Funded in honor of Nick Valvano by a challenge grant with
The University of North Carolina at Chapel Hill.
Personalized medicine for cancer patients is a current goal of biomedical research. A few gene expression-based assays have already proven to have clinical utility (i.e. value), especially for breast cancer patients (see 2016 ASCO biomarker guidelines). Therefore the continued discovery and clinical development of additional gene expression assays could be an important aspect for furthering personalized treatments. Here we propose to develop a new generation of gene expression-based assays for possible use in cancer care. The goal of this proposal is to further develop and test a genome-wide RNA-sequencing assay and it’s companion bioinformatics tool, for the automated classification of a tumor according to 300 different expression signatures. These signatures span a broad range of biological phenotypes including the microenvironment (immune cells, fibroblasts), tumor features (growth factor signaling pathways), and of cancer stem cells. Some of these 300 signature may eventually be of clinical value, and so in this proposal we will create a new technological platform with linked bioinformatics, to provide these signatures as new potential biomarkers for future clinical testing.