The long range goal of this project is to develop a high throughput method for companion diagnostics for cancer patients using next generation sequencing. It is a front end method compatible with all genome sequencing platforms, which preselects genes and labels samples in the first step to assure data integrity and to eliminate complexities of sequence analysis. The technology being tested in this Phase I grant can be developed into a tool for clinicians to help predict how a drug affects particular patient. The method will be used for comparative gene expression studies for many genes in many tiny tissue samples. The long term goal will be to quantify 1000 genes in 10,000 samples in one sequencing run. The samples could be micro samples isolated from a patient's tumor and tested directly, or could be cells grown from a tumor (when this is possible) and treated with many different potential drugs or drug combinations. One important application in the future will be transcriptional analysis of single, circulating tumor cells (CTCs) as a non-invasive diagnostic for patients at high risk for cancer or with recurrent cancer. This could be an approach to follow disease progression, for example, to define molecular changes that occur with treatment. Much work is being done to perfect methods to isolate live CTCs from a """"""""liquid"""""""" biopsy. We may be able to partner our technology to study the effects of putative drugs on individual CTCs. Recent data show that different parts of a tumor and similarly different CTCs vary widely in terms of gene expression. Analysis of many individual cells may be critical to characterize diversity and to understand how drugs affect subpopulations within a tumor, and then to predict which and test whether drugs will be effective for a particular patient. This project has the potential to hep improve clinical practice and contribute to the field of companion diagnostics. The short range goal of this Phase I SBIR grant is to validate the approach for preparing samples for next generation sequencing. It will be validated for 18 genes in two different cell lines. Previous time course experiments provide data that will be compared to data obtained using the new technology, and results will be compared with standard one-at-a-time methods of expression analysis. A successful completion of the Phase I grant will lead to a validated technology that can be used in Phase II to scale up the number of genes and samples that will be used on actual patient samples.
Personalized medicine is rapidly becoming the way to evaluate how to treat cancer and other diseases. The relevance of this SBIR grant to Public Health is the potential to be able to test a patient's tumor using high throughput next generation sequencing to measure a drugs effect on gene expression to determine which drug (or drugs) is best for treating that patient.