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

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 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 andamp resource commitments that significantly enhance the likelihood of successful commercialization PUBLIC HEALTH RELEVANCE The goal of this proposal is to provide an assay capable of obtaining more comprehensive information about individual patients in order to provide the most effective therapy Our approach will provide multiple orthogonal endpoints to improve the clinicianandapos s ability to match treatment to patient