UCSF / Northrop Grumman - Oncology Models Forum

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Investigator: Atul Butte, MD, PhD
Sponsor: NIH National Cancer Institute

Location(s): United States

Description

The mission for the Oncology Models Forum (OMF) is to align, harness and integrate data and knowledge of cancer mouse models to drive more rapid success in the discovery of diagnostics, therapeutics, and models of disease in cancer. Working with the community of researchers developing and using mouse models in cancer, we will build a new website for the OMF using the open-source HUBzero platform for researchers to share what they are learning about these cancer models.

The mission for the Oncology Models Forum (OMF) is to align, harness and integrate data and knowledge of cancer mouse models to drive more rapid success in the discovery of diagnostics, therapeutics, and models of disease in cancer. In early June 2014, the National Cancer Institute (NCI) released PAR-14-239 describing the OMF as a "comprehensive resource for information to guide generating, validating, and credentialing new models, informing their practical uses, advancing modeling technologies, [and] providing catalogs of available models resources, programs, and services." To maximize the use of available resources, this online site was prescribed to use HUBzero, an existing open-source scientific website framework, avoiding the expensive creation of a new scientific website from scratch. The OMF was designed as a community-building tool, with online discussion forums and an annual meeting. Specific content will be provided from the collaborative R01s funded in parallel to the OMF. Pre-clinical mouse and human-in-mouse models are critical to future translation in cancer. More than 4,300 manuscripts were published in 2013 describing or using cancer mouse models, including xenografts and transplantation models, spontaneous models, inbred mice, and genetically engineered mouse models (GEMM). The NCI Cancer Models Database (caMOD) now lists thousands of mouse models that are prone to develop tumors in one or more sites. But data on these models is scattered across numerous resources. Future success in research using cancer mouse models is now less dependent on the continued creation of new models, and more dependent on the validation of the thousands of currently available models, transparent access to knowledge and data on these models, comparisons of model data with human data, and organization of the research community. We plan to develop the Oncology Models Forum (OMF) to accomplish these goals. Our proposed OMF will integrate structured and unstructured data and knowledge on cancer mouse models, enabling new discoveries and the development of new translational tools.