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. (2025) The Open Pediatric Cancer Project. GigaScience 14: giaf093. [article]
Modern cancer breakthroughs depend on collaboration and open data. The Open Pediatric Cancer (OpenPedCan) Project, published last month in GigaScience, is opening new doors for discovery by harmonizing genomic and molecular data from more than 6,000 tumors across 100 types of cancer.
Led by teams at Children’s National Hospital and Children’s Hospital of Philadelphia, OpenPedCan creates one of the largest harmonized open-source pediatric cancer datasets ever assembled.
Why this is important
Pediatric cancers are rare and complex, which makes collaboration essential. No single institution can collect enough samples to reveal the full picture of how these diseases develop or respond to treatment.
OpenPedCan changes that. The project combines whole-genome or exome sequencing, RNA sequencing, methylation profiling, proteomics and clinical data from multiple international cohorts into a unified, open platform. Researchers can now explore harmonized data covering nearly 48,000 total biospecimens, including tumor and normal tissues, to identify patterns, compare findings and accelerate the search for new treatments.
What’s new
OpenPedCan builds on the success of The Open Pediatric Brain Tumor Atlas (OpenPBTA), which characterized more than 1,000 pediatric brain tumors. This new release expands beyond brain cancers to include a broad range of childhood solid tumors and leukemias.
It also introduces molecular subtyping that aligns with the World Health Organization’s (WHO) 2021 classification of central nervous system tumors, along with new layers of data such as proteomics, phospho-proteomics and microRNA sequencing. Together, these additions give scientists a deeper, multiomic view of pediatric cancers than ever before.
The big picture
Making these datasets and tools openly available to anyone reduces barriers to entry and encourages collaboration across institutions and disciplines. The data has already been used to update initial diagnoses, identify potential therapeutic targets and strengthen clinical trial design.
OpenPedCan helps redefine what collaboration looks like in pediatric cancer research. By connecting genomic data, analytical tools and global expertise, the project gives scientists a faster path to discovery — and gives children with cancer more reasons for hope.
Availability – Project homepage: https://github.com/d3b-center/OpenPedCan-analysis
Source – Children’s National Hospital
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. (2025) The Open Pediatric Cancer Project. GigaScience 14: giaf093. [article]
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Modern cancer breakthroughs depend on collaboration and open data. The Open Pediatric Cancer (OpenPedCan) Project, published last month in GigaScience, is opening new doors for discovery by harmonizing genomic and molecular data from more than 6,000 tumors across 100 types of cancer.
Led by teams at Children’s National Hospital and Children’s Hospital of Philadelphia, OpenPedCan creates one of the largest harmonized open-source pediatric cancer datasets ever assembled.
Why this is important
Pediatric cancers are rare and complex, which makes collaboration essential. No single institution can collect enough samples to reveal the full picture of how these diseases develop or respond to treatment.
OpenPedCan changes that. The project combines whole-genome or exome sequencing, RNA sequencing, methylation profiling, proteomics and clinical data from multiple international cohorts into a unified, open platform. Researchers can now explore harmonized data covering nearly 48,000 total biospecimens, including tumor and normal tissues, to identify patterns, compare findings and accelerate the search for new treatments.
What’s new
OpenPedCan builds on the success of The Open Pediatric Brain Tumor Atlas (OpenPBTA), which characterized more than 1,000 pediatric brain tumors. This new release expands beyond brain cancers to include a broad range of childhood solid tumors and leukemias.
It also introduces molecular subtyping that aligns with the World Health Organization’s (WHO) 2021 classification of central nervous system tumors, along with new layers of data such as proteomics, phospho-proteomics and microRNA sequencing. Together, these additions give scientists a deeper, multiomic view of pediatric cancers than ever before.
The big picture
Making these datasets and tools openly available to anyone reduces barriers to entry and encourages collaboration across institutions and disciplines. The data has already been used to update initial diagnoses, identify potential therapeutic targets and strengthen clinical trial design.
OpenPedCan helps redefine what collaboration looks like in pediatric cancer research. By connecting genomic data, analytical tools and global expertise, the project gives scientists a faster path to discovery — and gives children with cancer more reasons for hope.
Availability – Project homepage: https://github.com/d3b-center/OpenPedCan-analysis
Source – Children’s National Hospital
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. (2025) The Open Pediatric Cancer Project. GigaScience 14: giaf093. [article]
Related Posts
RNAmel simplifies RNA sequencing data analysis with a reproducible, integrated platform
Heart failure reshapes bone marrow to create inflammation-related immune memory
Overlooked DNA regions surrounding ‘microexons’ hold missing pieces of autism’s genetic puzzle
RiboBA improves detection of hidden protein-coding regions using ribosome profiling
An anti-senescence gene may fight spinal disc deterioration
Scientists identify the neuroblastoma cells that signal poor outcomes
Novel biosensor uses DNA ‘barcodes’ to uncover disease signals in cells
CellART extracts single-cell information from high-resolution spatial transcriptomics
Cell2space restores spatial context to single-cell RNA sequencing data
Urine test may improve bladder cancer diagnosis and guide treatment decisions
DeCoRE – a computational method to resolve RNA structural heterogeneity from RNA structure probing data by direct RNA sequencing
Tracing 700 million years of cell evolution
How should biological replicates be handled in long-read RNA sequencing?
RNA-Seq reveals a new way the developing heart controls its growth
The Human RNome Project Consortium seeks to publish first-ever complete sequence of the body’s RNA
scFlowReport brings multiple single-cell RNA sequencing analyses into one workflow
Long-read RNA sequencing reveals how neurons choose alternative RNA endings
DeOPUS improves cell-type estimates from bulk RNA sequencing
ResolVI improves accuracy in spatial transcriptomics analysis
RNA sequencing reveals transcriptional allele differences in prostate cancer stem cells
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