Document Type

Article

Publication Date

8-24-2021

Publication Title

Nat Commun

Keywords

Animals, Disease Models, Animal, Female, Gene Expression Regulation, Neoplastic, Genome, Genomics, Heterografts, Humans, Male, Mice, Models, Biological, Mutation, Neoplasms, Transcriptome, Xenograft Model Antitumor Assays

JAX Location

JGM, JMG

JAX Source

Nat Commun 2021 Aug 24; 12(1):5086

Volume

12

Issue

1

First Page

5086

Last Page

5086

ISSN

2041-1723

PMID

34429404

DOI

https://doi.org/10.1038/s41467-021-25177-3

Grant

CA034196

Abstract

Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs' recapitulation of human tumors.

Comments

The Jackson Laboratory (JAX) PDX resource data were supported by the National Cancer Institute under the JAX Cancer Center NCI Grant (Award Number P30CA034196). The genomic data for JAX PDX tumors used in this work were generated by JAX Genome Technologies and Single Cell Biology Scientific Service.

Carol Bult and Peter Robinson are members of the NCI PDXNet Consortium.

This article is licensed under a Creative Commons Attribution 4.0 International License.

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