; Rokita, Jo Lynne; Taroni, Jaclyn N.

doi:10.1016/j.xgen.2023.100340

Cited by 11 publications

(7 citation statements)

References 157 publications

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“…The single-cell RNA-seq data available on the Portal can also be used to deconvolute existing bulk RNA-seq datasets, allowing researchers to infer abundance of different cell types or cell states in bulk RNA-seq data. Data available on the ScPCA Portal can be used to re-analyze any existing pediatric cancer datasets with bulk RNA-seq, such as the Pediatric Brain Tumor Atlas [ 73,74 ]. This allows researchers to glean more insight from previously published data without obtaining fresh samples, saving time and money.…”

Section: Discussionmentioning

confidence: 99%

The Single-cell Pediatric Cancer Atlas: Data portal and open-source tools for single-cell transcriptomics of pediatric tumors

Hawkins,

Shapiro,

Spielman

et al. 2024

Preprint

Self Cite

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The Single-cell Pediatric Cancer Atlas (ScPCA) Portal (https://scpca.alexslemonade.org/) is a data resource for uniformly processed single-cell and single-nuclei RNA sequencing (RNA-seq) data and de-identified metadata from pediatric tumor samples. Originally comprised of data from 10 projects funded by Alex's Lemonade Stand Foundation, the Portal currently contains summarized gene expression data for over 500 samples from over 50 types of cancers from ALSF-funded and community-contributed datasets. In addition to gene expression data from single-cell and single-nuclei RNA-seq, the Portal holds data obtained from bulk RNA-seq, spatial transcriptomics, and feature barcoding methods, such as CITE-seq and cell hashing. ScPCA data are available for download as SingleCellExperiment or AnnData objects and are ready for downstream analyses. Objects include raw counts and normalized gene expression data, PCA and UMAP coordinates, and automated cell type annotations. Additionally, all downloads include two summary reports for each library: a quality control report summarizing sample statistics and displaying visualizations of cell metrics and a cell type annotation report with comparisons among cell type annotation methods and diagnostic plots to assess annotation quality. Merged SingleCellExperiment and AnnData objects containing all gene expression data and metadata for all samples in an ScPCA project are also available for download. These objects are useful when performing analysis on multiple samples simultaneously. Comprehensive documentation about data processing and the contents of files on the Portal, including a guide to getting started working with an ScPCA dataset, can be found at http://scpca.readthedocs.io. All data on the Portal were uniformly processed using scpca-nf, an open-source and efficient Nextflow workflow that uses alevin-fry to quantify all single-cell and single-nuclei RNA-seq data, any associated CITE-seq or cell hash data, spatial transcriptomics data, and bulk RNA-seq. Any pediatric cancer-relevant data sets processed with scpca-nf are eligible for inclusion on the ScPCA Portal, enabling continuous growth of the ScPCA Portal to help pediatric cancer researchers spend less time finding and processing data and more time answering their pressing research questions.

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Section: Discussionmentioning

confidence: 99%

The Single-cell Pediatric Cancer Atlas: Data portal and open-source tools for single-cell transcriptomics of pediatric tumors

Hawkins,

Shapiro,

Spielman

et al. 2024

Preprint

Self Cite

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“…(The dataset was downloaded from the PedcBioPortal, https://pedcbioportal. kidsfirstdrc.org/study/summary?id=openpbta,pbta_all (accessed on 16 May 2023) and compiled using the Open Pediatric Brain Tumor Atlas (OpenPBTA) and Pediatric Brain Tumor Atlas (PBTA, provisional) consortiums [40] (the keywordsfor the search were "brainstem glioma, diffuse intrinsic pontine glioma, diffuse midline glioma grade 4, diffuse midline glioma H2K27M WHO grade 4, diffuse midline glioma WHO grade 4 H3K27M mutant, DMG H3 K27M mutant WHO grade 4, diffuse midline high-grade glioma, diffuse hemispheric glioma H3 G34 mutant, WHO grade 4, and infiltrating DIPG")). The PedcBio-Portal enables the acquisition of CSV-formatted files for the compiled clinical metadata and expression values of the filtered patient subsets for further analyses [41][42][43][44].…”

Section: Methodsmentioning

confidence: 99%

“…Assays for mRNA expression values were obtained from 22 deceased patients: 1 at diagnosis, 20 from the initial CNS tumors, and 2 from progressive disease patients. The patient characteristics for these 45 pbDMG patients were compared using 171 pediatric high-grade gliomas and 404 low-grade gliomas obtained from the PBTA database (downloaded from the Ped-cBioPortal, https://pedcbioportal.kidsfirstdrc.org/study/summary?id=openpbta,pbta_all (accessed on 16 May 2023), and compiled using the Open Pediatric Brain Tumor Atlas (OpenPBTA) and Pediatric Brain Tumor Atlas (PBTA, provisional) consortiums [40] (the keywordsfor the high-grade glioma and low-grade glioma searches were "CAN-CER_TYPE_DETAILED: low-grade glioma, NOS, or high-grade glioma, NOS RNA expression" with "ONCOTREE_CODE: DIPG, hggnos, and lggnos).…”

Section: Methodsmentioning

confidence: 99%

Transforming Growth Factor Beta 2 (TGFB2) and Interferon Gamma Receptor 2 (IFNGR2) mRNA Levels in the Brainstem Tumor Microenvironment (TME) Significantly Impact Overall Survival in Pediatric DMG Patients

Qazi,

Talebi,

Trieu

2024

Biomedicines

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This hypothesis-generating study characterized the mRNA expression profiles and prognostic impacts of antigen-presenting cell (APC) markers (CD14, CD163, CD86, and ITGAX/CD11c) in pediatric brainstem diffuse midline glioma (pbDMG) tumors. We also assessed the mRNA levels of two therapeutic targets, transforming growth factor beta 2 (TGFB2) and interferon gamma receptor 2 (IFNGR2), for their biomarker potentials in these highly aggressive pbDMG tumors. The expressions of CD14, CD163, and ITGAX/CD11c mRNAs exhibited significant decreases of 1.64-fold (p = 0.037), 1.75-fold (p = 0.019), and 3.33-fold (p < 0.0001), respectively, in pbDMG tumors relative to those in normal brainstem/pons samples. The pbDMG samples with high levels of TGFB2 in combination with low levels of APC markers, reflecting the cold immune state of pbDMG tumors, exhibited significantly worse overall survival outcomes at low expression levels of CD14, CD163, and CD86. The expression levels of IFNGR2 and TGFB2 (1.51-fold increase (p = 0.002) and 1.58-fold increase (p = 5.5 × 10−4), respectively) were significantly upregulated in pbDMG tumors compared with normal brainstem/pons samples. We performed multivariate Cox proportional hazards modelling that showed TGFB2 was a prognostic indicator (HR for patients in the TGFB2high group of pbDMG patients = 2.88 (1.12–7.39); p = 0.028) for poor overall survival (OS) and was independent of IFNGR2 levels, the age of the patient, and the significant interaction effect observed between IFNGR2 and TGFB2 (p = 0.015). Worse survival outcomes in pbDMG patients when comparing high versus low TGFB2 levels in the context of low IFNGR2 levels suggest that the abrogation of the TGFB2 mRNA expression in the immunologically cold tumor microenvironment can be used to treat pbDMG patients. Furthermore, pbDMG patients with low levels of JAK1 or STAT1 mRNA expression in combination with high levels of TGFB2 also exhibited poor OS outcomes, suggesting that the inclusion of (interferon-gamma) IFN-γ to stimulate and activate JAK1 and STAT1 in anti-tumor APC cells present the brainstem TME can enhance the effect of the TGFB2 blockade.

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“…The raw normal and tumor whole-genome sequencing data and germline SNVs for 744 pediatric brain tumor patients were downloaded from CAVATICA ( https://cavatica.sbgenomics.com/ ). Sample characteristics, clinical data, somatic SNV, and somatic CNV data were retrieved from OpenPBTA 51 ( https://github.com/AlexsLemonade/OpenPBTA-analysis ). The consensus SV data, as called by four algorithms, along with clinical information including diagnosis and survival data of adult brain tumors, were obtained from the PCAWG consortium.…”

Section: Methodsmentioning

confidence: 99%