SBIR Phase I: CANCER DIAGNOSTIC TOOL USING CANCER GENOMIC SIGNATURES TO DETERMINE CANCER TYPE

Award ID: 2051900

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop a data analytic tool to predict and identify the organ of origin from early cancer screening blood tests. This will allow noninvasive detection of cancer at early stages, when it can be treated with potentially improved outcomes and in a less costly manner. Second, a complementary application of the proposed technology is to address an unmet need in identifying cancer organ of origin in metastatic cancers of unknown primary, where not knowing the organ of origin hampers designing an effective treatment plan in 30,000+ cases/yr in the U.S. This Small Business Innovation Research (SBIR) Phase I project will accomplish internal development, and external validation of the proposed data analytic technology so it is ready to be validated on circulating tumor DNA data from blood, and can be used for metastatic tumors of unknown primary origin. The proposed technology addresses the problem of the unknown primary by analyzing whole genome or large subsets using predictive tools. Different cancer (sub)types have different patterns or signatures of somatic single nucleotide variations in the cancer genome. A library of these signatures is built using a large number of whole genome data samples with a broad cross-section of known cancer (sub)types. The unknown cancer organ of origin of a new data sample is identified by comparing its somatic mutational patterns to the signatures in the library. A key research objective is to identify the minimum subset of whole genome required to determine the cancer organ of origin to facilitate its application in blood tests. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Alastair Monk