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.