Detecting Relapse-Causing Populations at the Time of Diagnosis in B-Cell Progenitor Acute Lymphoblastic Leukemia
Abstract
Dr. Kara Davis is an Assistant Professor of Pediatrics at Stanford University. Dr. Davis is a pediatric oncologist and specializes in the treatment of children with acute leukemia, with a focus on relapsed acute lymphoblastic leukemia. Dr. Davis is an expert in using novel single-cell technologies to study pediatric cancers. Dr. Davis aims to use these technologies to ultimately improve outcomes for children and young adults with cancer, specifically understanding why patients fail current therapies and learning how new therapies may improve patient outcomes. This award will enable Dr. Davis to realize this goal by providing support and mentorship to develop novel techniques in her laboratory to study cancer cells that are predictive of relapse in patients. Dr. Davis is focused on understanding how relapse occurs in B-cell acute lymphoblastic leukemia. This award will enable her to determine new therapies to target relapse-causing cells and to bring new relapse prediction tools to patient care. The majority of cancers will initially respond to therapy with decrease in tumor size and some improvement in patient symptoms. However, relapse, when cancer returns, remains the greatest barrier to providing a long-term cure and is a leading cause of death from cancer. This paradigm is true for childhood B-cell acute lymphoblastic leukemia, the most common cancer of childhood. B-cell acute lymphoblastic leukemia generally will go into remission for over 95% of patients with standard chemotherapy after one month. However, relapse is the leading cause of death for children with B-cell acute lymphoblastic leukemia. In order to improve outcomes for children with acute lymphoblastic leukemia, we need to do a better job of preventing relapsed disease. The overall goal of this proposal is to meet this challenge. Our previous work has identified a method that performs significantly better at predicting patients at risk for relapse. Currently, doctors use a complex combination of features to give families prognostic information regarding relapse risk. These features may only be known after weeks or months of therapy, and the prediction of relapse remains imperfect. In addition, these relapse tools do not provide suggestions on how to alter treatment in a targeted fashion to specifically kill leukemia cells that will cause relapse. The method we have developed for relapse prediction overcomes the shortcomings of the current tools. We can make a determination of relapse risk based on analysis of the leukemia cells at the time a child is diagnosed. Further, we can pinpoint the cells responsible for relapse and know features that may be targetable by drugs or other therapies. Thus, this provides a major advancement in the precision of relapse prediction and provides a way forward when choosing therapies to reduce relapse risk. Here, we propose to further study the leukemia cells we have identified that confer increased risk of relapse. We aim to understand how they can survive initial treatment and if novel targeted therapies may be used to kill them. We will use animal models to understand how potent these cells are at causing leukemia and if they have unique properties that make them better able to cause leukemia and survive standard treatments. Finally, we will use new technologies to determine if there are direct and quick ways to identify these cells so that a clinical test may be developed so every child with leukemia can be tested for the presence of these cells at the time of diagnosis. Together, we hope to be able to both rapidly detect these relapse predictive cells at the time a child is diagnosed with leukemia and discover new treatments that will specifically target and kill these relapse predictive cells. Ultimately, we hope that we will impact the incidence of relapse and decrease the number of children dying from relapsed B-cell progenitor acute lymphoblastic leukemia. What’s more, we believe that this approach can be ap
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 10, 2021
- Source ID
- W81XWH2010456
Entities
People
- Kara Davis
Organizations
- Stanford University
- United States Army