The overall objective of this application is to design and develop a technology permitting highly- multiplexed fluorescence in situ hybridization using probes from a broad library of genes. We will focus on genes whose copy number variation represents possible actionable therapeutic targets. We will build, test and validate an optimal assay platform leveraging our long-standing experience implementing diagnostic tests for chromosomal abnormalities in cancer. This objective will be achieved in two aims:
Aim I. Develop a robust, reproducible assay for constructing a library of at least 50 locus-specific DNA sequence probes. We will use a combinatorial labeling approach in which each probe is bar-coded with a combination of two or three fluorophores per probe, allowing for up to 120 DNA probes to be simultaneously hybridized. We will develop an imaging system to decode the combinatorial label, record, quantify and analyze the obtained data.
Aim II. We will begin to test the clinical utility of the assay by screening for actionable gene copy number alterations in surgical biopsy specimens and in isolated circulating tumor cells (CTCs). The development of this technology will allow us to get closer to address the question of whether patient-specific dynamics of tumor heterogeneity underlie variation in response to treatment and whether the evaluation of CTCs copy number profile in the follow up of treatment can predict response to therapy. This project will serve as a model for development and clinical implementation of diagnostics for the benefit of patients, and will be used to disseminate knowledge and expertise to the clinical cancer diagnostic field in general.
There is a growing clinical need to broadly genotype tumors for possible actionable genetic changes. Copy number changes, including gene deletions or amplifications, are an important subset of such changes, and we estimate that there are approximately 50 cancer driver genes with well-documented copy number alterations. Microarray, PCR, and next generation sequencing platforms can assay genome-wide changes using extracted DNA, but have limited analytic sensitivity to detect single-cell variability due to normal tissue contamination that is inherent in clinical samples. FISH especially powerful for the detection of rare events that might otherwise be lost among a heterogeneous population of cells. We propose to develop highly-multiplexed automated FISH assays, combining the genomic breadth of DNA-extraction techniques with the power and sensitivity afforded by in situ assays.
