The Human Cancer Model Initiative (HCMI) is an international consortium that is generating novel human tumor-derived culture models with associated genomic and clinical data. The HCMI consortium includes the US-National Cancer Institute, part of the National Institutes of Health, Cancer Research UK, foundation Hubrecht Organoid Technology, and Wellcome Trust Sanger Institute (more on the Consortium). The goal of HCMI is to create up to one thousand cancer models that recapitulate patients’ tumors as faithfully as possible.

To address the issue of tumor complexity, the HCMI will use next-generation culture techniques to develop models that more closely mirror the architecture and cellular heterogeneity of human tumors. In the future, resulting cancer models may be utilized to accomplish goals including, but not limited to, defining essential cancer pathways, determining mechanisms of drug resistance, and assessing response to small molecules.  In addition, the models can be used to study the biology of the various cell types.  The HCMI-developed models and related data will be available to the world-wide research community. 

  • The National Cancer Institute (NCI) has funded Cancer Model Development Centers (CMDCs) to generate fully credentialed cancer models originating from patient tissues (more on CMDCs). 
  • Cancer Research UK and Wellcome Trust Sanger Institute are co-funding generation of cancer organoids for the United Kingdom’s arm of the HCMI.
  • The foundation Hubrecht Organoid Technology, a not-for-profit organization founded by the Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences, and University Medical Center Utrecht, is generating and sequencing cancer organoid models for the Netherlands’ arm of the HCMI.

The collaborative nature of HCMI will allow for rapid learning and protocol sharing. When possible, procedures and resulting molecular data will be standardized. As part of NCI’s Precision Medicine Initiative in Oncology, these novel models will serve as valuable tools for the cancer research field and could be used in the future to inform individualized patient treatments.

Last updated: January 11, 2017