Identifying Genetic, Transcriptional, and Microenvironment Drivers of Lethal Prostate Cancer for Patient Stratification, Disease Tracking, and Drug Target Discovery
Abstract
One in seven men will be diagnosed with prostate cancer in their lifetime, and approximately 40% will develop metastasis. Although most will initially respond to androgen deprivation therapy, patients inevitably develop resistance, resulting in continued tumor growth. This condition is known as metastatic castration-resistant prostate cancer (mCRPC). mCRPC often displays high levels of androgen receptor (AR), and drugs that block AR activity, such as abiraterone and enzalutamide, initially halt tumor growth but ultimately fail to control the disease. Unfortunately, many patients with mCRPC develop treatment resistance and succumb within 7 to 24 months. There is an urgent need for long-lasting therapies for these patients. While we have an understanding of genetic mechanisms of resistance, these do not fully explain why patients stop responding to treatment. Clues are found in a rare subtype of mCRPC, neuroendocrine (NE) prostate cancer. Here, rather than acquiring mutations, cells go through major gene expression (transcriptional) changes that make them resistant. Since these transcriptional changes occur in all or most NE tumor cells, they can be easily identified with current technologies that measure the average gene expression across millions of cells. However, they are impossible to detect if they only occur in a subset of cells, potentially explaining why we have been unable to detect transcriptional resistance in other subtypes. With state-of-the-art single-cell technology, we can investigate thousands of cells individually and identify cells with distinct transcriptional profiles. Using this exciting new technology, we recently identified multiple distinct types of transcriptional resistance in another form of mCRPC, suggesting that transcriptional resistance is not limited to NE tumors. This led us to hypothesize that transcriptional resistance is widespread across mCRPC. To test this hypothesis, we will: Aim 1. Identify transcriptional resistant tumor cells in mCRPC metastatic samples. We will perform single-nucleus transcriptional analyses of metastatic specimens. The tumors of these patients had developed resistance to all drugs used in the clinic, and therefore all tumor cells in the specimens are resistant to treatment. We will analyze ~6,000 cells per specimen and use bioinformatics (computational tools) to identify populations of tumor cells with distinct transcriptional profiles. These will allow us to narrow down cell populations with transcriptional resistance and identify gene markers that can be used to identify cells with transcriptional resistance. Aim 2. Assess when men with mCRPC develop transcriptional resistance. Since our goal is to be able to detect when transcriptional resistance develops in mCRPC undergoing treatment, we need to first determine whether transcriptional resistance occurs very early in the disease treatment or later on. We will use a computational technique that looks at the DNA of tumor cells to estimate when cells with transcriptional resistance first emerged in the patient. We will determine which treatment coincided with the emergence of transcriptional resistance. This will allow us to identify treatments linked to transcriptional resistance and give us a timeline of when we should start testing for it in the clinic. Aim 3. Investigate how the cells surrounding tumor cells promote transcriptional resistance. Tumor cells often interact with immune cells and other surrounding cells. These surrounding cells can influence the tumor by switching certain genes on and off that can result in the development of transcriptional resistance. Here, we will investigate which cells surround the tumor in distinct metastatic lesions and how they promote transcriptional resistance. The beneficiaries of this project are men with lethal prostate cancer who have stopped responding to standard treatments. This project addresses the FY20 PCRP Overarching Ch
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 05, 2021
- Source ID
- W81XWH2110638
Entities
People
- Shahneen K Sandhu
Organizations
- United States Army
- University of Melbourne