Clinically Translatable Strategies to Improve Therapeutic Response in Metastatic Ovarian Cancers
Abstract
Ovarian cancer continues to be the most lethal gynecologic cancer and the fifth leading cause for cancer-associated deaths among women in the United States. Due to the absence of obvious symptoms and the lack of reliable methods to identify ovarian cancer early, the majority of women who have the disease are diagnosed at an advanced stage. At this stage, the cancer is no longer confined to the ovary, and unfortunately, the existing drugs are ineffective. This limitation of extant drugs and therapeutic strategies is a major limitation and the cause for the high mortality rate associated with ovarian cancer. This clinical reality highlights the urgent need to develop new and more effective ways to treat this deadly disease and translate them rapidly to the clinic. This research proposal outlines the plan to achieve this goal by developing and testing a new therapeutic strategy that addresses key deficiencies in current treatment options and promises to significantly improve the clinical outcome. To achieve this goal, we propose to target two major factors that are associated with disease progression, drug resistance, and poor clinical outcome in ovarian cancer. The first factor is mutations in a gene called p53. While p53 is known to suppress tumor formation, the mutations in this gene, such as the ones seen in about 70 percent of ovarian cancers, convert p53 into a tumor promoting protein that accumulates in cancer cells. The second factor we will target is the tumor-promoting microenvironment prevalent within metastatic ovarian tumors. The tumor-promoting microenvironment prevalent in a majority of ovarian tumors that is believed to be the major reason for the ineffectiveness of immunotherapy in ovarian cancer. Both these factors are extremely common in ovarian cancer and, therefore, by targeting them simultaneously, we aim to develop a therapeutic approach that will benefit a broad spectrum of ovarian cancer patients. Our approach builds on two very exciting recent discoveries made in our laboratory. First, we discovered using mouse models that mimic metastatic ovarian cancer progression that mutations in p53 is a key factor responsible for establishing the tumor-promoting microenvironment prevalent in ovarian cancer patients. This discovery is very important not just from the point of understanding the biology of the disease but also from a therapeutic standpoint. Our data suggest that, if we can develop a strategy to selectively deplete mutated p53 proteins, that are exclusive to cancer cells, we will not just target cancer cells to die and make them sensitive to extant drugs by changing properties that are intrinsic to the cancer cells, but will also induce their killing by recruiting immune cells into the tumors. Moreover, by recruiting more immune cells into the tumor, mutant p53 depletion will remodel the ovarian tumor microenvironment from a tumor promoting one to one that suppresses tumor growth and is permissive to the action of immunotherapy. Thus, combining mutant p53 with immunotherapy will help make immunotherapy effective in metastatic ovarian cancer patients. While extremely attractive, a major challenge in achieving these objectives is identifying therapeutics that will selectively deplete mutant p53 proteins in ovarian cancer cells in a clinically translatable manner. Despite being a highly sought-after therapeutic target mutant p53, targeting mutant p53 in the clinic has been difficult to achieve. Our second exciting discovery promises to overcome this challenge. We discovered that a combination two FDA-approved drugs, metformin and statin (or MET-STAT), both of which have been used in the clinic for decades to treat type-2 diabetes and hyperlipidemia, achieves potent and selective depletion of mutant p53. In this proposal, we will determine MET-STAT’s utility as a therapeutic: (1) by itself, (2) in combination with extant clinically approved chemotherapeutics, and (3) in combinat
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 04, 2024
- Source ID
- HT94252310232
Entities
People
- Achuth Padmanabhan
Organizations
- United States Army
- University of Maryland