Abstract 6910: CancerModels.org: An open global cancer research platform for patient-derived cancer models
Authors: Zinaida Perova, Mauricio Martinez, Tushar Mandloi, Marcelo Rios Almanza, Steven Neuhauser, Dale Degley, Debra Krupke, Carol Bult, Helen Parkinson
Journal: Cancer Research (2024)

Abstract 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. The portal publishes over 7500 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 90 million 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 course of the last twelve months, the platform has been enhanced with new functionality and an updated user interface to cater for a more varied set of use cases. Users can now search for models of interest by exploring molecular data summaries for models of specific cancer types, as well as by using the intuitive search and faceted filtering options of the web interface. 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 treatment and drug dosing studies. 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). More recently, we added immune-related features of tumors (HLA, MSI, TMB) and image data (also accessible via EMBL-EBI’s BioImage archive). Finally, to streamline model and data submission, we made available a Metadata dictionary and a Metadata validation service. Future work will focus on the curation of rare models with rich accessible metadata and data, 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 patient-derived cancer models 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, Mauricio Martinez, Tushar Mandloi, Marcelo Rios Almanza, Steven Neuhauser, Dale Degley, Debra Krupke, Carol Bult, Helen Parkinson. CancerModels.org: An open global cancer research platform for patient-derived cancer models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6910.