Combining fluorescence-based image segmentation and automated microfluidics for ultrafast cell-by-cell assessment of biomarkers for HER2-type breast carcinoma

Immunohistochemistry (IHC) is one of the main clinical techniques for biomarker assessment on tissue biopsies. It consists in chromogenic labeling with specific antibodies, followed by optical imaging, and it is used for diagnosis and therapeutic targeting. A well-known drawback of IHC is its limited robustness, which often precludes quantitative biomarker assessment. We combine microfluidic immunostaining, fluorescence imaging, and image-based cell segmentation to create an ultrafast procedure for accurate biomarker assessment via IHC. The experimental protocol is very simple and based on fast delivery of reagents in a microfluidic chamber created by clamping a half-chamber patterned in a silicon chip on top of a tumor tissue section. Also, the imaging procedure simply requires a standard fluorescence microscope, already widely used in clinical practice. The image processing is based on local-contrast enhancement and thresholding of the obtained fluorescence image, with subsequent Voronoi segmentation. To assess the experimental and analytical procedure on robust biological controls, we apply our method to well-characterized cell lines, which guarantee higher reproducibility than whole-tissue samples and therefore enable to disentangle the technical variability from the biological variability. To increase the potential translationality, we address the detection and quantification of the human epidermal growth factor receptor 2 (HER2) protein, which is a biomarker for HER2-type breast carcinoma diagnosis and therapy. We report both ultrafast immunofluorescence staining (5 min per sample) of two breast cancer biomarkers and ultrafast cell segmentation (1 min per sample = processing of thousands of cells). This provides a quantitative, cell-based immunofluorescent signal, with which we propose a potential diagnostic criterion to separate HER2-positive and HER2-negative breast cancer cells at high sensitivity and specificity. (c) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License.