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Mol Cell Proteomics. 2018 Apr;17(4):619-630. doi: 10.1074/mcp.RA117.000370. Epub 2018 Jan 20.

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

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From the ‡Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania.
§Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts.
¶Department of Pharmaceutical Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania.
‖Department of Cell Biology, University of Pittsburgh, Pittsburgh, Pennsylvania.
**University of Pittsburgh Cancer Center, Pittsburgh, Pennsylvania.
From the ‡Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania;
‡‡McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
§§Pittsburgh VA Medical Center, VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania.


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 all-human 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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