Identification, isolation and in vitro expansion of human and nonhuman primate T stem cell memory cell

The T cell compartment is phenotypically and functionally heterogeneous; subsets of naive and memory cells have different functional properties, and also differ with respect to homeostatic potential and the ability to persist in vivo. Human stem cell memory T (TSCM) cells, which possess superior immune reconstitution and antitumor response capabilities, can be identified by polychromatic flow cytometry on the basis of the simultaneous expression of several naive markers together with the memory marker CD95. We describe here a protocol based on the minimum set of markers required for optimal identification of human and nonhuman primate (NHP) TSCM cells with commonly available flow cytometers. By using flow sorters, TSCM cells can thereby be isolated efficiently at high yield and purity. With the use of the 5.5-h isolation procedure, depending on the number of cells needed, the sorting procedure can last for 2-15 h. We also indicate multiple strategies for their efficient expansion in vitro at consistent numbers for functional characterization or adoptive transfer experiments

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells

Rapid flow-sorting to simultaneously resolve multiplex massively parallel sequencing products

Sample preparation for Roche/454, ABI/SOLiD and Life Technologies/Ion Torrent sequencing are based on amplification of library fragments on the surface of beads prior to sequencing. Commonly, libraries are barcoded and pooled, to maximise the sequence output of each sequence run. Here, we describe a novel approach for normalization of multiplex next generation sequencing libraries after emulsion PCR. Briefly, amplified libraries carrying unique barcodes are prepared by fluorescent tagging of complementary sequences and then resolved by high-speed flow cytometric sorting of labeled emulsion PCR beads. The protocol is simple and provides an even sequence distribution of multiplex libraries when sequencing the flow-sorted beads. Moreover, since many empty and mixed emulsion PCR beads are removed, the approach gives rise to a substantial increase in sequence quality and mean read length, as compared to that obtained by standard enrichment protocols

Single-cell analysis tools for drug discovery and development

The genetic, functional or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development. Such heterogeneity hinders the design of accurate disease models and can confound the interpretation of biomarker levels and of patient responses to specific therapies. The complex nature of virtually all tissues has motivated the development of tools for single-cell genomic, transcriptomic and multiplex proteomic analyses. Here, we review these tools and assess their advantages and limitations. Emerging applications of single cell analysis tools in drug discovery and development, particularly in the field of oncology, are discussed

The Duration of Antigen-Stimulation Significantly Alters the Diversity of Multifunctional CD4 T Cells Measured by Intracellular Cytokine Staining

The assessment of antigen-specific T cell responses by intracellular cytokine staining (ICS) has become a routine technique in studies of vaccination and immunity. Here, we highlight how the duration of in vitro antigen pre-stimulation, combined with the cytokine accumulation period, are critical parameters of these methods. The effect of varying these parameters upon the diversity and frequency of multifunctional CD4 T cell subsets has been investigated using a murine model of TB vaccination and in cattle naturally infected with Mycobacterium bovis. We demonstrate a substantial influence of the duration of the antigen pre-stimulation period on the repertoire of the antigen-specific CD4 T cell responses. Increasing pre-stimulation from 2 to 6 hours amplified the diversity of the seven potential multifunctional CD4 T cell subsets that secreted any combination of IFN-γ, IL-2 and TNF-α. However, increasing pre-stimulation from 6 to 16 hours markedly altered the multifunctional CD4 T cell repertoire to a dominant IFN-γ+ only response. This was observed in both murine and cattle models

Sequential Array Cytometry: Multi-Parameter Imaging with a Single Fluorescent Channel

Heterogeneity within the human population and within diseased tissues necessitates a personalized medicine approach to diagnostics and the treatment of diseases. Functional assays at the single-cell level can contribute to uncovering heterogeneity and ultimately assist in improved treatment decisions based on the presence of outlier cells. We aim to develop a platform for high-throughput, single-cell-based assays using well-characterized hydrodynamic cell isolation arrays which allow for precise cell and fluid handling. Here, we demonstrate the ability to extract spatial and temporal information about several intracellular components using a single fluorescent channel, eliminating the problem of overlapping fluorescence emission spectra. Integrated with imaging technologies such as wide field-of-view lens-free fluorescent imaging, fiber-optic array scanning technology, and microlens arrays, use of a single fluorescent channel will reduce the cost of reagents and optical components. Specifically, we sequentially stain hydrodynamically trapped cells with three biochemical labels all sharing the same fluorescence excitation and emission spectrum. These markers allow us to analyze the amount of DNA, and compare nucleus-to-cytoplasm ratio, as well as glycosylation of surface proteins. By imaging cells in real-time we enable measurements of temporal localization of cellular components and intracellular reaction kinetics, the latter is used as a measurement of multi-drug resistance. Demonstrating the efficacy of this single-cell analysis platform is the first step in designing and implementing more complete assays, aimed toward improving diagnosis and personalized treatments to complex diseases

Dynamic Epitope Expression from Static Cytometry Data: Principles and Reproducibility

Background: An imprecise quantitative sense for the oscillating levels of proteins and their modifications, interactions, and translocations as a function of the cell cycle is fundamentally important for a cartoon/narrative understanding for how the cell cycle works. Mathematical modeling of the same cartoon/narrative models would be greatly enhanced by an openended methodology providing precise quantification of many proteins and their modifications, etc. Here we present methodology that fulfills these features. Methodology: Multiparametric flow cytometry was performed on Molt4 cells to measure cyclins A2 and B1, phospho-S10histone H3, DNA content, and light scatter (cell size). The resulting 5 dimensional data were analyzed as a series of bivariate plots to isolate the data as segments of an N-dimensional ‘‘worm’ ’ through the data space. Sequential, unidirectional regions of the data were used to assemble expression profiles for each parameter as a function of cell frequency. Results: Analysis of synthesized data in which the true values where known validated the approach. Triplicate experiments demonstrated exceptional reproducibility. Comparison of three triplicate experiments stained by two methods (single cyclin or dual cyclin measurements with common DNA and phospho-histone H3 measurements) supported the feasibility of combining an unlimited number of epitopes through this methodology. The sequential degradations of cyclin A2 followed by cyclin B1 followed by de-phosphorylation of histone H3 were precisely mapped. Finally, a two phase expression rat

MHC-based detection of antigen-specific CD8+ T cell responses

The hallmark of adaptive immunity is its ability to recognise a wide range of antigens and technologies that capture this diversity are therefore of substantial interest. New methods have recently been developed that allow the parallel analysis of T cell reactivity against vast numbers of different epitopes in limited biological material. These technologies are based on the joint binding of differentially labelled MHC multimers on the T cell surface, thereby providing each antigen-specific T cell population with a unique multicolour code. This strategy of ‘combinatorial encoding’ enables detection of many (at least 25) different T cell populations per sample and should be of broad value for both T cell epitope identification and immunomonitoring

Modeling flow cytometry data for cancer vaccine immune monitoring

Flow cytometry (FCM) is widely used in cancer research for diagnosis, detection of minimal residual disease, as well as immune monitoring and profiling following immunotherapy. In all these applications, the challenge is to detect extremely rare cell subsets while avoiding spurious positive events. To achieve this objective, it helps to be able to analyze FCM data using multiple markers simultaneously, since the additional information provided often helps to minimize the number of false positive and false negative events, hence increasing both sensitivity and specificity. However, with manual gating, at most two markers can be examined in a single dot plot, and a sequential strategy is often used. As the sequential strategy discards events that fall outside preceding gates at each stage, the effectiveness of the strategy is difficult to evaluate without laborious and painstaking back-gating. Model-based analysis is a promising computational technique that works using information from all marker dimensions simultaneously, and offers an alternative approach to flow analysis that can usefully complement manual gating in the design of optimal gating strategies. Results from model-based analysis will be illustrated with examples from FCM assays commonly used in cancer immunotherapy laboratories