anti-EGFR capture mitigates EMT- and chemoresistance-associated heterogeneity in a resistance-profiling CTC platform.

Capture and analysis of circulating tumor cells (CTCs) holds promise for diagnosing and guiding treatment of pancreatic cancer. To accurately monitor disease progression, capture platforms must be robust to processes that increase the phenotypic heterogeneity of CTCs. Most CTC-analysis technologies rely on the recognition of epithelial-specific markers for capture and identification, in particular the epithelial cell-adhesion molecule (EpCAM) and cytokeratin.

Randomized, Noncomparative, Phase II Trial of Early Switch From Docetaxel to Cabazitaxel or Vice Versa, With Integrated Biomarker Analysis, in Men With Chemotherapy-Naïve, Metastatic, Castration-Resistant Prostate Cancer.

Purpose The TAXYNERGY trial ( ClinicalTrials.gov identifier: NCT01718353) evaluated clinical benefit from early taxane switch and circulating tumor cell (CTC) biomarkers to interrogate mechanisms of sensitivity or resistance to taxanes in men with chemotherapy-naïve, metastatic, castration-resistant prostate cancer. Patients and Methods Patients were randomly assigned 2:1 to docetaxel or cabazitaxel.

Comparison and optimization of machine learning methods for automated classification of circulating tumor cells.

Advances in rare cell capture technology have made possible the interrogation of circulating tumor cells (CTCs) captured from whole patient blood. However, locating captured cells in the device by manual counting bottlenecks data processing by being tedious (hours per sample) and compromises the results by being inconsistent and prone to user bias. Some recent work has been done to automate the cell location and classification process to address these problems, employing image processing and machine learning (ML) algorithms to locate and classify cells in fluorescent microscope images.

Microfluidic immunocapture of circulating pancreatic cells using parallel EpCAM and MUC1 capture: characterization, optimization and downstream analysis.

We have developed and optimized a microfluidic device platform for the capture and analysis of circulating pancreatic cells (CPCs) and pancreatic circulating tumor cells (CTCs). Our platform uses parallel anti-EpCAM and cancer-specific mucin 1 (MUC1) immunocapture in a silicon microdevice. Using a combination of anti-EpCAM and anti-MUC1 capture in a single device, we are able to achieve efficient capture while extending immunocapture beyond single marker recognition.

Detection of circulating pancreas epithelial cells in patients with pancreatic cystic lesions.

Hematogenous dissemination is thought to be a late event in cancer progression. We recently showed in a genetic model of pancreatic ductal adenocarcinoma that pancreas cells can be detected in the bloodstream before tumor formation. To confirm these findings in humans, we used microfluidic geometrically enhanced differential immunocapture to detect circulating pancreas epithelial cells in patient blood samples.

Parametric control of collision rates and capture rates in geometrically enhanced differential immunocapture (GEDI) microfluidic devices for rare cell capture.

The enrichment and isolation of rare cells from complex samples, such as circulating tumor cells (CTCs) from whole blood, is an important engineering problem with widespread clinical applications. One approach uses a microfluidic obstacle array with an antibody surface functionalization to both guide cells into contact with the capture surface and to facilitate adhesion; geometrically enhanced differential immunocapture is a design strategy in which the array is designed to promote target cell–obstacle contact and minimize other interactions (Gleghorn et al. 2010; Kirby et al.