Prostate Cancer Biomarker Discovery and Drug Repurposing Using Cross-Cancer Learning
Abstract
Background and Rationale: The majority of prostate cancer tumors grow slowly and never become life-threatening. Scientific studies have yet to conclude whether screening for prostate cancer lowers the risk of death from prostate cancer. There are several reasons for this. One major reason is that screening tests do not tell the physicians whether or not the detected cancer is truly dangerous (needs treatment) or harmless. Ideally, dangerous cancers should be aggressively treated and others spared the harmful effects of such treatment. Hence, physicians need new indicators in the form of biological markers (“biomarkers”) associated with lethal and harmless prostate cancers for better treatment planning. Given that tumors are caused by the molecular anomalies in the cell biology, biomarkers based on the molecular properties of tumors offer earlier and more accurate prediction capability. Due to limited availability of molecular data and the infrequency of lethal prostate cancer (compared to harmless type), scientists have not been successful in discovering clinically useful molecular biomarkers of prostate cancer that can accurately detect lethal prostate cancer and predict the outcomes of its treatments. Oncologists have discovered remarkable biological similarities between breast, ovarian, and prostate cancers, which suggests biomarker commonality across these cancers. This discovery presents unique opportunities in synthesizing knowledge from other cancers with prostate cancer. Computer scientists’ progress in harnessing information and transfer of knowledge across different fields makes it possible to discover prostate cancer biomarkers. These cancer biomarkers can be also used to measure the effect on cells’ biological processes for drug repurposing (investigate existing drugs for use in treating new conditions). Objective: Discover clinically useful prostate cancer biomarkers by synthesizing knowledge from breast and ovarian cancers and reposition existing drugs using cell biological mechanisms impacted by these biomarkers. Specific Aims: 1. Discover prostate cancer specific biomarkers as well as jointly significant biomarkers across breast, prostate, and ovarian cancers using advanced mathematical and computational models. 2. Understand gene interactions and processes specific to prostate cancer and common across other biologically similar cancers to better understand the prostate cancer biology. 3. Identify treatment options common across prostate cancer and other biologically similar cancers by discovering new uses of FDA-approved drugs and drugs under trial beyond their initial approved indications. What Are the Likely Contributions of This Study to the FY19 PCRP Overarching Challenges? Aims 1 and 2 would help define the biology of lethal PCa to reduce death, and Aim 3 would help develop treatments leading to improved outcomes and reduced mortality. What Types of Patients Will It Help and How Will It Help Them? This research will significantly improve patient care by discovering a set biomarkers associated with primary and lethal prostate cancers, which would lead to more targeted and personalized treatment decisions. In addition, for those not responding well to prostate cancer targeting drugs (i.e., organ-specific drugs) or having complications, this research could potentially offer alternative multi-cancer treatment drugs through drug repurposing. What Are the Potential Clinical Applications, Benefits, and Risks? Clinical application of this research’s results will help clinicians better differentiate between treatment options for those with lethal and less harmful prostate cancers and guide their clinical decision-making and treatment planning specific to the patient’s characteristics. Benefits will be realized through avoidance of over-treating certain indolent prostate cancers and more aggressive and timely start of treatment for aggressive and lethal pro
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 05, 2021
- Source ID
- W81XWH2110570
Entities
People
- Suzan Arslanturk
Organizations
- United States Army
- Wayne State University