Daniel R. Gossett

Cell separation and sorting are essential steps in cell biology research and in many diagnostic and therapeutic methods. Recently, there has been interest in methods which avoid the use of biochemical labels; numerous intrinsic biomarkers have been explored to identify cells including size, electrical polarizability, and hydrodynamic properties. This review highlights microfluidic techniques used for label-free discrimination and fractionation of cell populations. Microfluidic systems have been adopted to precisely handle single cells and interface with other tools for biochemical analysis. We analyzed many of these techniques, detailing their mode of separation, while concentrating on recent developments and evaluating their prospects for application. Furthermore, this was done from a perspective where inertial effects are considered important and general performance metrics were proposed which would ease comparison of reported technologies. Lastly, we assess the current state of these technologies and suggest directions which may make them more accessible.

Cell state is often assayed through measurement of biochemical and biophysical markers. Although biochemical markers have been widely used, intrinsic biophysical markers, such as the ability to mechanically deform under a load, are advantageous in that they do not require costly labeling or sample preparation. However, current techniques that assay cell mechanical properties have had limited adoption in clinical and cell biology research applications. Here, we demonstrate an automated microfluidic technology capable of probing single-cell deformability at approximately 2,000 cells/s. The method uses inertial focusing to uniformly deliver cells to a stretching extensional flow where cells are deformed at high strain rates, imaged with a high-speed camera, and computationally analyzed to extract quantitative parameters. This approach allows us to analyze cells at throughputs orders of magnitude faster than previously reported biophysical flow cytometers and single-cell mechanics tools, while creating easily observable larger strains and limiting user time commitment and bias through automation. Using this approach we rapidly assay the deformability of native populations of leukocytes and malignant cells in pleural effusions and accurately predict disease state in patients with cancer and immune activation with a sensitivity of 91% and a specificity of 86%. As a tool for biological research, we show the deformability we measure is an early biomarker for pluripotent stem cell differentiation and is likely linked to nuclear structural changes. Microfluidic deformability cytometry brings the statistical accuracy of traditional flow cytometric techniques to label-free biophysical biomarkers, enabling applications in clinical diagnostics, stem cell characterization, and single-cell biophysics.

A blood-based, low cost alternative to radiation intensive CT and PET imaging is critically needed for cancer prognosis and management of its treatment. "Liquid biopsies" of circulating tumor cells (CTCs) from a relatively non-invasive blood draw are particularly ideal, as they can be repeated regularly to provide up to date molecular information about the cancer, which would also open up key opportunities for personalized therapies. Beyond solely diagnostic applications, CTCs are also a subject of interest for drug development and cancer research. In this paper, we adapt a technology previously introduced, combining the use of micro-scale vortices and inertial focusing, specifically for the high-purity extraction of CTCs from blood samples. First, we systematically varied parameters including channel dimensions and flow rates to arrive at an optimal device for maximum trapping efficiency and purity. Second, we validated the final device for capture of cancer cell lines in blood, considering several factors, including the effect of blood dilution, red blood cell lysis and cell deformability, while demonstrating cell viability and independence on EpCAM expression. Finally, as a proof-of-concept, CTCs were successfully extracted and enumerated from the blood of patients with breast (N = 4, 25-51 CTCs per 7.5 mL) and lung cancer (N = 8, 23-317 CTCs per 7.5 mL). Importantly, samples were highly pure with limited leukocyte contamination (purity 57-94%). This Vortex approach offers significant advantages over existing technologies, especially in terms of processing time (20 min for 7.5 mL of whole blood), sample concentration (collecting cells in a small volume down to 300 μL), applicability to various cancer types, cell integrity and purity. We anticipate that its simplicity will aid widespread adoption by clinicians and biologists who desire to not only enumerate CTCs, but also uncover new CTC biology, such as unique gene mutations, vesicle secretion and roles in metastatic processes.

Optical microscopy is one of the most widely used diagnostic methods in scientific, industrial, and biomedical applications. However, while useful for detailed examination of a small number (< 10,000) of microscopic entities, conventional optical microscopy is incapable of statistically relevant screening of large populations (> 100,000,000) with high precision due to its low throughput and limited digital memory size. We present an automated flow-through single-particle optical microscope that overcomes this limitation by performing sensitive blur-free image acquisition and nonstop real-time image-recording and classification of microparticles during high-speed flow. This is made possible by integrating ultrafast optical imaging technology, self-focusing microfluidic technology, optoelectronic communication technology, and information technology. To show the system's utility, we demonstrate high-throughput image-based screening of budding yeast and rare breast cancer cells in blood with an unprecedented throughput of 100,000 particles/s and a record false positive rate of one in a million.

Biophysical characteristics of cells are attractive as potential diagnostic markers for cancer. Transformation of cell state or phenotype and the accompanying epigenetic, nuclear, and cytoplasmic modifications lead to measureable changes in cellular architecture. We recently introduced a technique called deformability cytometry (DC) that enables rapid mechanophenotyping of single cells in suspension at rates of 1000 cells/s-a throughput that is comparable to traditional flow cytometry. We applied this technique to diagnose malignant pleural effusions, in which disseminated tumor cells can be difficult to accurately identify by traditional cytology. An algorithmic diagnostic scoring system was developed on the basis of quantitative features of two-dimensional distributions of single-cell mechanophenotypes from 119 samples. The DC scoring system classified 63% of the samples into two high-confidence regimes with 100% positive predictive value or 100% negative predictive value, and achieved an area under the curve of 0.86. This performance is suitable for a prescreening role to focus cytopathologist analysis time on a smaller fraction of difficult samples. Diagnosis of samples that present a challenge to cytology was also improved. Samples labeled as "atypical cells," which require additional time and follow-up, were classified in high-confidence regimes in 8 of 15 cases. Further, 10 of 17 cytology-negative samples corresponding to patients with concurrent cancer were correctly classified as malignant or negative, in agreement with 6-month outcomes. This study lays the groundwork for broader validation of label-free quantitative biophysical markers for clinical diagnoses of cancer and inflammation, which could help to reduce laboratory workload and improve clinical decision-making.