4.7 Article

A Model of Dormant-Emergent Metastatic Breast Cancer Progression Enabling Exploration of Biomarker Signatures

期刊

MOLECULAR & CELLULAR PROTEOMICS
卷 17, 期 4, 页码 619-630

出版社

AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC
DOI: 10.1074/mcp.RA117.000370

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资金

  1. NIH [5UH3TR000496-05]
  2. VA Merit Award
  3. DARPA [BAA-11-73, W911NF-12-2-0039]

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Breast cancer mortality predominantly results from dormant micrometastases that emerge as fatal outgrowths years after initial diagnosis. In order to gain insights concerning factors associated with emergence of liver metastases, we recreated spontaneous dormancy in an allhuman ex vivo hepatic microphysiological system (MPS). Seeding this MPS with small numbers (<0.05% by cell count) of the aggressive MDA-MB-231 breast cancer cell line, two populations formed: actively proliferating (growing; EdU(+)), and spontaneously quiescent (dormant; EdU(-)). Following treatment with a clinically standard chemotherapeutic, the proliferating cells were eliminated and only quiescent cells remained; this residual dormant population could then be induced to a proliferative state (emergent; EdU(+)) by physiologically-relevant inflammatory stimuli, lipopolysaccharide (LPS) and epidermal growth factor (EGF). Multiplexed proteomic analysis of the MPS effluent enabled elucidation of key factors and processes that correlated with the various tumor cell states, and candidate biomarkers for actively proliferating (either primary or secondary emergence) versus dormant metastatic cells in liver tissue. Dormancy was found to be associated with signaling reflective of cellular quiescence even more strongly than the original tumor-free liver tissue, whereas proliferative nodules presented inflammatory signatures. Given the minimal tumor burden, these markers likely represent changes in the tumor microenvironment rather than in the tumor cells. A computational decision tree algorithm applied to these signatures indicated the potential of this MPS for clinical discernment of each metastatic stage from blood protein analysis.

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