Abstract A047: CancerModels.Org: A comprehensive resource for advancing precision medicine in cancer research

Abstract Access to well-characterized patient-derived cancer models (PDCMs) is crucial for advancing our understanding of cancer biology and developing targeted therapies. CancerModels.Org addresses this need by providing a unified, open global research platform for PDCMs. Its key objectives are to aggregate and standardize clinical, genomic, and functional data from various patient-derived xenografts (PDXs), organoids, and cell lines across multiple cancer types and to facilitate easier discovery and comparison of cancer models by implementing standardized data formats and adhering to FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. CancerModels.Org, launched in 2023, offers a collection of over 9300 PDCMs across 13 cancer types and includes rare pediatric PDX models and models from minority ethnic backgrounds. A total of over 365 billion data points from 55 model providers in 12 countries are made available across a variety of data types, including gene expression, gene mutation, copy number alteration, biomarkers, immune-related features of tumors, patient treatment, model treatment and imaging data (Release 6.6 - Oct 2024), making CancerModels.Org the largest free-to-consumer and open-access resource of this kind. The platform's user-friendly web interface allows for efficient searching and filtering of models based on various criteria, including cancer type, genomic alterations, patient clinical information, and treatment response. The data is also accessible via cBioPortal instance and REST API, enabling offline analyses. For an improved prioritization of PDCMs we performed knowledge enrichment by linking to external resources, such as publication platforms, cancer-specific annotation tools (COSMIC, CIViC, OncoMX, OpenCRAVAT, ClinGen), and raw data archives (ENA, EGA, GEO, dbGAP - for sequence, and BioImage archive for image data).The project is driving the development of and promoting the use of descriptive standards to facilitate data interoperability and promote global sharing of models, e.g. PDX Minimal Information standard (PDX-MI) and in vitro PDCM Minimal Information standard (manuscript in preparation). We provide expertise and software components to support several worldwide consortia, including PDXNet and EurOPDX. The project is supported by NCI and is freely available on Github under an Apache 2.0 licence.In conclusion, CancerModels.Org serves as a valuable resource for researchers maximizing utility and reusability of models and data, facilitating collaboration and data sharing among researchers and fostering a more integrated approach to precision oncology. By providing a standardized format for model data and encouraging contributions from the scientific community, the platform promotes reproducibility and accelerates the translation of laboratory findings into clinical applications, contributing to the development of more effective, personalized cancer treatments. Citation Format: Zinaida Perova, Mauricio Martinez, Tushar Mandloi, Marcelo Rios Almanza, Steven Neuhauser, Debbie Krupke, Dale Begley, Carol Bult, Helen Parkinson. CancerModels.Org: A comprehensive resource for advancing precision medicine in cancer research [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Functional and Genomic Precision Medicine in Cancer: Different Perspectives, Common Goals; 2025 Mar 11-13; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(5 Suppl):Abstract nr A047.

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Journal
Cancer Research
Published
2025-03-11
DOI
https://doi.org/10.1158/1538-7445.genfunc25-a047
Primary Topic
Cancer Genomics and Diagnostics
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article
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article

Abstract A047: CancerModels.Org: A comprehensive resource for advancing precision medicine in cancer research

Dale A. Begley, Zinaida Perova, Helen E. Parkinson, Debbie M. Krupke et al.
Cancer Research
Cancer Genomics and Diagnostics
article

Abstract A047: CancerModels.Org: A comprehensive resource for advancing precision medicine in cancer research

Dale A. Begley, Zinaida Perova, Helen E. Parkinson, Debbie M. Krupke, Carol J. Bult, Tushar Mandloi, Steven B. Neuhauser, Mauricio Martinez, Marcelo Rios Almanza
article en

Abstract

Abstract Access to well-characterized patient-derived cancer models (PDCMs) is crucial for advancing our understanding of cancer biology and developing targeted therapies. CancerModels.Org addresses this need by providing a unified, open global research platform for PDCMs. Its key objectives are to aggregate and standardize clinical, genomic, and functional data from various patient-derived xenografts (PDXs), organoids, and cell lines across multiple cancer types and to facilitate easier discovery and comparison of cancer models by implementing standardized data formats and adhering to FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. CancerModels.Org, launched in 2023, offers a collection of over 9300 PDCMs across 13 cancer types and includes rare pediatric PDX models and models from minority ethnic backgrounds. A total of over 365 billion data points from 55 model providers in 12 countries are made available across a variety of data types, including gene expression, gene mutation, copy number alteration, biomarkers, immune-related features of tumors, patient treatment, model treatment and imaging data (Release 6.6 - Oct 2024), making CancerModels.Org the largest free-to-consumer and open-access resource of this kind. The platform's user-friendly web interface allows for efficient searching and filtering of models based on various criteria, including cancer type, genomic alterations, patient clinical information, and treatment response. The data is also accessible via cBioPortal instance and REST API, enabling offline analyses. For an improved prioritization of PDCMs we performed knowledge enrichment by linking to external resources, such as publication platforms, cancer-specific annotation tools (COSMIC, CIViC, OncoMX, OpenCRAVAT, ClinGen), and raw data archives (ENA, EGA, GEO, dbGAP - for sequence, and BioImage archive for image data).The project is driving the development of and promoting the use of descriptive standards to facilitate data interoperability and promote global sharing of models, e.g. PDX Minimal Information standard (PDX-MI) and in vitro PDCM Minimal Information standard (manuscript in preparation). We provide expertise and software components to support several worldwide consortia, including PDXNet and EurOPDX. The project is supported by NCI and is freely available on Github under an Apache 2.0 licence.In conclusion, CancerModels.Org serves as a valuable resource for researchers maximizing utility and reusability of models and data, facilitating collaboration and data sharing among researchers and fostering a more integrated approach to precision oncology. By providing a standardized format for model data and encouraging contributions from the scientific community, the platform promotes reproducibility and accelerates the translation of laboratory findings into clinical applications, contributing to the development of more effective, personalized cancer treatments. Citation Format: Zinaida Perova, Mauricio Martinez, Tushar Mandloi, Marcelo Rios Almanza, Steven Neuhauser, Debbie Krupke, Dale Begley, Carol Bult, Helen Parkinson. CancerModels.Org: A comprehensive resource for advancing precision medicine in cancer research [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Functional and Genomic Precision Medicine in Cancer: Different Perspectives, Common Goals; 2025 Mar 11-13; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(5 Suppl):Abstract nr A047.

Cancer ResearchVol. 85(5_Supplement)
European Bioinformatics Institute (GB), Jackson Laboratory (US)
Openalex Percentile: Top 95%
Cancer Genomics and Diagnostics
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