Reference #: 1744
The University of South Carolina is offering licensing opportunities for StarTrace: A Multiplex Drug Testing Platform for Personalized Medicine
Background:
The development of cancer treatments tailored to the needs of individual patients is a promising paradigm for oncology. Increased utilization of tumor sequencing illustrates the growing interest in using therapies that specifically target genetic variations in tumors. However, while genetic sequencing has advanced the identification of targetable mutations, only a small percentage of tumors have mutations known to be actionable, and even those that do may not always respond predictably to treatment. Many tumors, despite lacking clear genetic indicators, may still be highly sensitive to drugs that are not typically considered for those patients. The disconnect between somatic mutations and therapeutic response highlights the need for more versatile approaches to cancer treatment.
There is an unmet need for more relevant preclinical models that can be used at early stages of drug discovery such as high-throughput screening (HTS). Patients-derived organoid avatars (PDOs) are sophisticated and highly relevant in vitro models. Organoids are self-organizing mammalian adult stem cells and are strong tools for ex vivo tissue morphogenesis and organogenesis simulations Because cancer and normal organoids contain the array of germline and somatic mutations that influence drug response, this technology has the potential to bridge the gap between our basic science understanding of cancer genetics and pragmatic testing of new treatments for patients.
Invention Description:
Here we show a new methodology, called StarTrace. StarTrace is a drug sensitivity assay platform applied to mixtures of patient-derived organoid avatars as a practical solution for choosing therapy. The result is high-throughput in vitro drug screening of a pool of genetically barcoded colorectal cancer organoid avatars. Drug effect is measured over long periods of time in terms of Darwinian fitness using both next-generation sequencing (NGS) and qPCR to quantify each barcode in the mixture.
Potential Applications:
Biomedical fields involving cancer research and the prediction of tumor drug responses.
Advantages and Benefits:
The platform is shown to be accurate and high throughput at relatively low cost. In addition to being useful for testing individual patients and predicting clinical response, pharmaceutical industry can use this platform during drug discovery efforts to significantly reduce time and costs associated with drug development, biomarker discovery, and market decision-making. A key advantage is the platform tracks tumor drug responses over long-term exposure times (1 month or longer) that mimics clinical reality better than typical short-term (5-day) assays. The method is relatively cost-effective and scalable and can handle anywhere from 2 to 100 PDOs simultaneously