Main Content

A Compendium of Next-Generation Patient-Derived Models for Diverse Cancers

Citation TBD

Development of new therapeutics and validation of pathogenetic mechanisms in cancer require representative laboratory models. However, existing model collections do not yet represent the full spectrum of diversity observed in human cancer. Recent technologies enable more efficient model derivation (e.g., tumor organoids), yet whether such models maintain the molecular states of the originating tumor during long- term ex vivo expansion has not been systematically investigated. Here, we present the results of a large-scale international program—the Human Cancer Models Initiative (HCMI)—generating a resource of 665 patient-derived models from 2,780 donors with 25 cancer types, with integrated tumor/model whole genome, exome, methylome and transcriptome analyses. The resource encompasses 522 models with comprehensive clinical data, 153 models of rare cancers, and 71 models from participants with non-European ancestry. Analysis of 421 matched tumor/model pairs revealed a high degree of genetic (97.8%) and epigenetic (95%) concordance and defines specific correlates of discordance and model fidelity. However, single-nucleus RNA sequencing shows that, for some models, detectable cell states are influenced by culture conditions. We identify models with extrachromosomal DNA-based gene amplification and post-treatment mutational signatures, providing opportunities to study mechanisms of therapeutic resistance. This model repository is being made available to the cancer research community–including multimodal molecular profiling, clinical attributes, such as response to treatments before and after model generation, and integrative software tools–thus providing a valuable resource for preclinical investigation of cancer pathogenesis and treatment response.

Supplemental Data

Additional Resources

Instructions for Data Download

Open Access Data

  1. Download the appropriate manifest file from the publication page
  2. Use the manifest file to download data using the GDC Data Transfer Tool (DTT) or the GDC API

Controlled Access Data

  1. Download the appropriate manifest file from the publication page
  2. Download a token from the GDC Data Portal
  3. Use the manifest file and token to download data using the GDC DTT or the GDC API

For assistance, please contact the GDC Help Desk: support@nci-gdc.datacommons.io.