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[Preprint]. 2025 Jun 28:2024.07.09.599086.
doi: 10.1101/2024.07.09.599086.

The Open Pediatric Cancer Project

Affiliations

The Open Pediatric Cancer Project

Zhuangzhuang Geng et al. bioRxiv. .

Update in

  • The Open Pediatric Cancer Project.
    Geng Z, Wafula E, Corbett RJ, Zhang Y, Jin R, Gaonkar KS, Shukla S, Rathi KS, Hill D, Lahiri A, Miller DP, Sickler A, Keith K, Blackden C, Chroni A, Brown MA, Kraya AA, Clark KL, Rood BR, Resnick AC, Van Kuren N, Maris JM, Farrel A, Koptyra MP, Trooskin GR, Coleman N, Zhu Y, Stefankiewicz S, Abdullaev Z, Chinwalla AT, Santi M, Naqvi AS, Mason JL, Koschmann CJ, Huang X, Diskin SJ, Aldape K, Farrow BK, Ma W, Zhang B, Ennis BM, Tasian S, Phul S, Lueder MR, Zhong C, Dybas JM, Wang P, Taylor D, Rokita JL. Geng Z, et al. Gigascience. 2025 Jan 6;14:giaf093. doi: 10.1093/gigascience/giaf093. Gigascience. 2025. PMID: 40891528 Free PMC article.

Abstract

Background: In 2019, the Open Pediatric Brain Tumor Atlas (OpenPBTA) was created as a global, collaborative open-science initiative to genomically characterize 1,074 pediatric brain tumors and 22 patient-derived cell lines. Here, we present an extension of the OpenPBTA called the Open Pediatric Cancer (OpenPedCan) Project, a harmonized open-source multi-omic dataset from 6,112 pediatric cancer patients with 7,096 tumor events across more than 100 histologies. Combined with RNA-Seq from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA), OpenPedCan contains nearly 48,000 total biospecimens (24,002 tumor and 23,893 normal specimens).

Findings: We utilized Gabriella Miller Kids First (GMKF) workflows to harmonize WGS, WXS, RNA-seq, and Targeted Sequencing datasets to include somatic SNVs, InDels, CNVs, SVs, RNA expression, fusions, and splice variants. We integrated summarized CPTAC whole cell proteomics and phospho-proteomics data, miRNA-Seq data, and have developed a methylation array harmonization workflow to include m-values, beta-vales, and copy number calls. OpenPedCan contains reproducible, dockerized workflows in GitHub, CAVATICA, and Amazon Web Services (AWS) to deliver harmonized and processed data from over 60 scalable modules which can be leveraged both locally and on AWS. The processed data are released in a versioned manner and accessible through CAVATICA or AWS S3 download (from GitHub), and queryable through PedcBioPortal and the NCI's pediatric Molecular Targets Platform. Notably, we have expanded PBTA molecular subtyping to include methylation information to align with the WHO 2021 Central Nervous System Tumor classifications, allowing us to create research-grade integrated diagnoses for these tumors.

Conclusions: OpenPedCan data and its reproducible analysis module framework are openly available and can be utilized and/or adapted by researchers to accelerate discovery, validation, and clinical translation.

Keywords: Docker; OpenPedCan; Pediatric cancer; multi-omics; open science; reproducibility.

PubMed Disclaimer

Conflict of interest statement

Declarations of Interest The authors declare no conflicts.

Figures

Figure 1:
Figure 1:. OpenPedCan Data.
A, OpenPedCan contains multi-omic data from seven cohorts of pediatric tumors (A-B) with counts by tumor event, RNA-Seq from adult tumors from The Cancer Genome Atlas (TCGA) Program (C-D) and RNA-Seq from normal adult tissues from the Genotype-Tissue Expression (GTeX) project (E) with counts by specimen. (Abbreviations: TARGET = Therapeutically Applicable Research to Generate Effective Treatments, PPTC = Pediatric Preclinical Testing Consortium, PBTA = Pediatric Brain Tumor Atlas, Maris = Neuroblastoma cell lines from the Maris Laboratory at CHOP, GMKF = Gabriella Miller Kids First, DGD = Division of Genomic Diagnostics at CHOP, CPTAC = Clinical Proteomic Tumor Analysis Consortium)
Figure 2:
Figure 2:. OpenPedCan Analysis Workflow.
Depicted are the datasets (yellow, orange, and grey) contained within OpenPedCan. These datasets are made available in a harmonized manner through primary analysis workflows (blue) for DNA, RNA, and/or proteogenomics data. Files derived from the primary analysis workflows (green) are released within OpenPedCan. Additional analysis modules developed within OpenPedCan (red) also generate results files (green) which are released within OpenPedCan.
Figure 3:
Figure 3:. Medulloblastoma Sample Clustering.
A, UMAP projection of 271 MB tumors and B, 63 SHH-activated MB tumors using methylation beta values of the 20,000 most variable probes from the Infinium MethylationEPIC array. C, UMAP projection of MB, SHH activated samples indicating copy number status of SHH subgroup known somatic driver genes CCND2, GLI2, MYCN, and PTEN.

References

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