An integrated microfluidic system for automatic detection of cholangiocarcinoma cells from bile.

Abstract

Cholangiocarcinoma (CCA) is an aggressive cancer that originates from the epithelial cells lining the bile ducts. Due to its location deep within the body and nonspecific symptoms in the early stages, it is often diagnosed at the advanced stage, thus leading to worse prognosis. Circulating tumor cells within liquid biopsies (i.e. blood) have been considered as promising biomarkers for CCA diagnosis, though current methods for profiling them are not satisfactory in terms of sensitivity and specificity. Herein we developed a new cancer cell probing and immuno-tracking assay known as "CAPTURE", which was performed on an integrated microfluidic system (IMS) to automate CCA diagnosis from bile with a sample amount of only 1 mL. The assay utilized magnetic beads surface-coated with two affinity reagents, a nucleic acid aptamer (HN16) and a glycosaminoglycan (SCH 45-mix), for capturing cancer cells in bile; the "gold standard" anti-epithelial cell adhesion molecule was used as a comparison. In a single-blind test of 54 CCA-positive (+) and 102 CCA-negative (-) clinical samples, sensitivities and specificities of 96 and 80%, respectively, were documented with the CAPTURE assay on-bench. An IMS composed of a centrifugal module for sample pretreatment and a CAPTURE module for cell capture and staining was integrated with a new "vertical integration module" for detecting cancer cells from bile without human intervention. Furthermore, a novel micro-tier structure within the centrifugal module was designed to block passage of gallbladder stones with diameters >1 mm, thereby preventing their interference during the subsequent CAPTURE assay. Improved sensitivity and specificity (100 & 83%, respectively) by using three affinity reagents were achieved on the IMS when using 26 clinical bile samples, confirming its clinical bio-applicability for CCA diagnosis. This approach could be therefore used for early-stage CCA diagnostics, ideally enabling effective treatment, as well as reducing potential for relapse.