4.8 Article

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

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NATL ACAD SCIENCES
DOI: 10.1073/pnas.0404727101

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  1. NCI NIH HHS [R01 CA085405, R37 CA087660, CA087660, R01 CA087660-04, CA085405, R01 CA087660] Funding Source: Medline
  2. NCRR NIH HHS [P41 RR011823, RR11823] Funding Source: Medline

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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.

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