PDXNet Portal: Patient-Derived Xenograft model, data, workflow, and tool discovery
Michael W Lloyd,
Sai Lakshmi Subramanian,
Xing Yi Woo,
Brian J Sanderson,
Yvonne A. Evrard,
Tiffany A. Wallace,
Jeffrey A Moscow,
James H. Doroshow,
Moon S. Chen,
Alana L Welm,
Bryan E. Welm,
Michael T Lewis,
Peter N Robinson,
Carol J Bult,
Dennis A. Dean,
Jeffrey H. Chuang
Posted 16 Oct 2021
bioRxiv DOI: 10.1101/2021.10.15.464537
Posted 16 Oct 2021
We created the PDX Network (PDXNet) Portal (https://portal.pdxnetwork.org/) to centralize access to the National Cancer Institute-funded PDXNet consortium resources (i.e., PDX models, sequencing data, treatment response data, and bioinformatics workflows), to facilitate collaboration among researchers, and to make resources easily available for research. The portal includes sections for resources, analysis results, metrics for PDXNet activities, data processing protocols, and training materials for processing PDX data. The initial portal release highlights PDXNet model and data resources, including 334 new models across 33 cancer types. Tissue samples of these models were deposited in the NCIs Patient-Derived Model Repository (PDMR) for public access. These models have 2,822 associated sequencing files from 873 samples across 307 patients, which are hosted on the Cancer Genomics Cloud powered by Seven Bridges and the NCI Cancer Data Service for long-term storage and access with dbGaP permissions. The portal also includes results from standardized analysis workflows on PDXNet sequencing files and PDMR data (2,594 samples from 463 patients across 78 disease types). These 15 analysis workflows for whole-exome and RNA-Seq data are freely available, robust, validated, and standardized. The model and data lists will grow substantially over the next two years and will be continuously updated as new data are available. PDXNet models support multi-agent treatment studies, determination of sensitivity and resistance mechanisms, and preclinical trials. The PDXNet portal is a centralized location for these data and resources, which we expect to be of significant utility for the cancer research community.
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