Prostate tumor cells over-express a prostate specific membrane antigen (PSMA) that can be used as a marker to select these cells from highly heterogeneous clinical samples, even when found in low abundance. Antibodies and aptamers have been developed that specifically bind to PSMA. In this study, anti-PSMA aptamers were immobilized onto the surface of a capture bed poised within a poly(methyl methacrylate), PMMA, microchip, which was fabricated into a high throughput micro-sampling unit (HTMSU) used for the selective isolation of rare circulating prostate tumor cells resident in a peripheral blood matrix. The HTMSU capture bed consisted of 51 ultra-high aspect ratio parallel curvilinear channels with a width similar to the prostate cancer cell dimensions. The surface density of the PSMA-specific aptamers on a UV-modified PMMA microfluidic capture bed surface was determined to be 8.4 × 10 12 molecules/cm 2 . Using a linear velocity for optimal cell capture in the aptamer-tethered HTMSU (2.5 mm/s), a recovery of 90% of LNCaP cells (prostate cancer cell line; used as a model in this example) was found. Due to the low abundance of these cells, the input volume required was 1 mL and this could be processed in approximately 29 min using an optimized linear flow rate of 2.5 mm/s. Captured cells were subsequently released intact from the affinity surface using 0.25% (w/v) trypsin followed by counting individual cells using a contact conductivity sensor integrated into the HTMSU that provided high detection and sampling efficiency (~100%) and did not require staining of the cells for enumeration.

A circulating tumor cell (CTC) selection microfluidic device was integrated to an electrokinetic enrichment device for preconcentrating CTCs directly from whole blood to allow for the detection of mutations contained within the genomic DNA of the CTCs. Molecular profiling of CTCs can provide important clinical information that cannot be garnered simply by enumerating the selected CTCs. We evaluated our approach using SW620 and HT29 cells (colorectal cancer cell lines) seeded into whole blood as a model system. Because SW620 and HT29 cells overexpress the integral membrane protein EpCAM, they could be immunospecifically selected using a microfluidic device containing anti-EpCAM antibodies immobilized to the walls of a selection bed. The microfluidic device was operated at an optimized flow rate of 2 mm s−1, which allowed for the ability to process 1 mL of whole blood in <40 min. The selected CTCs were then enzymatically released from the antibody selection surface and hydrodynamically transported through a pair of Pt electrodes for conductivity-based enumeration. The efficiency of CTC selection was found to be 96% ± 4%. Following enumeration, the CTCs were hydrodynamically transported at a flow rate of 1 μL min−1 to an on-chip electromanipulation unit, where they were electrophoretically withdrawn from the bulk hydrodynamic flow and directed into a receiving reservoir. Using an electric field of 100 V cm−1, the negatively charged CTCs were enriched into an anodic receiving reservoir to a final volume of 2 μL, providing an enrichment factor of 500. The collected CTCs could then be searched for point mutations using a PCR/LDR/capillary electrophoresis assay. The DNA extracted from the CTCs was subjected to a primary polymerase chain reaction (PCR) with the amplicons used for a ligase detection reaction (LDR) to probe for KRAS oncogenic point mutations. Point mutations in codon 12 of the KRAS gene were successfully detected in the SW620 CTCs for samples containing <10 CTCs in 1 mL of whole blood. However, the HT29 cells did not contain these mutations, consistent with their known genotype.

In this manuscript, we discuss the development and clinical use of a thermoplastic modular microsystem for the high-throughput analysis of CTCs directly from whole blood. The modular system offers some innovative features that address challenges currently associated with many CTC platforms; it can exhaustively process 7.5 ml of blood in less than 45 min with recoveries >90%. In addition, the system automates the post-selection CTC processing steps and thus, significantly reduces assay turnaround time (from selection to enumeration <1.5 h as compared to >8 h for many reported CTC platforms). The system is comprised of 3 functional modules including; (i) a thermoplastic CTC selection module composed of high aspect ratio (30 μm × 150 μm) channels containing anti-EpCAM antibodies that is scalable in terms of throughput by employing channel numbers ranging from 50 to 320 – the channel number is user selected to accommodate the volume of blood that must be processed; (ii) an impedance sensor module for label-less CTC counting; and (iii) a staining and imaging module for the placement of released cells into a 2D array within a common imaging plane for phenotypic identification. To demonstrate the utility of this system, blood samples from patients with local resectable and metastatic pancreatic ductal adenocarcinoma (PDAC) were analyzed. We demonstrate the ability to select EpCAM positive CTCs from PDAC patients in high purity (>86%) and with excellent yields (mean = 53 CTCs per ml for metastatic PDAC patients) using our modular system. In addition, we demonstrate the ability to detect CTCs in PDAC patients with local resectable disease (mean = 11 CTCs per ml).

Efficient selection and enumeration of low-abundance biological cells are highly important in a variety of applications. For example, the clinical utility of circulating tumor cells (CTCs) in peripheral blood is recognized as a viable biomarker for the management of various cancers, in which the clinically relevant number of CTCs per 7.5 ml of blood is two to five. Although there are several methods for isolating rare cells from a variety of heterogeneous samples, such as immunomagnetic-assisted cell sorting and fluorescence-activated cell sorting, they are fraught with challenges. Microsystem-based technologies are providing new opportunities for selecting and isolating rare cells from complex, heterogeneous samples. Such approaches involve reductions in target-cell loss, process automation, and minimization of contamination issues. In this review, we introduce different application areas requiring rare cell analysis, conventional techniques for their selection, and finally microsystem approaches for low-abundance-cell isolation and enumeration.

Low abundant (<100 cells mL -1 ) E. coli O157:H7 cells were isolated and enriched from environmental water samples using a microfluidic chip. The poly(methylmethacrylate), PMMA, chip contained 8 devices each equipped with 16 curvilinear high aspect ratio channels that were covalently decorated with polyclonal anti-O157 antibodies (pAb) and could search for rare cells through a pAb mediated process. The chip could process independently 8 different samples or one sample using 8 different parallel inputs to increase volume processing throughput. After cell enrichment, cells were released and enumerated using bench top real-time quantitative PCR, targeting genes which effectively discriminated the O157:H7 serotype from other non-pathogenic bacteria. The recovery of target cells from water samples was determined to be ~72%, and the limit-of-detection was found to be 6 colony forming units (cfu) using the slt1 gene as a reporter. We subsequently performed analysis of lake and waste water samples. The simplicity in manufacturing and ease of operation makes this device attractive for the selection of pathogenic species from a variety of water supplies suspected of containing bacterial pathogens at extremely low frequencies.

T-cell responses to minor histocompatibility antigens (mHAs) mediate both antitumor immunity (graft-versus-leukemia [GVL]) and graft-versus-host disease (GVHD) in allogeneic stem cell transplant. Identifying mHAs with high allele frequency, tight binding affinity to common HLA molecules, and narrow tissue restriction could enhance immunotherapy against leukemia. Genotyping and HLA allele data from 101 HLA-matched donor-recipient pairs (DRPs) were computationally analyzed to predict both class I and class II mHAs likely to induce either GVL or GVHD. Roughly twice as many mHAs were predicted in HLA-matched unrelated donor (MUD) stem cell transplantation (SCT) compared with HLA-matched related transplants, an expected result given greater genetic disparity in MUD SCT. Computational analysis predicted 14 of 18 previously identified mHAs, with 2 minor antigen mismatches not being contained in the patient cohort, 1 missed mHA resulting from a noncanonical translation of the peptide antigen, and 1 case of poor binding prediction. A predicted peptide epitope derived from GRK4, a protein expressed in acute myeloid leukemia and testis, was confirmed by targeted differential ion mobility spectrometry-tandem mass spectrometry. T cells specific to UNC-GRK4-V were identified by tetramer analysis both in DRPs where a minor antigen mismatch was predicted and in DRPs where the donor contained the allele encoding UNC-GRK4-V, suggesting that this antigen could be both an mHA and a cancer-testis antigen. Computational analysis of genomic and transcriptomic data can reliably predict leukemia-associated mHA and can be used to guide targeted mHA discovery.

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Differential ion mobility spectrometry (DIMS) can be used as a filter to remove undesired background ions from reaching the mass spectrometer. The ability to use DIMS as a filter for known analytes makes DIMS coupled to tandem mass spectrometry (DIMS–MS/MS) a promising technique for the detection of cancer antigens that can be predicted by computational algorithms. In experiments using DIMS–MS/MS that were performed without the use of high-performance liquid chromatography (HPLC), a predicted model antigen, GLR (FLSSANEHL), was detected at a concentration of 10 pM (20 amol) in a mixture containing 94 competing model peptide antigens, each at a concentration of 1 μM. Without DIMS filtering, the GLR peptide was undetectable in the mixture even at 100 nM. Again, without using HPLC, DIMS–MS/MS was used to detect 2 of 3 previously characterized antigens produced by the leukemia cell line U937.A2. Because of its sensitivity, a targeted DIMS–MS/MS methodology can likely be used to probe for predicted cancer antigens from cancer cell lines as well as human tumor samples.