Researchers are using a diagnostic technology to pursue linkages between shifts in gene expression patterns mediated by epigenetic DNA modifications and the early onset of a disease etiology. The eventual result is that molecular, biochemical and physiological activities will diverge from a normative state and overtly express the disease symptom progression. If shifts in gene expression could be detected early, a diagnosis could be made before symptoms were significant. Better yet, detecting pre-symptomatic changes in regulatory controls over gene expression events (like epigenetic DNA methylation) would make it possible to diagnosis the pre-onset of an impending disease or disease risk. Early intervention prior to the onset of any disease could potentially reduce the progression of the disease and perhaps reduce the severity of the symptoms. The team proposes to apply an epigenetic profiling technology to the characterization of human lung cancer tumors. Once a tumor is large enough to spot on an x-ray it usually has already metastasized to nearby lymph nodes. Consequently, there is a large unmet need for tests that can diagnose certain types of cancer at an early stage, when the cancer is more likely to respond to treatment. The team is pursuing technical proof of concept work for the epigenetic profiling platform.
The team's quantitative algorithms are combined with statistical pattern recognition technology that can enable rapid and cost-effective screening of billions of base pairs of sequence data in a biopsy or tissue sample, producing a sophisticated and statistically rigorous report to an attending physician, clinic or submitting laboratory. This information can be critical for the development of effective personalized medicine strategies for a broad range of disease detection and treatment needs. With genome sequencing rapidly becoming cost-effective, there is an increasing requirement for profiling DNA methylation sites within a patient's genome to provide an individual fingerprint profile of abnormal gene activities. This project may solve this need for rapid, high-throughput, low-cost, computational modeling and statistical pattern recognition to identify how a patient's DNA methylation profile varies from a normative population state.
This project explored the commercial viability of a genetic diagnostic software platform originally developed in the PI's laboratory at the University of Delaware. Support was provided for an advanced graduate student to learn and execute basic entrepreneurial concepts and practices to transition academic discoveries into a biotech startup company. Together, we conducted marketing surveys to build a better understanding of the genetic diagnostic market relative to the new field of epigenetics. We conducted a trial diagnostic study through a collaboration with a clinical cancer hospital focusing on epigenetic markers associated with agressive breast tumors in "triple-negative" patients (i.e., women who were negative for the three major breast cancer marker tests: two for Brca gene mutations and one for an estrogen receptor mutation). Overall, we were able to establish the validity of our analytical epigenetic profiling software in a clinical application and were able to derive a successful starting business model (after many pivots) to get our company, Genome Profiling LLC, off the ground. The company currently has Angel investor backing that has allowed us to pursue further clinical demonstration projects with three large regional cancer hospitals with specialties in translational medicine. The breast cancer pilot project has been expanded to an R21 NIH proposal in which the company is a key collaborator for providing epigenetic profiling services for a study of 32 patients. Overall, the support and professional guidance provided by the I-Corps Program has greatly facilitated the startup activities of the entrepreneurial lead graduate student, the PI and the business mentors involved with guiding us forward.
