Abstract 1064: PDX Like Me: A molecular profile-based search tool

Abstract

Abstract Patient Derived Xenografts (PDXs) are generated through the engraftment of human tumor tissue into a specialized (usually, immunodeficient) mouse host strain. PDXs are a useful pre-clinical platform for evaluating the efficacy of single agent and combination therapies that are targeted to specific genomic characteristics of a patient’s tumor. We have implemented the PDX Like Me search tool to assist researchers in identifying PDX models whose tumors match - or are similar to - molecular profiles comprised of one or more genes and one or more genomic characteristics (e.g., copy number status, mutation, and expression). The PDX Like Me interface uses a search syntax similar to the Onco Query Language used by the popular cBioPortal resource. PDX Like Me is one of several search interfaces supported by the Mouse Models of Human Cancer database (formerly, the Mouse Tumor Biology database). MMHCdb (http://tumor.informatics.jax.org) is a comprehensive resource of information on both genetically engineered mouse models (GEMMs) and PDX models of human cancer that has been expertly curated from peer-reviewed scientific publications and direct data submissions from individual investigators and large-scale programs. MMHCdb provides an easy-to-use search interface as well as tools for visualizing associated data from these models. Information in the database is standardized using controlled vocabularies and official gene and mouse strain nomenclature. MMHCdb contains data from spontaneous or endogenously induced tumors from genetically defined mice. MMHCdb holds data on over 7,500 different strains including over 93,000 tumor frequencies and over 2,250 pathology reports with over 6,300 images from over 4,600 references. MMHCdb provides access to clinical, pathology, dosing study results, and genomics data from over 450 PDX models distributed by The Jackson Laboratory. MMHCdb in collaboration with EMBL-EBI has also co-developed the PDX Finder resource to provide a comprehensive global catalog of PDX models available for researchers. MTB is supported by NCI grant CA089713. Citation Format: Dale A. Begley, Debra M. Krupke, Steven B. Neuhauser, Joel E. Richardson, John P. Sundberg, Carol J. Bult. PDX Like Me: A molecular profile-based search tool [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1064.