An Integrated Genomic Definition and Therapeutic Strategy for Androgen-Indifferent Prostate Cancers
Abstract
Prostate cancer develops when the prostate’s normal control system becomes faulty. This malfunctioning of the control system leads to out-of-control cell growth and forms a mass of tissue called a tumor. For decades, we have focused on the prostate cancer cell alone and held the prevailing view that it is the accumulation of genetic aberrations that drives tumor progression. However, it is becoming increasingly clear that in addition to accumulation of genetic aberrations, the interaction of the cancer cell with others, such as immune cells, in its microenvironment enables it to adopt different cellular identities that allow it to adapt to its surroundings and to the pressures of treatment. This ability to change cellular identities is termed plasticity and is now understood to have a principal role in prostate cancers that are resistant to androgen signaling inhibitors. Unfortunately, there is no measurable definition of plasticity that can help to identify it and develop it as a biomarker of the disease or a therapy target. This is a critical unmet need. We propose to develop computational tools to quantify plasticity using existing data from tumor biopsies of patients with advanced prostate cancers. This measure of plasticity can serve as a metric to better classify patients and predict therapeutic benefits. Further, we will use deep learning tools to determine the association between plasticity scores and improve on biomarker signatures that can be currently obtained in clinical practice to accelerate their clinical applicability. In the process, we will also develop robust, user-friendly, and open-source bioinformatics software to further prostate cancer genomic studies. The expected results of our studies will address the FY21 PCRP Overarching Challenge to define the biology of lethal prostate cancer to reduce death by developing robust biomarkers that classify the disease into therapeutically relevant subsets. Our computational tools will contribute to the understanding of the dynamic relationships that exist between various molecules (such as DNA, RNA, proteins, etc.) within a tumor or immune cell and this will help better understand prostate cancer heterogeneity and plasticity. In addition, our results will improve the quality of life to enhance outcomes and overall health and wellness for those impacted by prostate cancer by reducing exposure to the toxicities of unnecessary treatments for patients with less aggressive prostate cancers. Finally, we will also provide a foundation to develop treatments that improve outcomes for men with lethal prostate cancer by providing a measurable definition of plasticity that nominates it as a target and facilitates the development of therapies that modulate it.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 28, 2022
- Source ID
- W81XWH2210259
Entities
People
- Ana Aparicio
Organizations
- The University of Texas MD Anderson Cancer Center
- United States Army