Abstract
The early detection of metastatic cells can lead to better prognosis and higher survival rate. These cells have the capacity to travel through the circulatory system and invade other tissues. Often the symptoms for metastasis are not evident until cancer incapacitates a secondary organ. Hence, early detection is crucial. An imaging-based approach with a contour detection technique is presented here to distinguish metastatic breast cancer cells from benign cells when captured on anti-EGFR aptamer modified glass substrates. Metastatic (MDA-MDB-231) and non-metastatic (MCF-7) breast cancer cells were studied. The temporal tracking of cells showed that metastatic cells depicted prominent morphological changes, whereas the benign cells did not show such behavior. The metastatic cells showed rapid changes in their shapes by protruding/retracting cell membranes. The images of each type of cells captured on functionalized substrates were analyzed, and morphology changes were quantified with similarity and distance analysis. Low similarity coefficients and high distance values meant larger morphology changes. The metastatic cells showed lower similarity coefficients and higher distance metric values (average Hausdorff distance = 2.8 a.u.; average Mahalanobis distance = 0.7 a.u.) than non-metastatic cells (average Hausdorff distance = 1.5 a.u.; average Mahalanobis distance = 0.31 a.u.). These parameters were successfully used to detect 52% of metastatic cells from a cell mixture that imitated breast tissue. This approach can be used for detecting metastatic potential of a given sample towards precise therapy for a patient.
Published Version
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