Profiling Enzyme Activities in Human Breast Cancer
Creators: name: University Of California Office Of The President
Publisher: name: University of California Office of the President
publisherIdentifier: https://ror.org/00dmfq477
publisherIdentifierScheme: ROR
Year: 2024

description: The molecular features special to metastatic breast carcinomas that support their motile and invasive behavior are complex and ill-defined. Although one generally 
 
 accepted notion assigns proteins, such as proteases and catabolic enzymes, a central role in promoting the aggressive properties of metastatic breast tumors. Indeed, 
 
 many proteases and their endogenous inhibitors show altered expression patterns (i.e., gene transcription and protein abundance) during breast tumorigenesis; 
 
 however, the overall functional outcome of such changes remains unclear. The current confusion surrounding the relationship between specific enzymes and cancer arises 
 
 from an inability to identify those enzymes whose activities actually change during the progression of this disease. For example, the coincidental or coordinated 
 
 up-regulation of both a protease and its endogenous inhibitor (as occurs in breast cancer for urokinase and its natural inhibitor PAI-1) might result in little net difference in enzyme activity. To better understand how protease and other enzyme activities impact breast cancer, we have developed a novel chemical proteomics strategy, termed activity-based protein profiling (ABPP), that allows complex cell and tissue samples to be studied. 
 
 
 
 
 
 
 
 The translational collaboration supported by this CBCRP grant consists of basic science expertise of ABPP-based proteomics (Dr. Cravatt) with breast cancer gene 
 
 expression profiling and clinical disease classification (Dr. Jeffrey). Previous CBCRP support to Dr. Cravatt successfully applied ABPP probes to the proteomic 
 
 analysis of several enzyme classes across a panel of human breast cancer lines and mouse xenograft models of human breast cancer. These studies resulted in the 
 
 identification of multiple proteases, lipases, and glutathione S-transferases, that were differentially expressed in estrogen receptor (ER)(+) and ER(-) breast cancer lines. The critical next step for the association of these enzymes with breast cancer is to determine whether their expression pattern is maintained in primary human tumors. Since genomics-based research by Dr. Jeffrey and others has shown that clinical breast cancers are divided into a variety of sub-types, it becomes important to apply the ABPP methodology to breast cancer sub-types and relate critical, cell invasion-related protease activity to other key cancer genes. Since proteases are thought to be so tightly associated with metastasis, this information will shed light on this aspect of clinical disease progression and outcome. Accordingly, we propose to use ABPP to determine the enzyme activity profiles of a panel of primary human breast tumors and correlate these proteomic data to key molecular and clinical parameters, including 1) gene expression profiles, 2) tumor type and grade, and 3) survival outcome. In addition to ABPP, we will employ biostatistics, in situ hybridization, and immunohistochemistry techniques, so that gene transcript and protein expression data can be compared to protein activity. These studies should not only validate of our cell line-derived breast 
 
 cancer markers in the clinical setting, but also identify novel tumor-associated enzyme activities that are not expressed in breast cancer lines. Finally, we will determine the cellular and sub-cellular distribution of key breast cancer enzyme activities, which should provide important insights into the potential roles that these proteins play in tumorigenesis. 
 
 
 
 
 
 
 
 Progress towards better diagnostic and therapeutic agents to treat breast cancer relies heavily on our ability to identify new proteins that are both: 1) up-regulated in breast cancer samples, and 2) of functional relevance to the progression of this disease. We anticipate that our ABPP method will identify novel enzymes that support the growth and metastatic properties of breast cancer in vivo. These enzymes will in turn represent valuable markers and targets for future studies aimed at understanding, diagnosing, and ultimately treating breast cancer.