Rare Cancer Genetics Registry

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DESCRIPTION (provided by applicant): Taken as an aggregate, rare cancers (those affecting fewer than 200,000 people in the US according to the Orphan Disease Act definition) account for 27% of the US cancer diagnoses and 25% of cancer mortality. However, while new therapies have changed the way some common cancers are treated, there has been little advance in the treatment of most rare cancers and research directed at these diseases is sparse. The main goal of this proposal is to expand the infrastructure and launch a research program for the Rare Cancer Genetics Registry (RCGR), a project that was funded by an NIH Challenge grant in 2009 to "promote research into the causes and treatment of these diseases". Currently, the RCGR is a registry with over 500 participants and consists of a coordinating center at Massachusetts General Hospital, five academic clinical recruiting sites, and an academic medical informatics site. This proposal plans to expand the registry by 600 participants with very rare (incidence below 5,000/year in the US) and understudied cancers. Registrants will be recruited at 5 academic clinical sites and from registries of existing foundations during the 5 years of the grant. Diagnoses of chordoma, uveal melanoma, Merkel cell carcinoma, vulvar cancer, and adenoid cystic carcinoma will be the focus of recruitment, chosen due to preliminary results and feasibility of recruitment during the 5-year project period. Tumor tissue and DNA will be obtained, along with chart-abstracted data on diagnosis, treatment, response and recurrence. Registrants will be consented for re-contact to participate in future studies. A new research program will be launched, aimed at 1) characterizing the genetic profile of rare tumors that could inform the choice of therapeutic interventions, and 2) understanding the clinical, pathological, and therapeutic predictors of outcomes of response and recurrence and late effects in rare cancer patients. The tumor genotyping will be carried out using a state-of-the-art robotic technology that detects a set of mutations that arise in many common cancers, and for which potential targeted therapies are available or in development. The outcomes analysis will require sophisticated statistical methods that can deal with the small numbers of patients within each individual diagnosis by appropriately analyzing the aggregate of patients in the registry. This proposed project could provide resources that will be available to the wider research community and will serve cancer research for many years to come.