Getting More from Less: Multi-omic Capture and Analysis from Patient Samples

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 DESCRIPTION (provided by applicant): Personalized medicine is predicated on having sufficient patient specific information to provide a diagnosis specific to that patient. Genomics (e.g. next generation sequencing) is now being adopted into clinical practice and is enabling improvements in patient specific care particularly in cancer. However, sequence information alone will not be sufficient to realize the full potential of personalized medicine. If we examine prostate cancer, more than half of patients do not benefit from new anti-cancer therapies such as Abiraterone and Enzalutamide and nearly all patients who initially benefit develop resistance within 1-2 years. Yet, for the clinician the treatment decisions are largely guesswork as he/she has little quantitative mechanistic data to guide treatment choices. Importantly, prostate cancer is driven in large part by the Androgen Receptor (AR) including ligand binding and translocation from the cytoplasm to the nucleus activating a transcriptional program critical to tumorigenesis. Multiple drugs are currently available that prevent nuclear translocation of the AR via different mechanisms, but sequencing alone will be insufficient to accurately guide therapy choice and to monitor the development of resistance (similar scenarios exist in other cancers and other diseases). Predicting and monitoring targeted therapies requires orthogonal multi-omic (i.e., protein, genomic, gene expression) endpoints. Circulating tumor cells (CTCs) have great potential as an accessible sample and many technologies are being developed for CTC analysis, but none have the ability to perform multi-omic analysis from a single sample. This proposal addresses these issues by leveraging and advancing Exclusion-based Sample Preparation (ESP) to enable the rapid and efficient isolation of multiple analytes (cells, proteins RNA, DNA) from a single precious sample with high recovery and purity. To efficiently move this platform into the clinic, we have signed licensing agreements with Gilson and Foundation Medicine (recently acquired by Roche) industry leaders in instrumentation/manufacturing, and advanced cancer diagnostics/clinical laboratory test development respectively. Additionally our clinical collaborator, Dr. Lang (University of Wisconsin), will enable us to directly demonstrate the clinical efficacy of our multi-omic approach during the SBIR proposal period, using advanced prostate cancer as a clinical model. As illustrated by the AR model system, assays capable of measuring multi-omic biomarkers would enable clinicians to make more informed decisions about what type of therapy to use and when to use it for patients with progressive disease, informing both choice of initial treatment as well as when to switch therapy as resistance occurs. We have chosen to submit a Fast-Track SBIR Proposal and have addressed the Fast-Track requirements of clear Phase I goals and clear evidence (e.g. letters) of additional funding & resource commitments that significantly enhance the likelihood of successful commercialization.