Abstract 3820: CancerModels.Org: A comprehensive resource for advancing precision medicine in cancer research
Authors: Zinaida Perova, Tushar Mandloi, Mauricio Martinez, Marcelo Rios Almanza, Steven Neuhauser, Debra Krupke, Dale Begley, Carol Bult, Helen Parkinson
Journal: Cancer Research (2025)

CancerModels.Org (www.cancermodels.org) is a research platform that standardises, harmonizes and integrates the complex and diverse data associated with Patient-Derived Cancer Models (PDCMs) for the cancer community. As of November 2024, the portal publishes over 9300 models - covering patient-derived xenografts (PDX), organoids and cell lines - across 13 cancer types, including rare pediatric PDX models and models from minority ethnic backgrounds. A total of over 356 billion data points are made available across a variety of data types, such as clinical metadata, molecular data and treatment-based information, which makes CancerModels.Org the largest free-to-consumer and open-access resource of this kind. Over the last twelve months, we enhanced the platform with new functionality to cater to new use cases. Users can explore molecular data summaries for models of specific cancer types, find models using the intuitive search and faceted filtering options of the web interface, visualize data via a dedicated cBioPortal instance and contact providers/suppliers for additional details. The data is also accessible via REST API, hence enabling offline analyses. The underpinning data model was augmented with additional dimensions and covers gene expression, gene mutation, copy number alteration, biomarkers, patient and model treatment, imaging and immune markers. 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) and image archives (BioImage archive). Finally, to streamline the model and data submission, we updated the Metadata dictionary and Metadata validation service to calculate the Model characterization score and provide suggestions on its improvement. Future work will focus on the curation of rare models with rich accessible metadata and data, including precancerous models, new data visualizations, integration of new data types and resources, as well as devising a model quality rating using user feedback. These developments will maximize utility and improve reusability of models and data, and reduce barriers to model and data sharing. CancerModels.Org is deeply integrated into the general PDCM landscape, underpinning or contributing to the data and/or software infrastructure of some of the long-running consortia, such as EUROPDX and PDXNet. The resource is freely available under an Apache 2.0 license (https://github.com/PDCMFinder). Citation Format: Zinaida Perova, Tushar Mandloi, Mauricio Martinez, Marcelo Rios Almanza, Steven Neuhauser, Debra Krupke, Dale Begley, Carol Bult, Helen Parkinson. CancerModels.Org: A comprehensive resource for advancing precision medicine in cancer research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3820.