Qihui Shi

A clinical microchip for evaluation of single immune cells reveals high functional heterogeneity in phenotypically similar T cells.

Cellular immunity has an inherent high level of functional heterogeneity. Capturing the full spectrum of these functions requires analysis of large numbers of effector molecules from single cells. We report a microfluidic platform designed for highly multiplexed (more than ten proteins), reliable, sample-efficient (∼1 × 104 cells) and quantitative measurements of secreted proteins from single cells. We validated the platform by assessment of multiple inflammatory cytokines from lipopolysaccharide (LPS)-stimulated human macrophages and comparison to standard immunotechnologies. We applied the platform toward the ex vivo quantification of T cell polyfunctional diversity via the simultaneous measurement of a dozen effector molecules secreted from tumor antigen–specific cytotoxic T lymphocytes (CTLs) that were actively responding to tumor and compared against a cohort of healthy donor controls. We observed profound, yet focused, functional heterogeneity in active tumor antigen–specific CTLs, with the major functional phenotypes quantitatively identified. The platform represents a new and informative tool for immune monitoring and clinical assessment.

Single-cell proteomic chip for profiling intracellular signaling pathways in single tumor cells

We describe a microchip designed to quantify the levels of a dozen cytoplasmic and membrane proteins from single cells. We use the platform to assess protein–protein interactions associated with the EGF-receptor-mediated PI3K signaling pathway. Single-cell sensitivity is achieved by isolating a defined number of cells (n = 0–5) in 2 nL volume chambers, each of which is patterned with two copies of a miniature antibody array. The cells are lysed on-chip, and the levels of released proteins are assayed using the antibody arrays. We investigate three isogenic cell lines representing the cancer glioblastoma multiforme, at the basal level, under EGF stimulation, and under erlotinib inhibition plus EGF stimulation. The measured protein abundances are consistent with previous work, and single-cell analysis uniquely reveals single-cell heterogeneity, and different types and strengths of protein–protein interactions. This platform helps provide a comprehensive picture of altered signal transduction networks in tumor cells and provides insight into the effect of targeted therapies on protein signaling networks.

Self-powered microfluidic chips for multiplexed protein assays from whole blood

We report herein on a self-powered, self-contained microfluidic-based chip designed to separate plasma from whole blood, and then execute an assay of a multiplexed panel of plasma biomarker proteins. The power source is based upon a chemical reaction that is catalytically triggered by the push of a button on the chip. We demonstrate assays of a dozen blood-based protein biomarkers using this automated, self-contained device. This platform can potentially permit high throughput, accurate, multiplexed blood diagnostic measurements in remote locations and by minimally trained individuals.

Quantitating cell-cell interaction functions with applications to glioblastoma multiforme cancer cells.

We report on a method for quantitating the distance dependence of cell-cell interactions. We employ a microchip design that permits a multiplex, quantitative protein assay from statistical numbers of cell pairs, as a function of cell separation, with a 0.15 nL volume microchamber. We interrogate interactions between pairs of model brain cancer cells by assaying for six functional proteins associated with PI3k signaling. At short incubation times, cells do not appear to influence each other, regardless of cell separation. For 6 h incubation times, the cells exert an inhibiting influence on each other at short separations and a predominately activating influence at large separation. Protein-specific cell-cell interaction functions are extracted, and by assuming pairwise additivity of those interactions, the functions are shown to correctly predict the results from three-cell experiments carried out under the identical conditions.

Chemistries for Patterning Robust DNA MicroBarcodes Enable Multiplex Assays of Cytoplasm Proteins from Single Cancer Cells

The optimization of chemistries to enable the patterning of miniaturized DNA barcodes using microfluidics flow channels is described (see picture). Experiment and theory reveal that solvent mixtures in which counterions are strongly associated with the negatively charged DNA oligomers may be harnessed to produce high quality, high density DNA microarray patterns over a large area.

Hypoxia induces a phase transition within a kinase signaling network in cancer cells

Significance Reduced oxygen supply—hypoxia—is a near-universal feature of solid tumors that can alter how tumors respond to therapies. We investigated the transition from normoxia to hypoxia in model brain cancer systems, using single-cell proteomics and data analysis tools based on physicochemical concepts. This approach permits the simplification of otherwise complex biology. We find a hypoxia-induced switch within a mammalian target of rapamycin (mTOR) signaling network. At the switching point, mTOR is predicted, and then shown by experiment, to be unresponsive to inhibition. These results may help explain the undistinguished performance of mTOR inhibitors in certain clinical trials. Hypoxia is a near-universal feature of cancer, promoting glycolysis, cellular proliferation, and angiogenesis. The molecular mechanisms of hypoxic signaling have been intensively studied, but the impact of changes in oxygen partial pressure (pO2) on the state of signaling networks is less clear. In a glioblastoma multiforme (GBM) cancer cell model, we examined the response of signaling networks to targeted pathway inhibition between 21% and 1% pO2. We used a microchip technology that facilitates quantification of a panel of functional proteins from statistical numbers of single cells. We find that near 1.5% pO2, the signaling network associated with mammalian target of rapamycin (mTOR) complex 1 (mTORC1)—a critical component of hypoxic signaling and a compelling cancer drug target—is deregulated in a manner such that it will be unresponsive to mTOR kinase inhibitors near 1.5% pO2, but will respond at higher or lower pO2 values. These predictions were validated through experiments on bulk GBM cell line cultures and on neurosphere cultures of a human-origin GBM xenograft tumor. We attempt to understand this behavior through the use of a quantitative version of Le Chatelier’s principle, as well as through a steady-state kinetic model of protein interactions, both of which indicate that hypoxia can influence mTORC1 signaling as a switch. The Le Chatelier approach also indicates that this switch may be thought of as a type of phase transition. Our analysis indicates that certain biologically complex cell behaviors may be understood using fundamental, thermodynamics-motivated principles.

Single-cell codetection of metabolic activity, intracellular functional proteins, and genetic mutations from rare circulating tumor cells.

The high glucose uptake and activation of oncogenic signaling pathways in cancer cells has long made these features, together with the mutational spectrum, prime diagnostic targets of circulating tumor cells (CTCs). Further, an ability to characterize these properties at a single cell resolution is widely believed to be essential, as the known extensive heterogeneity in CTCs can obscure important correlations in data obtained from cell population-based methods. However, to date, it has not been possible to quantitatively measure metabolic, proteomic, and genetic data from a single CTC. Here we report a microchip-based approach that allows for the codetection of glucose uptake, intracellular functional proteins, and genetic mutations at the single-cell level from rare tumor cells. The microchip contains thousands of nanoliter grooves (nanowells) that isolate individual CTCs and allow for the assessment of their glucose uptake via imaging of a fluorescent glucose analog, quantification of a panel of intracellular signaling proteins using a miniaturized antibody barcode microarray, and retrieval of the individual cell nuclei for subsequent off-chip genome amplification and sequencing. This approach integrates molecular-scale information on the metabolic, proteomic, and genetic status of single cells and permits the inference of associations between genetic signatures, energy consumption, and phosphoproteins oncogenic signaling activities in CTCs isolated from blood samples of patients. Importantly, this microchip chip-based approach achieves this multidimensional molecular analysis with minimal cell loss (<20%), which is the bottleneck of the rare cell analysis.

Single cell proteomics in biomedicine: High‐dimensional data acquisition, visualization and analysis

New insights on cellular heterogeneity in the last decade provoke the development of a variety of single cell omics tools at a lightning pace. The resultant high‐dimensional single cell data generated by these tools require new theoretical approaches and analytical algorithms for effective visualization and interpretation. In this review, we briefly survey the state‐of‐the‐art single cell proteomic tools with a particular focus on data acquisition and quantification, followed by an elaboration of a number of statistical and computational approaches developed to date for dissecting the high‐dimensional single cell data. The underlying assumptions, unique features, and limitations of the analytical methods with the designated biological questions they seek to answer will be discussed. Particular attention will be given to those information theoretical approaches that are anchored in a set of first principles of physics and can yield detailed (and often surprising) predictions.

High-throughput screening of rare metabolically active tumor cells in pleural effusion and peripheral blood of lung cancer patients

Significance Identification of cancer cells in the pleural effusions of lung cancer patients is an important clinical diagnosis to verify the malignant pleural involvement. Elevated glucose uptake is a hallmark of cancer cells and has been used in positron-emission tomography to detect malignant tumors in vivo. We hypothesize that cells with enhanced glucose uptake and without expression of leukocyte markers in pleural effusion or peripheral blood samples are highly likely to be malignant cells that can be confirmed via single-cell sequencing. To this end, a high-throughput metabolic-based assay is developed for rapid detection of rare metabolically active tumor cells in pleural effusion, enabling sensitive diagnosis of malignant pleural effusion in the clinic that is associated with metastatic malignancies. Malignant pleural effusion (MPE), the presence of malignant cells in pleural fluid, is often the first sign of many cancers and occurs in patients with metastatic malignancies. Accurate detection of tumor cells in pleural fluid is crucial because the presence of MPE denotes an advanced stage of disease and directs a switch in clinical managements. Cytology, as a traditional diagnostic tool, has limited sensitivity especially when tumor cells are not abundant, and may be confounded by reactive mesothelial cells in the pleural fluid. We describe a highly sensitive approach for rapid detection of metabolically active tumor cells in MPE via exploiting the altered glucose metabolism of tumor cells relative to benign cells. Metabolically active tumor cells with high glucose uptake, as evaluated by a fluorescent glucose analog (2-NBDG), are identified by high-throughput fluorescence screening within a chip containing 200,000 addressable microwells and collected for malignancy confirmation via single-cell sequencing. We demonstrate the utility of this approach through analyzing MPE from a cohort of lung cancer patients. Most candidate tumor cells identified are confirmed to harbor the same driver oncogenes as their primary lesions. In some patients, emergence of secondary mutations that mediate acquired resistance to ongoing targeted therapies is also detected before resistance is manifested in the clinical imaging. The detection scheme can be extended to analyze peripheral blood samples. Our approach may serve as a valuable complement to cytology in MPE diagnosis, helping identify the driver oncogenes and resistance-leading mutations for targeted therapies.

A microfluidic chip with double-sided herringbone microstructures for enhanced capture of rare tumor cells

A microfluidic chip with single-sided herringbone microstructure has been developed to isolate circulating tumor cells (CTCs) from blood samples of cancer patients. Here, we describe a new double-sided herringbone chip in which staggered herringbone micromixers are placed on both top and bottom surfaces of microchannels. The double-sided herringbone structure enables a high CTC capture efficiency of whole blood samples without depletion of red blood cells because of the effects of leukocyte margination and plasma skimming. However, compared with the traditional single-sided herringbone chip, the double-sided herringbone chip has more complicated geometrical design, leading to a difficulty in experimental optimization of geometrical parameters. In this study, we developed an analytical model to geometrically optimize the herringbone chip by investigating the interactions between cells and antibody-immobilized device surfaces for enhancing CTC capture efficiency. On-chip cell capture experiments for validating modeling results were performed by spiking cultured EpCAM-positive tumor cells into blood samples from healthy donors. Based on the geometrical parameters optimized from the single-sided herringbone chip, the geometrically optimized double-sided herringbone chip enables a capture efficiency of 94 ± 4% of rare tumor cells directly from whole blood.