Monocyte-derived macrophage assisted breast cancer cell invasion as a personalized, predictive metric to score metastatic risk

Scientific Reports
Keon-Young ParkManu O Platt

Abstract

Patient-to-patient variability in breast cancer progression complicates clinical treatment decisions. Of women undergoing prophylactic mastectomies, many may not have progressed to indolent forms of disease and could have benefited from milder, localized therapy. Tumor associated macrophages contribute significantly to tumor invasion and metastasis, with cysteine cathepsin proteases as important contributors. Here, a method is demonstrated by which variability in macrophage expression of cysteine cathepsins, their inhibitor cystatin C, and kinase activation can be used to train a multivariate model and score patients for invasion risk. These enzymatic profiles were used to predict macrophage-assisted MCF-7 breast cancer cell invasion in the trained computational model. To test these predictions, a priori, signals from monocytes isolated from women undergoing mastectomies were input to score their cancer invasion potential in a patient-specific manner, and successfully predicted that patient monocytes with highest predicted invasion indices matched those with more invasive initial diagnoses of the nine patients tested. Together this establishes proof-of-principle that personalized information acquired from minimally invasive blo...Continue Reading

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Citations

Jan 13, 2017·Protein Science : a Publication of the Protein Society·Meghan C Ferrall-FairbanksManu O Platt
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Mar 13, 2018·ACS Biomaterials Science & Engineering·Maria F GencogluShelly R Peyton

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Methods Mentioned

BETA
imaging techniques
blood draw
proteolytic profiling
confocal microscopy
magnetic
ELISA

Software Mentioned

SIMCA
Bioplex
ImageJ

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