A streamlined platform for high-content functional proteomics of primary human specimens.

Achieving information content of satisfactory breadth and depth remains a formidable challenge for proteomics. This problem is particularly relevant to the study of primary human specimens, such as tumor biopsies, which are heterogeneous and of finite quantity. Here we present a functional proteomics strategy that unites the activity-based protein profiling and multidimensional protein identification technologies (ABPP-MudPIT) for the streamlined analysis of human samples. This convergent platform involves a rapid initial phase, in which enzyme activity signatures are generated for functional classification of samples, followed by in-depth analysis of representative members from each class. Using this two-tiered approach, we identified more than 50 enzyme activities in human breast tumors, nearly a third of which represent previously uncharacterized proteins. Comparison with cDNA microarrays revealed enzymes whose activity, but not mRNA expression, depicted tumor class, underscoring the power of ABPP-MudPIT for the discovery of new markers of human disease that may evade detection by other molecular profiling methods.

Breast cancer cell lines grown in vivo: what goes in isn't always the same as what comes out.

Human cell lines constitute powerful model systems for the in vitro and in vivo analysis of cancer. Cancer lines that are invasive in culture often form tumors and metastases in immune deficient mice. It is generally assumed that, in such cases, the principal population of cancer cells in culture corresponds to the tumor-forming cells in vivo. Here, we high-light a recent functional proteomics investigation that suggests the contrary. In this study, cells derived from orthotopic xenograft tumors formed by the invasive breast cancer line MDA-MB-231 were found to exhibit profound differences in their enzyme activity profiles and increased tumor growth rates and metastasis when compared to the parental line. These findings suggest that the in vivo microenvironment of the mouse mammary fat pad cultivates the growth of human breast cancer cells with elevated tumorigenic properties. Characterization of the unique molecular properties of these tumor-forming cells may reveal new strategies for the diagnosis and treatment of breast cancer.

Carcinoma and stromal enzyme activity profiles associated with breast tumor growth in vivo.

Cancer research depends on the use of human cell lines for both the in vitro (culture) and in vivo (xenograft) analysis of tumor progression and treatment. However, the extent to which cultured preparations of human cancer lines display similar properties in vivo, where important host factors may influence tumor biology, remains unclear. Here, we address this question by conducting a functional proteomic analysis of the human breast cancer line MDA-MB-231 grown in culture and as orthotopic xenograft tumors in the mammary fad pad of immunodeficient mice. Using a suite of activity-based chemical probes, we identified carcinoma (human) enzyme activities that were expressed selectively in culture or in xenograft tumors. Likewise, distinct groups of stromal (mouse) enzyme activities were found that either infiltrated or were excluded from xenograft tumors, indicating a contribution by specific host components to breast cancer development. MDA-MB-231 cells isolated from tumors exhibited profound differences in their enzyme activity profiles compared with the parent cell line, including the dramatic posttranscriptional up-regulation of the serine proteases urokinase plasminogen activator and tissue plasminogen activator and down-regulation of the glycolytic enzyme phosphofructokinase. These altered enzyme activity profiles correlated with significantly greater tumor growth rates and metastases for xenograft-derived MDA-MB-231 cells upon reintroduction into mice. Collectively, these data indicate that the in vivo environment of the mouse mammary fat pad cultivates the growth of human breast cancer cells with elevated tumorigenic properties and highlight the value of activity-based protein profiling for identifying proteomic signatures that depict such changes in cancer cell biology.

Activity-based probes for the proteomic profiling of metalloproteases.

Metalloproteases (MPs) are a large and diverse class of enzymes implicated in numerous physiological and pathological processes, including tissue remodeling, peptide hormone processing, and cancer. MPs are tightly regulated by multiple posttranslational mechanisms in vivo, hindering their functional analysis by conventional genomic and proteomic methods. Here we describe a general strategy for creating activity-based proteomic probes for MPs by coupling a zinc-chelating hydroxamate to a benzophenone photocrosslinker, which promote selective binding and modification of MP active sites, respectively. These probes labeled active MPs but not their zymogen or inhibitor-bound counterparts and were used to identify members of this enzyme class up-regulated in invasive cancer cells and to evaluate the selectivity of MP inhibitors in whole proteomes. Interestingly, the matrix metalloproteinase inhibitor GM6001 (ilomastat), which is currently in clinical development, was found to also target the neprilysin, aminopeptidase, and dipeptidylpeptidase clans of MPs. These results demonstrate that MPs can display overlapping inhibitor sensitivities despite lacking sequence homology and stress the need to evaluate MP inhibitors broadly across this enzyme class to develop agents with suitable target selectivities in vivo. Activity-based profiling offers a powerful means for conducting such screens, as this approach can be carried out directly in whole proteomes, thereby facilitating the discovery of disease-associated MPs concurrently with inhibitors that selectively target these proteins.

The development and application of methods for activity-based protein profiling.

Recent advances in genomic and proteomic technologies have begun to address the challenge of assigning molecular and cellular functions to the numerous protein products encoded by prokaryotic and eukaryotic genomes. In particular, chemical strategies for proteome analysis have emerged that enable profiling of protein activity on a global scale. Herein, we highlight these chemical proteomic methods and their application to the discovery and characterization of disease-related enzyme activities.

Enzyme activity profiles of the secreted and membrane proteome that depict cancer cell invasiveness.

By primarily measuring changes in transcript and protein abundance, conventional genomics and proteomics methods may fail to detect significant posttranslational events that regulate protein activity and, ultimately, cell behavior. To address these limitations, activity-based proteomic technologies that measure dynamics in protein function on a global scale would be of particular value. Here, we describe the application of a chemical proteomics strategy to quantitatively compare enzyme activities across a panel of human breast and melanoma cancer cell lines. A global analysis of the activity, subcellular distribution, and glycosylation state for the serine hydrolase superfamily resulted in the identification of a cluster of proteases, lipases, and esterases that distinguished cancer lines based on tissue of origin. Strikingly, nearly all of these enzyme activities were down-regulated in the most invasive cancer lines examined, which instead up-regulated a distinct set of secreted and membrane-associated enzyme activities. These invasiveness-associated enzymes included urokinase, a secreted serine protease with a recognized role in tumor progression, and a membrane-associated hydrolase KIAA1363, for which no previous link to cancer had been made. Collectively, these results suggest that invasive cancer cells share discrete proteomic signatures that are more reflective of their biological phenotype than cellular heritage, highlighting that a common set of enzymes may support the progression of tumors from a variety of origins and thus represent attractive targets for the diagnosis and treatment of cancer.