Quantitative Phase Microscopy for Real-Time Clinical Determination of Drug Therapy Response in Primary and Metastatic Breast Cancer
Abstract
Cancer patients with advanced disease and no available treatment options will often have their tumors analyzed using genetic techniques. This is expensive and usually does not identify better therapies. For these patients, there is no quantitative way to predict how their cancer will respond to therapy fast enough to help doctors choose the best option. Our project uses a new approach based on weighing single cancer cells growing outside the body with light. By weighing cancer cells as they increase in size over time, we directly measure growth. We aim to use this method to observe a patient s cancer cells when treated with possible therapies. This will show us which therapies stop or slow cancer cell growth, suggesting they will likely be effective in the patient. We plan to use this technique to test different treatments within hours after removal from the patient. Our goal is to be able to give a personalized drug sensitivity/resistance report back to the doctor within 2 days. Since this method is unproven, we need to build an instrument and test its accuracy before it can be used for patient care. The time required by our method is essential. Our first goal is to ensure our method is fast enough to measure therapy response within hours. We also plan to use our approach to test many different therapies so we can provide options for the most appropriate treatment. Each of these therapies affects cancer cells in a different way, so we will need to test each therapy separately to tell us what an effective or ineffective treatment looks like using our method. We will then compare our method to standard, slower ways of measuring cancer cell growth to make sure it is accurate. Once we have shown how our method performs for each therapy with cells grown in culture, we will then see how well our approach does with cancer cells collected directly from patients with advanced or metastatic breast cancer who have been treated at the Huntsman Cancer Institute. From this extensive sample library, we will first determine which samples give us the widest possible range of different treatments and outcomes. This will give us the best way to tell if our method is effective. Then we will work out how to use these samples in the fastest, most efficient way possible to attain our overall goal of providing data to doctors within 2 days. Just as we did in the first part of the project, we will compare our data to a gold standard, slower method for measuring response to therapy. Finally, we will compare our results to the known clinical outcome of each patient whose samples we tested. This will tell us how good our method is at predicting when a patient is likely to respond or not to a given therapy. One of the Principal Investigators for this project is an engineer who helped develop the method we plan to use. The other Principal Investigator is a board certified clinical pathologist that serves as a Medical Director for a large pathology reference laboratory that offers cancer testing using methods that he developed and validated. As a team, we plan to move this promising technology into a method that can help patients within the next 6 years, including the 3 years covered by our proposed project. One overarching challenge we will address is to reduce patient suffering by reducing unnecessary side effects of ineffective treatments. We also hope to improve survival of breast cancer patients by telling doctors which therapy to use for each individual patient. The major risk of our approach is that the samples we will use are removed from a patient and grown in a dish. This is very unlike the actual environment inside the body. However, promising initial data shows that, for at least some therapies, our approach should be able to predict how a patient s cancer is likely to respond. We have chosen to start with patients who have advanced or metastatic breast cancer because we have the samples available at our in
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 05, 2019
- Source ID
- W81XWH1910066
Entities
People
- Philip Bernard
Organizations
- United States Army
- University of Utah