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Profiling Enzyme Activities in Human Breast Cancer
Background: The molecular mechanisms special to breast cancer (BC) that support its motile and invasive behavior are complex and ill-defined. To accelerate the discovery of enzymes supporting BC progression, we have developed a novel chemical proteomic strategy termed activity-based protein profiling (ABPP), which uses active site-directed probes to measure changes in enzyme activities in complex samples. Previously, we used ABPP to identify enzyme activities that classify BC cell lines differing in invasiveness and tumorigenic potential. In BC xenograft models, we identified both tumor- and stromal-derived enzyme activities associated with tumor progression in vivo. A critical next step in validating the association of these enzymes with BC is to demonstrate that their activities are maintained in primary tumors and, if so, to define the specific BC subtypes associated with these activities. However, so far, ABPP has been restricted to gel electrophoresis-based methods, which exhibit limited resolution and sensitivity and thus hinder the detection of low-abundance enzymes in biopsies of minute quantity. Objective: We will develop a mass spectrometry-based strategy for quantitative ABPP with unmatched resolution and sensitivity. We will apply it to analyze primary tumors. We hypothesize: 1) enzyme activities upregulated in cancer lines are also upregulated in primary tumors, 2) primary tumors express novel activities not observed in the cancer lines, and 3) BC subtypes differing in grade/outcome display distinct enzyme activity profiles. The proteomic data will be correlated with existing genomic and clinical data to identify novel enzyme activities upregulated in specific BC subtypes. Specific Aims: 1) to develop a mass spectrometry-based, quantitative ABPP method, and 2) to profile enzyme activities in primary breast tumors, and relate the data to gene expression profiles and clinical parameters. Design: Experimental parameters of the gel-free ABPP will be evaluated using a cancer line extensively analyzed by the gel-based method. The optimal protocol will then be combined with isotope-coded ABPP probes to create a quantitative method. We will profile normal breast tissue and a panel of primary tumors differing in grade, biomarker status, and clinical outcome. Potential benefits: This study aims toward answering a central question in BC pathology: what are the molecular mechanisms special to BC that support its progression. It can lead to the discovery of novel enzymes that may serve as both diagnostic/prognostic markers and therapeutic targets of the disease.
Several properties define a cell as cancerous, foremost of which are: 1) indefinite growth, 2) unregulated proliferation, and 3) invasion and colonization of surrounding and distant tissues. It is the third phenotype that marks the most aggressive and debilitating form of cancer. The molecular mechanisms special to breast cancer (BC) that support its aggressive behavior are complex and ill-defined. One generally accepted hypothesis assigns proteins such as proteases and catabolic enzymes a central role in promoting BC progression. Normally, proteases degrade other proteins in a manner that is tightly regulated by our cells and tissues. However, excessive or unregulated protease activity appears to be one of the main factors that permit tumor cells to invade and eventually take over normal tissues. Similarly, catabolic enzymes, which also serve an important function in normal cells, can exhibit increased activity in cancer cells that lead to their resistance to conventional chemotherapy. Despite their well-recognized importance in supporting tumor progression, the identities of these proteases and catabolic enzymes remain elusive.
To accelerate the discovery of enzymes supporting BC progression, we have previously developed a novel method termed activity-based protein profiling (ABPP) that enables direct measurement of the activities of many enzymes in complex samples. Here, we propose to develop an advanced version of the ABPP approach that will exhibit unmatched resolution and sensitivity. This new method will allow us to analyze tumor biopsy samples of minute quantity. We hypothesize that we will identify, from primary tumors, novel enzyme activities that have not been observed in the cellular or animal models of BC, and that BC subtypes differing in grade/outcome will display distinct enzyme activity profiles. Specifically, our tasks are: 1) to develop a mass spectrometry-based, quantitative ABPP method, and 2) to use the new method to analyze normal breast tissue and a panel of primary tumors differing in grade, biomarker status, and clinical outcome. We will correlate our data with existing genomic and clinical data to identify novel enzyme activities associated with specific BC subtypes. This study will help to answer a central question in BC pathology: what are the enzymes special to BC that support its aggressive behavior. It can lead to the discovery of novel enzymes that may serve as both diagnostic/prognostic markers and therapeutic targets of this disease.