CyTOF: We have mass appeal. The technology backed by 1,000+ publications.

CyTOF® is the only high-parameter single-cell analysis system vetted by more than 1,000 publications. Covering a wide spectrum of diseases and research applications, this collection of studies demonstrates the versatility and proven performance of mass cytometry for translational and clinical research around the world.

Explore the publications by research area using the links to the right.

Bibliography

Browse our complete catalog of over 1,000 CyTOF related publications to see how Helios™ and mass cytometry empower researchers to make breakthrough discoveries in basic, translational and clinical research. Download Now

Mass Cytometry Publications Trending Now

Take a look at the issues of Mass Cytometry Publications Trending Now, a quarterly anthology series covering the most recent and impactful publications that help expand our understanding of human health and disease

• Overview

  Number of papers per research area as of August, 2021

  Number of cumulative papers as of August, 2021

• Recent

  • Two subsets of stem-like CD8 + memory T cell progenitors with distinct fate commitments in humans
    Galletti, G., Simone, G.D., Mazza, E.M.C. Nature Immunology (2020): doi: 10.1038/s41590-020-0791-5
  • Th17-inducing autologous dendritic cell vaccination promotes antigen-specific cellular and humoral immunity in ovarian cancer patients
    Block, M. S., Dietz, A.B., Gustafson, M.P. Nature Communications (2020): doi.org/10.1038/s41467-020-18962-z
  • Glioma stem-like cells can be targeted in boron neutron capture therapy with boronophenylalanine
    Kondo, N., Hikida, M., Nakada , M. Cancers (2020): doi.org/10.3390/cancers12103040
  • Application of an activity-based probe to determine proteolytic activity of cell surface cathepsin G by mass cytometry data acquisition
    Gärtner, F., Knippschild, U., Burster, T. ACS Omega (2020): doi.org/10.1021/acsomega.0c04092
  • Salmonella enterica serovar Typhi exposure elicits ex vivo cell-type-specific epigenetic changes in human gut cells
    Sztein, M.B., Bafford, A.C., Salerno-Goncalves, R. Scientific Reports (2020): doi.org/10.1101/cshperspect.a029546
  • Agile workflow for interactive analysis of mass cytometry data
    Casado, J., Lehtonen, O., Rantanen, V. Bioinformatics (2020): DOI: 10.1093/bioinformatics/btaa946

• Research Areas

  • Biomarker Screening

    • Single-cell peripheral immunoprofiling of Alzheimer’s and Parkinson’s diseases
      Phongpreecha, T., Fernandez, R., Mrdjen, D. Science Advances (2020): DOI: 10.1126/sciadv.abd5575
    • CD8+T-bet+ cells as a predominant biomarker for inclusion body myositis
      Dzangué-Tchoupou, G., Mariampillai, K., Bolko, L. et al. Autoimmunity Reviews (2019): 325–33
    • A high-sensitivity lanthanide nanoparticle reporter for mass cytometry: tests on microgels as a proxy for cells
      Lin, W., Hou, Y., Lu, Y. et al. Langmuir (2014): 3,142–53
    • Mass cytometry identifies distinct lung CD4+ T cell patterns in Löfgren’s syndrome and non-Löfgren’s syndrome sarcoidosis
      Kaiser, Y., Lakshmikanth, T., Chen, Y., et al. Frontiers in Immunology (2017): 1,130
    • High dimensional immune biomarkers demonstrate differences in phenotypes and endotypes in food allergy and asthma
      Chinthrajah, R.S., Purington, N., Sampath, V. et al. Annals of Allergy, Asthma, and Immunology (2018): 117–9.e1
    • A frameshift in CSF2RB predominant among Ashkenazi Jews increases risk for Crohn's disease and reduces monocyte signaling via GM-CSF
      Chuang, L.S., Villaverde, N., Hui, K.Y. et al. Gastroenterology (2016): 710–723.e2
    • Distinct predictive biomarker candidates for response to anti-CTLA-4 and anti-PD-1 immunotherapy in melanoma patients
      Subrahmanyam, P.B., Dong, Z., Gusenleitner, D. et al. Journal for ImmunoTherapy of Cancer (2018): 18
    • A time to amaze, a time to settle down, and a time to discover
      Cosma, A. Cytometry Part A (2015): 795–6
    • Immune cell profiling to guide therapeutic decisions in rheumatic diseases
      Ermann, J., Rao, D.A., Teslovich, N.C. et al. Nature Reviews Rheumatology (2015): 541–51
    • Signaling effects of sodium hydrosulfide in healthy donor peripheral blood mononuclear cells
      Sulen, A., Gullaksen, S.E., Bader, L. et al. Pharmacological Research (2016): 216–27

  • Data Analysis Methods

    • Prediction of functional markers of mass cytometry data via deep learning
      Solís-Lemus, C., Ma, X., HostetterII, M. et al. Statistical Modeling in Biomedical Research (2020): 95-104
    • Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets
      Trussart, M., Teh, C. E., Tan, T. et al. eLife (2020): doi.org/10.1038/s41591-018-0243-z
    • Visual cohort comparison for spatial single-cell omics-data
      Somarakis, A., Ijsselsteijn, M. E., Luk, S. J. et al. IEEE Transactions on Visualization and Computer Graphics (2020): 1-1
    • GigaSOM.jl: High-performance clustering and visualization of huge cytometry datasets
      Kratochv´ıl, M., Hunewald, O., Heirendt, L. GigaScience (2020): DOI: 10.1093/gigascience/giaa127
    • PARC: ultrafast and accurate clustering of phenotypic data of millions of single cells
      Moonsamy, P.V., Williams, T., Bonella, P. et al. Bioinformatics (2021): 2778–2786
    • SwiftReg cluster registration automatically reduces flow cytometry data variability including batch effects.
      Rebhahn, J.A., Quataert, S.A., Sharma, G. Communications Biology (2021): doi.org/10.5281/zenodo.3733491
    • Brick plots: an intuitive platform for visualizing multiparametric immunophenotyped cell clusters
      Norton, S.E., Leman, J. K. H., Khong, T. BMC Bioinformatics (2021): doi.org/10.1186/s12859-020-3469-y
    • The Extended Polydimensional Immunome Characterization (EPIC) web-based reference and discovery tool for cytometry data
      Yeo, J.G., Wasser, M., Albani, S. Nature Biotechnology (2020): 679–684
    • Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions
      Culos, A., Tsai, A. S., Aghaeepour, N. Nature Machine Intelligence (2020): 619–628
    • Uncovering the key dimensions of high-throughput biomolecular data using deep learning
      Zhang, S., Li, X., Lin, Q. Nucleic Acid Research (2020): 56
    • Learning pathway dynamics from single‐cell proteomic data: a comparative study
      Verrou, K.M., Tsamardinos, L., Papoutsoglou, G. Cytometry Part A (2020): doi.org/10.1002/cyto.a.23976
    • VoPo leverages cellular heterogeneity for predictive modeling of single-cell data
      Stanley, N., Stelzer, I.A., Aghaeepour, N. Nature Communications (2020): doi.org/10.1182/bloodadvances.2020001565
    • Visualizing Structure and Transitions for Biological Data Exploration
      Moon, K.R., van Dijk, D., Wang, Z. et al. Cell (2018): 1,482–92
    • HiPPO and PANDA: Two bioinformatics tools to support analysis of mass cytometry data
      Pirrò, S., Spada, F., Gadaleta, E. et al. Journal of Computational Biology (2019): 1,283–94
    • High‐dimensional data analysis algorithms yield comparable results for mass cytometry and spectral flow cytometry data
      Ferrer-Font, L., Mayer, J.U., Old, S. Cytometry Part A (2020): 824–31
    • Uncovering axes of variation among single-cell cancer specimens
      Chen, W.S., Zivanovic, N., van Dijk, D. et al. Nature Methods (2020): 302–10
    • FLOW-MAP: a graph-based, force-directed layout algorithm for trajectory mapping in single-cell time course datasets
      Ko, M.E., Williams, C.M., Fread, K.I. et al. Nature Protocols (2020): 398-420.
    • Stabilized reconstruction of signaling networks from single-cell cue-response data
      Kumar, S., Lun, X-K., Bodenmiller, B. et al. Scientific Reports (2020): 1233
    • Structure-preserving visualisation of high dimensional single-cell datasets
      Szubert, B., Cole, J.E., Monaco, C. et al. Scientific Reports (2019): 8914
    • Cell cycle analysis and relevance for single-cell gating in mass cytometry
      Rein, I.D., Notø, H. Ø., Bostad, M. et al. Cytometry Part A (2020): DOI: 10.1002/cyto.a.23926
    • CytoFA: Automated gating of mass cytometry data via robust skew factor analyzers
      Lee, S.X. Advances in Knowledge Discovery and Data Mining. Lecture Notes in Computer Science (2019): 514–25
    • Learning single‐cell distances from cytometry data
      Nguyen, B., Rubbens, P., Kerckhof, F.M. et al. Cytometry Part A (2019): 782–91
    • Visualizing structure and transitions in high-dimensional biological data
      Moon, K.R., van Dijk, D., Wang, Z. et al. Nature Biotechnology (2019): 1,482–92
    • Computational analysis of high-dimensional mass cytometry data from clinical tissue samples
      Norton, S. and Kemp, R. Mass Cytometry: Methods and Protocols (2019): 295–307
    • Exploring single-cell data with deep multitasking neural networks
      Amodio, M., van Dijk, D., Srinivasan, K., et al. Nature Methods (2019): 1,139–45
    • Analysis of high-dimensional phenotype data generated by mass cytometry or high-dimensional flow cytometry
      Cirovic, B., Katzmarski, N., and Schlitzer, A. Mass Cytometry: Methods and Protocols (2019): 281–94
    • SCENERY: a web application for (causal) network reconstruction from cytometry data
      Papoutsoglou, G., Athineou G., Lagani, V. et al. Nucleic Acids Research (2017): W270–W275
    • Automated data cleanup for mass cytometry
      Bagwell, C.B., Inokuma, M., Hunsberger, B., et al. Cytometry Part A (2019): 184–198
    • Modeling cell-cell interactions from spatial molecular data with spatial variance component analysis
      Arnol, D., Schapiro, D., Bodenmiller, B. et al. Cell Reports (2019): P202–211.E6
    • Visualization and quantification of high-dimensional cytometry data using Cytofast and the upstream clustering methods FlowSOM and Cytosplore
      Beyrend, G., Stam, K., Ossendorp, F. et al. Journal of Visual Experiments (2019): DOI: 10.3791/60525
    • A comparison framework and guideline of clustering methods for mass cytometry data
      Liu, X., Song, W., Wong, B.Y., et al. Genome Biology (2019): 297
    • Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets
      Belkina, A.C., Ciccolella, C.O., Anno, R., et al. Nature Communications (2019): 5415
    • Challenges in the multivariate analysis of mass cytometry data: The effect of randomization
      Papoutsoglou, G., Lagani, V., Schmidt, A., et al. Cytometry Part A (2019): DOI: 10.1002/cyto.a.23908
    • Acquisition, processing, and quality control of mass cytometry data
      Lee, B.H. and Rahman, A.H. Mass Cytometry: Methods and Protocols (2019): 13–31
    • Supervised machine learning with CITRUS for single cell biomarker discovery
      Polikowsky, H.G. and Drake, K.A. Mass Cytometry: Methods and Protocols (2019): 309–32
    • Analysis of mass cytometry data
      Pederson, C.B. and Olsen, L.R. Mass Cytometry: Methods and Protocols (2019): 267–79
    • Automated cell type discovery and classification through knowledge transfer
      Lee, H.C., Kosoy, R., Becker, C.E. et al. Bioinformatics (2017): 1,689–95
    • CytoNorm: A normalization algorithm for cytometry data
      Van Gas, S., Gaudilliere, B., Angst , M.S. et al. Cytometry Part A (2019): doi: 10.1002/cyto.a.23904
    • Minimizing Batch Effects in Mass Cytometry Data
      Schuyler, R.P., Jackson, C., Garcia-Perez, J.E. et al. Frontiers in Immunology (2019): doi: 10.3389/fimmu.2019.02367
    • Predicting cell populations in single cell mass cytometry data
      Abdelaal, T., van Unen, V., Höllt T. et al. Cytometry Part A (2019): 769–81
    • Computational approaches for characterizing the tumor immune microenvironment
      Liu, C.C., Steen, C.B., and Newman, A.M. Immunology (2019): 70–84
    • SCINA: A semi-supervised subtyping algorithm of single cells and bulk samples
      Zhang, Z., Luo, D., Zhong, X. et al. Genes (2019): 531
    • A novel, five-marker alternative to CD16-CD14 gating to identify the three human monocyte subsets
      Ong, S.M., Teng, K., Newell, E. et al. Frontiers in Immunology (2019): 1,761
    • Methods for analyzing tellurium Imaging Mass Cytometry data
      Bassan, J. and Nitz, M. PLoS One (2019): e0221714
    • VOLARE: visual analysis of disease-associated microbiome-immune system interplay
      Siebert, J.C., Preston Neff, C., Schneider, J.M. et al. BMC Bioinformatics (2019): 432
    • Improving the t-SNE algorithms for cytometry and other technologies: Cen-Se′ mapping
      Bagwell, C.B., Bray, C.M., Herbert, D.J. et al. Journal of Biometrics & Biostatistics (2019): 430
    • diffcyt: Differential discovery in high-dimensional cytometry via high-resolution clustering
      Weber, L.M., Nowicka, M., Soneson, C. et al. Communications Biology (2019): 183
    • ImaCytE: Visual exploration of cellular microenvironments for Imaging Mass Cytometry data
      Somarakis, A., van Unen, V., Koning, F. et al. IEEE Transactions on Visualization and Computer Graphics (2019): doi: 10.1109/TVCG.2019.2931299.
    • Advanced imaging technology applications in cytology
      Pantanowitz, L., Preffer, F., Wilbur, D.C. Nature Communications (2018): 5–14
    • Mass synaptometry: High-dimensional multi parametric assay for single synapses
      Gajera, C.R., Fernandez, R., Postupna, N. et al. Journal of Neuroscience Methods (2018): 73–83
    • histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data
      Schapiro, D., Jackson, H.W., Raghuraman, S. et al. Nature Methods (2017): 873–6
    • Clustergrammer, a web-based heatmap visualization and analysis tool for high-dimensional biological data
      Fernandez, N.F., Gundersen, G.W., Rahman, A. et al. Scientific Data (2017): 170151
    • CytoBinning: immunological insights from multi-dimensional data
      Shen, Y., Chaigne-Delalande, B., Lee, R.W.J. et al. PLoS One (2018): e0205291
    • Compensation of signal spillover in suspension and Imaging Mass Cytometry
      Chevrier, S., Crowell, H.L., Zanotelli, V.R.T. et al. Cell Systems (2018): 612–20
    • Automated subset identification and characterization pipeline for multidimensional flow and mass cytometry data clustering and visualization
      Meehan, S., Kolyagin, G.A., Parks, D. et al. Nature Communications Biology (2019): 229
    • Quantitative comparison of conventional and t-SNE-guided gating analyses treatment in cynomolgus monkeys
      Eshgi, S.T., Au-Yeung, A., Takahashi, C. et al. Frontiers in Immunology (2019): 1,194
    • Development of a comprehensive antibody staining database using a standardized analytics pipeline
      Amir, E.D., Lee, B., Badoual, P. et al. Frontiers in Immunology (2019): 1,315
    • CyTOFmerge: Integrating mass cytometry data across multiple panels
      Abdelaal, T., Höllt T., van Unen, V. et al. Bioinformatics (2019): btz180
    • Robust prediction of clinical outcomes using cytometry data
      Hu, Z., Glicksberg, B.S., Butte, A.J. Bioinformatics (2018): 1,197–203
    • ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
      Sidhom, J.W., Theodros, D., Murter, B. et al. Journal of Visualized Experiments (2019): doi: 10.3791/57473.
    • CytoBackBone: an algorithm for merging of phenotypic information from different cytometric profiles
      Pereira, A.L., Lambotte, O., Le Grand, R. et al. Bioinformatics (2019): btz212
    • High throughput automated analysis of big flow cytometry data
      Rahim, A., Meskas, J., Drissler, S. et al. Methods (2018): 164–76
    • GateFinder: projection-based strategy optimization for flow and mass cytometry.
      Aghaeepour, N., Simonds, E.F., Knapp D.J.H.F. et al. Bioinformatics (2018): 4,131–3
    • QFMatch: multidimensional flow and mass cytometry samples alignment
      Orlova, D.Y., Meehan, S., Parks D. et al. Scientific Reports (2018): 3,291
    • Cytosplore: interactive immune cell phenotyping for large single-cell datasets
      Höllt, T., Pezzotti, N., van Unen, V. et al. Computer Graphics Forum (2016): 171–80
    • A roadmap towards personalized immunology
      Delhalle, S., Bode, S.F.N., Balling, R. et al. Systems Biology and Applications (2018): 9
    • Cytofast: A workflow for visual and quantitative analysis of flow and mass cytometry data to discover immune signatures and correlations
      Beyrend, G., Stam, K., Höllt, T. et al. Computational and Structural Biotechnology Journal (2018): 435–42
    • Dimensionality reduction for visualizing single-cell data using UMAP
      Becht, E., McInnes, L., Healy, J. et al. Nature Biotechnology (2018): 38–44
    • Single-cell epigenetics - Chromatin modification atlas unveiled by mass cytometry
      Cheung, P., Vallania, F., Dvorak, M. et al. Clinical Immunology (2018): 40–8
    • MetaCyto: A Tool for Automated Meta-analysis of Mass and Flow Cytometry Data
      Hu, Z., Jujjavarapu, C., Hughey, J.J. et al. Cell Reports (2018): 1,377–88
    • Unsupervised trajectory analysis of single-cell RNA-seq and imaging data reveals alternate tuft cell origins in the gut
      Pollyea, D.A., Stevens, B.M., Jones, C.L. et al. Cell Systems (2018): 37–51
    • CytoML for cross-platform cytometry data sharing
      Finak, G., Jiang, W., Gottardo, R. Cytometry Part A: Journal of the ISAC (2018): 1,189–96
    • Removal of batch effects using distribution-matching residual networks
      Shaham, U., Stanton, K.P., Zhao, J. et al. Bioinformatics (2017): 2,539–46
    • Mixed-effects association of single cells identifies an expanded effector CD4+ T cell subset in rheumatoid arthritis
      Fonseka, C.Y., Rao, D.A., Teslovich, N.C. et al. Science Translational Medicine (2018): eaaq0305
    • Sensitive detection of rare disease-associated cell subsets via representation learning
      Arvaniti, E., Claassen, M. Nature Communications (2017): doi: 10.1007/s12094-018-02004-8
    • Multiparametric analysis of colorectal cancer immune responses
      Leman, J.K.H., Sandford, S.K., Rhodes, J.L. et al. World Journal of Gastroenterology (2018): 2,995-3,005
    • Learning time-varying information flow from single-cell epithelial to mesenchymal transition data
      Krishnaswamy, S., Zivanovic, N., Sharma, R. et al. PLoS One (2018): e0203389
    • Continuous Immune Cell Differentiation Inferred From Single-Cell Measurements Following Allogeneic Stem Cell Transplantation
      Chen, Y., Lakshmikanth, T., Olin, A. et al. Frontiers in Molecular Biosciences (2018): 81
    • Average Overlap Frequency: a simple metric to evaluate staining quality and community identification in high dimensional mass cytometry experiments
      Amir, E.D., Guo, X.V., Mayovska, O. et al. Journal of Immunological Methods (2018): 20–29
    • Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE
      Qiu, P., Simonds, E.F., Bendall, S.C. et al. Nature Biotechnology (2011): 886–91
    • Bayesian hierarchical models for protein networks in single-cell mass cytometry
      Mitra, R., Müller, P., Qiu, P. et al. Cancer Informatics (2014): 79–89
    • Cytofkit: a bioconductor package for an integrated mass cytometry data analysis pipeline
      Chen, H., Lau, M.C., Wong, M.T. et al. PLoS Computational Biology (2016): e1005112
    • ImmPort, toward repurposing of open access immunological assay data for translational and clinical research
      Bhattacharya, S., Dunn, P., Thomas, C.G. et al. Scientific Data (2018): 180,015
    • Alternatives to current flow cytometry data analysis for clinical and research studies
      Gondhalekar, C., Rajwa, B., Patsekin, V. et al. Methods (2018): 113–29
    • Generating quantitative cell identity labels with marker enrichment modeling (MEM)
      Diggins, K.E., Gandelman, J.S., Roe, C.E. et al. Current Protocols in Cytometry (2018): 10.21.1–28
    • CellCycleTRACER accounts for cell cycle and volume in mass cytometry data
      Rapsomaniki, M.A., Lun, X.K., Woerner, S. et al. Nature Communications (2018): 632
    • Comparison of clustering methods for high-dimensional single-cell flow and mass cytometry data
      Weber, L.M., Robinson, M.D. Cytometry Part A (2016): 1,084–96
    • Gating mass cytometry data by deep learning
      Li, H., Shaham, U., Stanton, K.P. et al. Bioinformatics (2017): 3,423–30
    • Scalable multi-sample single-cell data analysis by Partition-Assisted Clustering and Multiple Alignments of Networks
      Li, Y.H., Li, D., Samusik, N. et al. PLoS Computational Biology (2017): e1005875
    • A computational approach for phenotypic comparisons of cell populations in high-dimensional cytometry data
      Platon, L., Pejoski, D., Gautreau, G. et al. Methods (2017): 66–75
    • Automated identification of stratifying signatures in cellular subpopulations
      Bruggner, R.V., Bodenmiller, B., Dill, D.L. et al. Proceedings of the National Academy of Sciences of the United States of America (2014): E2770–E2777
    • OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis
      Finak, G., Frelinger, J., Jiang, W. et al. PLoS Computational Biology (2014): e1003806
    • Conditional density-based analysis of T cell signaling in single-cell data
      Krishnaswamy, S., Spitzer, M.H., Mingueneau, M. et al. Science (2014): 1,250,689
    • Unsupervised trajectory analysis of single-cell RNA-seq and imaging data reveals alternative tuft cell origins in the gut
      Herring, C.A., Banerjee, A., McKinley, E.T. et al. Cell Systems (2018): 37–51.e9
    • Visual analysis of mass cytometry data by hierarchical stochastic neighbour embedding reveals rare cell types
      Van Unen, V., Höllt, T., Pezzotti, N. et al. Nature Communications (2017): 1,740
    • CyteGuide: visual guidance for hierarchical single-cell analysis
      Holt, T., Pezzotti, N., van Unen, V. et al. IEEE Transactions on Visualization and Computer Graphics (2018): 739–48
    • A beginner's guide to analyzing and visualizing mass cytometry data
      Kimball, A.K., Oko, L.M., Bullock, B.L. et al. Journal of Immunology (2018): 3–22
    • Integrated inference and analysis of regulatory networks from multi-level measurements
      Poultney, C.S., Greenfield, A., Bonneau, R. Methods in Cell Biology (2012): 19–56
    • RchyOptimyx: cellular hierarchy optimization for flow cytometry
      Aghaeepour, N., Jalali, A., O'Neill, K. et al. Cytometry, Part A (2012): 1,022–30
    • Automatic Classification of Cellular Expression by Nonlinear Stochastic Embedding (ACCENSE)
      Shekhar, K., Brodin, P., Davis, M.M. et al. Proceedings of the National Academy of Sciences (2014): 202–7
    • Enhanced flowType/RchyOptimyx: a BioConductor pipeline for discovery in high-dimensional cytometry data
      O'Neill, K., Jalali, A., Aghaeepour, N. et al. Bioinformatics (2014): 1,329–30
    • FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data
      Van Gassen, S., Callebaut, B., Van Helden, M.J. et al. Cytometry Part A (2015): 636–45
    • An Interactive Reference Framework for Modeling a Dynamic Immune System
      Spitzer, M.H., Gherardini, P.F., Fragiadakis, G.K. et al. Science (2015): 1,259,425
    • immunoClust—An automated analysis pipeline for the identification of immunophenotypic signatures in high-dimensional cytometric datasets
      Sörensen, T., Baumgart, S., Durek, P. et al. Cytometry, Part A (2015): 603–15
    • NetworkPainter: dynamic intracellular pathway animation in Cytobank
      Karr, J.K., Guturu, H., Chen, E.Y. et al. BMC Bioinformatics (2015): 172
    • Computationally efficient multidimensional analysis of complex flow cytometry data using second order polynomial histograms
      Zaunders, J., Jing, J., Leipold, M. et al. Cytometry, Part A (2015): 44–58
    • Processing, visualising and reconstructing network models from single-cell data
      Woodhouse, S., Moignard, V., Göttgens, B., Fisher, J. Immunology and Cell Biology (2015): 256–65
    • Wishbone identifies bifurcating developmental trajectories from single-cell data
      Setty, M., Tadmor, M.D., Reich-Zeliger, S. et al. Nature Biotechnology (2016): 637–45
    • Automated mapping of phenotype space with single-cell data
      Samusik, N., Good, Z., Spitzer, M.H. et al. Nature Methods (2016): 493–6
    • Computational flow cytometry: helping to make sense of high-dimensional immunology data
      Saeys, Y., Gassen, S.V., Lambrecht, B.N. Nature Reviews Immunology (2016): 449–62
    • The end of gating? An introduction to automated analysis of high dimensional cytometry data
      Mair, F., Hartmann, F.J., Mrdjen et al. European Journal of Immunology (2015): 34–43
    • Mapping the effects of drugs on the immune system
      Kidd, B.A., Wroblewska, A., Boland, M.R. et al. Nature Biotechnology (2015): 47–54
    • densityCut: an efficient and versatile topological approach for automatic clustering of biological data
      Ding, J., Shah, S., Condon, A. Bioinformatics (2016): 2,567–76
    • Categorical Analysis of Human T Cell Heterogeneity with One-Dimensional Soli-Expression by Nonlinear Stochastic Embedding
      Cheng, Y., Wong, M.T., van der Maaten, L., Newell, E.W. Journal of Immunology (2016): 924–32
    • AirLab: a cloud-based platform to manage and share antibody-based single-cell research
      Catena, R., Özcan, A., Jacobs, A. et al. Genome Biology (2016): 142
    • destiny: diffusion maps for large-scale single-cell data in R
      Angerer, P., Haghverdi, L., Büttner, M. et al. Bioinformatics (2016): 1,241–3
    • Visualization and cellular hierarchy inference of single-cell data using SPADE
      Anchang, B., Hart, T.D., Bendall, S.C. et al. Nature Protocols (2016): 1,264–79
    • Predicting Causal Relationships from Biological Data: Applying Automated Causal Discovery on Mass Cytometry Data of Human Immune Cells
      Triantafillou, S., Lagani, V., Heinze-Deml, C. et al. Scientific Reports (2017): 12,724
    • Toward deterministic and semiautomated SPADE analysis
      Qiu, P. Cytometry Part A (2017): 281–9
    • CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets
      Nowicka, M., Krieg, C., Weber, L.M. et al. F1000 Research (2017): 748
    • Cluster stability in the analysis of mass cytometry data
      Melchiotti, R., Gracio, F., Kordasti, S. et al. Cytometry Part A (2017): 73–84
    • Testing for differential abundance in mass cytometry data
      Lun, A.T.L., Richard, A.C., Marioni, J.C. Nature Methods (2017): 707–9
    • SPADEVizR: an R package for visualization, analysis and integration of SPADE results
      Gautreau, G., Pejoski, D., Le Grand, R. et al. Bioinformatics (2017): 779–81
    • Characterizing cell subsets in heterogeneous tissues using marker enrichment modeling
      Diggins, K.E., Greenplate, A.R., Leelatian, N. et al. Nature Methods (2017): 275-8
    • Exploring Glucocorticoid Receptor Agonists Mechanism of Action through Mass Cytometry and Radial Visualizations
      Abraham, Y., Gerrits, B., Ludwig, M.G. et al. Cytometry Part B Clinical Cytometry (2016): 42–56

  • Immuno-oncology

    • Skin dendritic cells in melanoma are key for successful checkpoint blockade therapy
      Prokopi, A., Tripp, C. H., Tummers, B. Journal for ImmunoTherapy of Cancer (2021): doi: 10.1136/jitc-2020-000832
    • Phase 1 trial of N-803, an IL-15 receptor agonist, with rituximab in patients with indolent non-Hodgkin lymphoma
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    • Clinical response to PD-1 blockade correlates with a sub-fraction of peripheral central memory CD4+ T cells in patients with malignant melanoma
      Takeuchi, Y., Tanemura, A., Tada, Y. et al. International Immunology (2018): 13–22
    • High-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy
      Krieg, C., Nowicka, M., Guglietta, S. et al. Nature Medicine (2018): 144–53
    • Comprehensive immunoproteogenomic analyses of malignant pleural mesothelioma
      Lee, H.S., Jang, H.J., Choi, J.M. et al. Journal of Clinical Investigation Insight (2018): e98575
    • Bystander CD8+ T cells are abundant and phenotypically distinct in human tumour infiltrates
      Simoni, Y., Becht, E., Fehlings, M. et al. Nature (2018): 575–9
    • Epigenomic-Guided Mass Cytometry Profiling Reveals Disease-Specific Features of Exhausted CD8 T Cells
      Bengsch, B., Ohtani, T., Khan, O. et al. Immunity (2018): 1,029–45
    • Commonly occurring cell subsets in high-grade serous ovarian tumors identified by single-cell mass cytometry
      Gonzalez, V.D., Samusik, N., Chen, T.J. et al. Cell Reports (2018): 1,875–88
    • Technology to watch in 2018: boosting cancer vaccines
      Mardis, E. Nature (2018): 532
    • Immunotherapy-induced sarcoidosis in patients with melanoma treated with PD-1 checkpoint inhibitors: Case series and immunophenotypic analysis
      Lomax, A.J., McGuire, H.M., McNeil, C. et al. International Journal of Rheumatic Diseases (2017): 1,277–85
    • Delineation of an immunosuppressive gradient in hepatocellular carcinoma using high-dimensional proteomic and transcriptomic analyses
      Chew, V., Lai, L., Pan, L. et al. Proceedings of the National Academy of Sciences of the United States of America (2017): E5900–9
    • T-cell invigoration to tumour burden ratio associated with anti-PD-1 response
      Huang, A.C., Postow, M.A., Orlowski, R.J. et al. Nature (2017): 60–5
    • Mitochondrial dysregulation and glycolytic insufficiency functionally impair CD8 T cells infiltrating human renal cell carcinoma
      Siska, P.J., Beckerman, K.E., Mason, F.M. et al. JCI Insight (2017): e93411
    • VISTA is an inhibitory immune checkpoint that is increased after ipilimumab therapy in patients with prostate cancer
      Gao, J., Ward, J.F., Pettaway, C.A. et al. Nature Medicine (2017): 551–5
    • Natural Killer Defective Maturation Is Associated with Adverse Clinical Outcome in Patients with Acute Myeloid Leukemia
      Chretien, A.S., Fauriat, C., Orlanducci, F. et al. Frontiers in Immunology (2017): 573
    • An immune atlas of clear cell renal cell carcinoma
      Chevrier, S., Levine, J.H., Zanotelli, V.R.T. et al. Cell (2017): 736–49
    • Systems immune monitoring in cancer therapy
      Greenplate, A.R., Johnson, D.B., Ferrell, P.B. Jr., Irish, J.M. European Journal of Cancer (2016): 77–84
    • Combined targeting of BCL-2 and BCR-ABL tyrosine kinase eradicates chronic myeloid leukemia stem cells
      Carter, B.Z., Mak, P.Y., Mu, H. et al. Science Translational Medicine (2016): 355ra117

  • Immunology

    • Single-cell analysis by mass cytometry reveals metabolic states of early-activated CD8+ T cells during the primary immune response
      Levine, L.S., Hiam-Galvez, K.J., Marquez, D.M. Immunity (2021): doi.org/10.1016/j.immuni.2021.02.018
    • Identification of human immune cell subtypes most responsive to IL-1β–induced inflammatory signaling using mass cytometry
      Kothari, H., Williams, C.M., McSkimming, C. Science Signaling (2021): DOI: 10.1126/scisignal.abc5763
    • Profiling cellular heterogeneity in asthma with single cell multiparameter CyTOF
      Stewart, E., Wang, X., Chupp, G. L. et al. Journal of Leukocyte Biology (2020): DOI: 10.1002/JLB.5MA0720-770RR
    • Deep phenotyping by mass cytometry and single cell RNA-sequencing reveals LYN regulated signaling profiles underlying monocyte subset heterogeneity and lifespan
      Roberts, M.E., Barvalia, M., Silva, J. A. F. D. et al. Circulation Research (2020): DOI: 10.1161/CIRCRESAHA.119.315708
    • Integration of molecular profiles in a longitudinal wellness profiling cohort
      Tebani, A., Gummesson, A., Fagerberg, L. et al. Nature Communications (2020): doi.org/10.5878/rdys-mz27
    • Single-cell sequencing reveals clonal expansions of pro-inflammatory synovial CD8 T cells expressing tissue-homing receptors in psoriatic arthritis
      Penkava, F., Velasco-Herrera, M. D. C., Young, M. D. et al. Nature Communications (2020): doi.org/10.1038/nprot.2014.006
    • Reduced polyfunctional T cells and increased cellular activation markers in adult allergy patients reporting adverse reactions to food
      Sonnet, F., Namork, E., Stylianou, E.et al. BMC Immunology (2020): doi.org/10.1186/s12865-020-00373-w
    • Exhausted-like CD8 T cell phenotypes linked to C-peptide preservation in alefacept-treated T1D subjects
      Diggins, K.E., Serti, E., Muir, V. S. et al. JCI Insight (2020): doi.org/10.1172/jci.insight.142680
    • Delineation of a molecularly distinct terminally differentiated memory CD8 T cell population
      Milner, J.J., Nguyen, H., Omilusik, K. et al. Proceedings of the National Academy of Sciences of the United States of America (2020): DOI: 10.1073/pnas.2008571117
    • High-dimensional T helper cell profiling reveals a broad diversity of stably committed effector states and uncovers interlineage relationships
      Tortola, L., Jacobs, A., Pohlmeier , L. et al. Immunity (2020): DOI: 10.1016/j.immuni.2020.07.001
    • Notch controls urothelial integrity in the mouse bladder
      Paraskevopoulou, V., Bonis, V., Dionellis, V.S. JCI Insight (2020): e133232
    • Comprehensive profiling of an aging immune system reveals clonal GZMK+ CD8+ T cells as conserved hallmark of inflammaging
      Mogilenko, D.A., Shpynov, O., Andhey, P. S Immunity (2021): doi.org/10.1016/j.immuni.2020.11.005
    • Differential IRF8 transcription factor requirement defines two pathways of dendritic cell development in humans
      Cytlak, U., Resteu, A., Pagan, S. Immunity (2021): doi.org/10.1016/j.immuni.2020.07.003
    • Autoantibody-positive healthy individuals with lower lupus risk display a unique immune endotype
      Slight-Webb, S., Smith, M., Bylinska, A. Journal of Allergy and Clinical Immunology (2021): DOI: 10.1016/j.jaci.2020.04.047
    • IL-7 receptor alpha defines heterogeneity and signature of human effector memory CD8+ T cells in high dimensional analysis
      Shin, M.S., Kim, D., Yim, K. Cellular Immunology (2021): DOI: 10.1016/j.cellimm.2020.104155
    • Cutting edge: characterization of human tissue-resident memory T Cells at different infection sites in patients with tuberculosis
      Yamakawa, K., Tajima, G., Keegan, J. W. Journal of Leukocyte Biology (2020): DOI: 10.1002/JLB.4A0520-122R
    • Exploration of T-cell diversity using mass cytometry
      Kaitlin C O'Boyle, Takuya Ohtani, Sasikanth Manne Methods in Molecular Biology (2020): DOI: 10.1007/978-1-0716-0266-9_1
    • Stimulation of strength controls the rate of initiation but not the molecular organization of TCR-induced signalling
      Ma, C.Y., Marioni , J. C., Griffiths , G. M. eLife (2020): doi.org/10.3389/fimmu.2018.00713
    • Chromatin landscape underpinning human dendritic cell heterogeneity
      Leylek, R., Alcántara-Hernández, M., Granja, J. M. Cell Reports (2020): DOI: 10.1016/j.celrep.2020.108180
    • Single-cell metabolic profiling of human cytotoxic T cells
      Hartmann, F.J., Mrdjen, D., McCaffrey, E. Nature Biotechnology (2020): doi.org/10.5281/zenodo.3951613.
    • Mass Cytometry phenotyping of human granulocytes reveals novel basophil functional heterogeneity
      Vivanco Gonzalez, N., Oliveria, j. P., Tebaykin, D. iScience (2020): doi.org/10.1016/j.isci.2020.101724
    • Meningeal γδ T cells regulate anxiety-like behavior via IL-17a signaling in neurons
      Alves de Lima, K., Rustenhoven , J., Mesquita, S.D. Nature Immunology (2020): DOI: 10.1038/s41590-020-0776-4
    • Two subsets of stem-like CD8 + memory T cell progenitors with distinct fate commitments in humans
      Galletti, G., Simone, G.D., Mazza, E.M.C. Nature Immunology (2020): doi: 10.1038/s41590-020-0791-5
    • Human immune system variation during 1 Year
      Lakshmikanth, T., Muhammad, S.A., Olin, A. Cell Reports (2020): doi.org/10.1016/j.celrep.2020.107923
    • Fetal–derived macrophages persist and sequentially maturate in ovaries after birth in mice
      Jokela, H., Lokka, E., Kiviranta, M. European Journal of Immunology (2020): DOI: 10.1002/eji.202048531
    • TGF-β and IL-15 synergize through MAPK pathways to drive the conversion of human NK cells to an innate lymphoid cell 1-like phenotype
      Hawke, L.G., Mitchell, B.Z., Ormiston, M.L. Journal of Immunology (2020): DOI: 10.4049/jimmunol.1900866
    • Preferential inhibition of adaptive immune system dynamics by glucocorticoids in patients after acute surgical trauma
      Ganio, E.A., Stanley, N., Einhaus, J. Nature Communications (2020): doi.org/10.3390/cancers11050613
    • Coexpression of CD71 and CD117 identifies an early unipotent neutrophil progenitor population in human bone marrow
      Dinh, H.Q., Eggert, T., Meyer, M.A. Immunity (2020): DOI: 10.1016/j.immuni.2020.07.017
    • Long-term robustness of a T-cell system emerging from somatic rescue of a genetic block in T-cell development
      Kury, P., Fuhrer, M., Fuchs, S. EBioMedicine (2020): doi.org/10.1016/j.ebiom.2020.102961
    • The time-dependent shift in the hepatic graft and recipient macrophage pool following liver transplantation
      Huang, H., Zhang, X., Zhang, C. et al. Cellular & Molecular Immunology (2019): 412–14
    • Activation of the TLR signaling pathway in CD8+ T cells counteracts liver endothelial cell-induced T cell tolerance
      Zhang, E., Yan, H., Li, Q. et al. Cellular & Molecular Immunology (2019): 774–6
    • Negative Co-stimulation Constrains T Cell Differentiation by Imposing Boundaries on Possible Cell States
      Wei, S.C., Sharma, R., Anang, N.A.S. et al. Immunity (2019): P1084–98.E10
    • Quantifying the dynamics of hematopoiesis by in vivo IdU pulse-chase, mass cytometry, and mathematical modeling
      Erez, A., Mukherjee, R., and Altan-Bonnet, G. Cytometry Part A (2019): 1,075–84
    • Integrated cross-species analysis identifies a conserved transitional dendritic cell population
      Leylek, R., Alcántara-Hernández, M., Lanzar, Z., et al. Cell Reports (2019): 3,736–50.E8
    • T-cell exhaustion correlates with improved outcomes in kidney transplant recipients
      Fribourg, M., Anderson, L., Fischman, C. et al. Kidney International (2019): 436–49
    • Subsets of ILC3−ILC1-like cells generate a diversity spectrum of innate lymphoid cells in human mucosal tissues
      Cella, M., Gamini, R., Secca, C. et al. Nature Immunology (2019): 980–91
    • Complex mammalian-like haematopoietic system found in a colonial chordate
      Rosental, B., Kowarsky, M., Seita, J. et al. Nature (2018): 425–9
    • Spatiotemporal segregation of human marginal zone and memory B cell populations in lymphoid tissue
      Zhao, Y., Uduman, M., Siu, J.H.Y. et al. Nature Communications (2018): 3,857
    • A genome-wide transcriptomic analysis of protein-coding genes in human blood cells
      Uhlen, M., Karlsson, M.J., Zhong, W., et al. Science (2019): eaax9198
    • Multidimensional analyses of proinsulin peptide-specific regulatory T cells induced by tolerogenic dendritic cells
      Suwandi, J.S., Laban, S., Vass, K., et al. Journal of Autoimmunity (2019): 102361
    • Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy
      Ghaemi, M.S., DiGiulio, D.B., Kévin Contrepois, K. et al. Bioinformatics (2019): 95–103
    • Plasmacytoid dendritic cells develop from Ly6D+ lymphoid progenitors distinct from the myeloid lineage
      Dress, R.J., Dutertre, C.A., Giladi, A. et al. Nature Immunology (2019): 852–64
    • Single-cell mass cytometry reveals in vivo immunological response to surgical biomaterials
      Wu, H., Han, S., Wu, B. et al. Applied Materials Today (2019): 169–78
    • Analysis of the murine bone marrow hematopoietic system using mass and flow cytometry
      Ashhurst, T.M., Cox, D.A., Smith, A.L. et al. Mass Cytometry: Methods and Protocols (2019): 159–92
    • Picturing polarized myeloid phagocytes and regulatory cells by mass cytometry
      Roussel, M., Bartkowiak, T. and Irish, J.M. Mass Cytometry: Methods and Protocols (2019): 217–26
    • Development of a 2-dimensional atlas of the human kidney with Imaging Mass Cytometry
      Singh, N., Avigan, Z.M., Kliegel, J.A. et al. JCI Insight (2019): e129477
    • Single-cell analysis of human mononuclear phagocytes reveals subset-defining markers and identifies circulating inflammatory dendritic cells
      Dutertre, C.A., Becht, E., Irac, S.E. et al. Immunity (2019): 30,334–6.
    • Mass cytometry reveals species-specific differences and a new level of complexity for immune cells in the prostate
      Fox, J.J., Navarro, H.I., Hashimoto, T. et al. American Journal of Clinical and Experimental Urology (2019): 281–96.
    • Spatiotemporal immune zonation of the human kidney
      Stewart, B.J., Ferdinand, J.R., Young, M.D. et al. Science (2019): 1,461–6
    • Highly multiplexed Imaging Mass Cytometry allows visualization of tumor and immune cell interactions of the tumor microenvironment in FFPE tissue sections
      Singh, M., Chaudhry, P., Gerdtsson, E. et al. Blood (2017): 2,751
    • Dietary intake regulates the circulating inflammatory monocyte pool
      Jordan, S., Tung, N., Casanova-Acebes, M. et al. Cell (2019): 1,102–14
    • Maturation of the Human Intestinal Immune System Occurs Early in Fetal Development
      Stras, S.F., Werner. L., Toothaker, J.M. et al. Developmental Cell (2019): 357–73.e5
    • Decoding human fetal liver haematopoiesis
      Popescu, D.M, Botting, R.A., Stephenson, E. et al. Nature (2019): 365–71
    • Early-life compartmentalization of immune cells in human fetal tissues revealed by high-dimensional mass cytometry
      Li, N., van Unen, V., Guo, N. et al. Frontiers in Immunology (2019): 1,932
    • Increased T cell differentiation and cytolytic function in Bangladeshi compared to American children
      Wagar, L.E., Bolen, C.R., Sigal, N. et al. Frontiers in Immunology (2019): doi: 10.3389/fimmu.2019.02239
    • Circulating B cells with memory and antibody-secreting phenotypes are detectable in pediatric kidney transplant recipients before the development of antibody-mediated rejection
      Fischman, C., Fribourg, M., Ginevri, F. et al. Transplantation Direct (2019): e481
    • Effect of CTLA4-Ig (abatacept) treatment on T cells and B cells in peripheral blood of patients with polymyositis and dermatomyositis
      Tang, Q., Ramsköld, D., Krystufkova, O. et al. Scandinavian Journal of Immunology (2018): 89
    • Differential control of human Treg and effector T cells in tumor immunity by Fc-engineered anti-CTLA-4 antibody
      Ha, D., Tanaka, A., Kibayashi, T. et al. PNAS (2018): 609–18
    • Human regulatory T cells undergo self-inflicted damage via granzyme pathways upon activation
      Sula Karreci, E., Eskandari, S.K., Dotiwala, F. et al. JCI Insight (2017): e91599
    • T cells expressing chimeric antigen receptor promote immune tolerance
      Pierini, A., Iliopoulou, B.P., Peiris, H. et al. JCI Insight (2017): e92865
    • In silico modeling identifies CD45 as a regulator of IL-2 synergy in the NKG2D-mediated activation of immature human NK cells
      Mukherjee, S., Jensen, H., Stewart, W. et al. Science Signaling (2017): eaai9062
    • Identification and analysis of islet antigen-specific CD8+ T cells with T cell libraries
      Ogura, H., Preston-Hurlburt, P., Perdigoto, A.L. et al. Journal of Immunology (2018): 1,662–70
    • Human bone marrow assessment by single-cell RNA sequencing, mass cytometry, and flow cytometry
      Oetjen, K.A., Lindblad, K.E., Goswami, M. et al. JCI Insight (2018): e124928
    • Gene regulatory programs conferring phenotypic identities to human NK cells
      Collins, P.L., Cella, M., Porter, S.I. et al. Cell (2018): 348-360.e12
    • Opposing Roles of Dendritic Cell Subsets in Experimental GN
      Brähler, S., Zinselmeyer, B.H., Raju, S. et al. Journal of the American Society of Nephrology (2018): 138–54
    • CD44 variant isoform 9 emerges in response to injury and contributes to the regeneration of the gastric epithelium
      Bertaux-Skeirik, N., Wunderlich, M., Teal, E. et al. Journal of Pathology (2017): 463–75
    • Preparation of whole bone marrow for mass cytometry analysis of neutrophil-lineage cells
      Zhu, Y.P., Padgett, L., Dinh, H.Q. et al. Journal of Visual Experiments (2019): doi: 10.3791/59617.
    • Mass cytometry reveals systemic and local immune signatures that distinguish inflammatory bowel diseases
      Rubin, S.J.S., Bai, L., Haileselassie, Y. et al. Nature Communications (2019): 2686
    • Direct CD137 costimulation of CD8 T cells promotes retention and innate-like function within nascent atherogenic foci
      Xu, M.M., Ménoret, A., Nicolas, S.E. et al. American Journal of Physiology Heart and Circulatory Physiology (2019): H1,480–H1,494.
    • Fibro-adipogenic progenitors of dystrophic mice are insensitive to NOTCH regulation of adipogenesis
      Marinkovic, M., Fuoco, C., Sacco, F. et al. Life Science Alliance (2019): e201900437
    • JunB regulates homeostasis and suppressive functions of effector regulatory T cells
      Koizumi, S.-I., Sasaki,D., Hsieh,T.H. et al. Nature Communications (2018): 5,344
    • Fetal-derived macrophages dominate in adult mammary glands
      Jäppinen, N., Félix, I., Lokka, E. et al. Nature Communications (2019): 281
    • Differential dynamics of the maternal immune system in healthy pregnancy and preeclampsia
      Han, X., Ghaemi, M.S., Ando, K. et al. Frontiers in Immunology (2019): 1,305
    • Human Lymph Nodes Maintain TCF-1hi Memory T Cells with High Functional Potential and Clonal Diversity throughout Life
      Miron, M., Kumar, B.V., Meng, W. et al. Journal of Immunology (2018): 2,132–40
    • High-dimensional single-cell proteomics analysis identifies immune checkpoint signatures and therapeutic targets in ulcerative colitis
      Fuchs, S., Sawas, N., Staedler, N. et al. European Journal of Immunology (2018): 462–75
    • Penalized Supervised Star Plots: Example Application in Influenza-Specific CD4+ T Cells
      Holmes, T.H., Subrahmanyam, P.B., Wang, W. et al. Viral Immunology (2019): 102–9
    • Human Germinal Center B Cells Differ from Naïve and Memory B Cells in CD40 Expression and CD40L-Induced Signaling Response
      Huse, K., Wogsland, C.E., Polikowsky, H.G. et al. Cytometry Part A (2019): 442–9
    • The female-biased factor VGLL3 drives cutaneous and systemic autoimmunity
      Billi, A.C., Gharaee-Kermani,M., Fullmer,J. et al. JCI Insight (2019): 127291
    • Memory CD4+ T cells are generated in the human fetal intestine
      Li, N., van Unen, V., Abdelaal, T. et al. Nature Immunology (2019): 301–12
    • Conventional DCs sample and present myelin antigens in the healthy CNS and allow parenchymal T cell entry to initiate neuroinflammation
      Mundt, S., Mrdjen, D., Utz, S.G. et al. Science Immunology (2019): eaau8380
    • Evidence for innate and adaptive immune responses in a cohort of intractable pediatric epilepsy surgery patient
      Owens, G.C., Garcia, A.J., Mochizuki, A.Y. et al. Frontiers in Immunology (2019): 121
    • NK cell immune responses differ after prime and boost vaccination
      Palgen, J.L., Tchitchek, N., Huot, N. et al. Journal of Leukocyte Biology (2019): 1,055–73
    • Single-Cell Proteomics Reveal that Quantitative Changes in Co-expressed Lineage-Specific Transcription Factors Determine Cell Fate
      Palii, C.G., Cheng, Q., Gillespie, M.A. et al. Cell Stem Cell (2019): 812–20.e5
    • Reduced CD27−IgD− B Cells in Blood and Raised CD27−IgD− B Cells in Gut-Associated Lymphoid Tissue in Inflammatory Bowel Disease
      Pararasa, C., Zhang, N., Tull, T.J. et al. Frontiers in Immunology (2019): 361
    • A year-long immune profile of the systemic response in acute stroke survivors
      Tsai, A.S., Berry, K., Beneyto, M.M. et al. Brain (2019): 978–91
    • Lymphocyte mass cytometry identifies a CD3-CD4+ cell subset with a potential role in psoriasis
      Guo, R., Zhang, T., Meng, X. et al. JCI Insight (2019): 125,306
    • RUNX3 levels in human hematopoietic progenitors are regulated by aging and dictate erythroid-myeloid balance
      Balogh, P., Adelman, E.R., Pluvinage, J.V. et al. Haematologica (2019): doi:10.3324/haematol.2018.208918 %J Haematologica
    • The biology of the cell - insights from mass cytometry
      Brodin, P. FEBS Journal (2018): 1,514–22
    • A Subset of Type I Conventional Dendritic Cells Controls Cutaneous Bacterial Infections through VEGFα-Mediated Recruitment of Neutrophils
      Janela, B., Patel, A.A., Lau, M.C. et al. Immunity (2019): 1,069–83
    • Increased monocyte count as a cellular biomarker for poor outcomes in fibrotic diseases: a retrospective, multicentre cohort study
      Scott, M.K.D., Quinn, K., Li, Q. et al. The Lancet (2019): 497–508
    • Dissecting alterations in human CD8+ T cells with aging by high-dimensional single cell mass cytometry
      Shin, M.S., Yim, K., Moon, K. et al. Clinical Immunology (2019): 24–30
    • Spatiotemporal Modeling of the Key Migratory Events During the Initiation of Adaptive Immunity
      Hayes, A.J., Rane, S., Scales, H.E. et al. Frontiers in Immunology (2019): 598
    • Autocrine TGFβ is a Survival Factor for Monocytes and Drives Immunosuppressive Lineage Commitment
      Gonzalez-Junca, A., Driscoll, K., Pellicciotta, I. et al. Cancer Immunology Research (2019): DOI: 10.1158/2326-6066.CIR-18-0310
    • T cell cytolytic capacity is independent of initial stimulation strength
      Richard, A.C., Lun, A.T.L., Lau, W.W.Y. et al. Nature Immunology (2018): 849–58
    • Airway Epithelial Cell-Derived Colony Stimulating Factor-1 Promotes Allergen Sensitization
      Moon, H.G., Kim, S.J., Jeong, J.J. et al. Immunity (2018): 275–87.e5
    • Induction and transcriptional regulation of the co-inhibitory gene module in T cells
      Chihara, N., Madi, A., Kondo, T. et al. Nature (2018): 454–9
    • Implementation of Mass Cytometry as a Tool for Mechanism of Action Studies in Inflammatory Bowel Disease
      Tyler, C.J., Pérez-Jeldres, T., Ehinger, E. et al. Inflammatory Bowel Diseases (2018): 2,366–76
    • Atherosclerosis in the single-cell era
      Winkels, H., Ehinger, E., Ghosheh, Y. et al. Current Opinion in Lipidology (2018): 389–96
    • Identification of an Early Unipotent Neutrophil Progenitor with Pro-tumoral Activity in Mouse and Human Bone Marrow
      Zhu, Y.P., Padgett, L., Dinh, H.Q. et al. Cell Reports (2018): 2,329–41
    • CD8+ T Cell Priming in Established Chronic Viral Infection Preferentially Directs Differentiation of Memory-like Cells for Sustained Immunity
      Snell, L.M., MacLeod, B.L., Law, J.C. et al. Immunity (2018): 678–94
    • Human retinoic acid-regulated CD161+ regulatory T cells support wound repair in intestinal mucosa
      Povoleri, G.A.M., Nova-Lamperti, E., Scottà, C. et al. Nature Immunology (2018): 1,403–14
    • Proof of concept study of mass cytometry in septic shock patients reveals novel immune alterations
      Gossez, M., Rimmelé, T., Andrieu, T. et al. Scientific Reports (2018): 17,296
    • OMIP-048 MC: Quantification of calcium sensors and channels expression in lymphocyte subsets by mass cytometry
      Jaracz-Ros, A., Hémon, P., Krzysiek, R. et al. Cytometry Part A: Journal of the ISAC (2018): 681–4
    • The 10,000 Immunomes Project: Building a Resource for Human Immunology
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    • Unravelling immune cell complexity in atherosclerosis
      Clément, M., Mallat, Z. Nature Protocols (2018): 1,306-7
    • Genomic Profiling of T-Cell Neoplasms Reveals Frequent JAK1 and JAK3 Mutations With Clonal Evasion From Targeted Therapies
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    • CD161 Defines a Functionally Distinct Subset of Pro-Inflammatory Natural Killer Cells
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    • Acute microglia ablation induces neurodegeneration in the somatosensory system
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    • Visual analysis of multidimensional CyTOF data from allergic asthmatics pre and post allergen challenge
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    • Single-cell mass cytometry and transcriptome profiling reveal the impact of graphene on human immune cells
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    • Unique phenotypes and clonal expansions of human CD4 effector memory T cells re-expressing CD45RA
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    • Exposure to NO2, CO, and PM2.5 is linked to regional DNA methylation differences in asthma
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    • Differences Between Pediatric and Adult T Cell Responses to In Vitro Staphylococcal Enterotoxin B Stimulation
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      Thomas, G.D., Hamers, A.A.J., Nakao, C. et al. Arteriosclerosis, Thrombosis and Vascular Biology (2017): 1,548–58
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    • Detection, phenotyping, and quantification of antigen-specific T cells using a peptide-MHC dodecamer
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    • A High-Dimensional Atlas of Human T Cell Diversity Reveals Tissue-Specific Trafficking and Cytokine Signature
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    • Mass cytometry profiling the response of basophils and the complete peripheral blood compartment to peanut
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      Mingueneau, M., Boudaoud, S., Haskett, S. et al. The Journal of Allergy and Clinical Immunology (2016): 1,809–21
    • Increased lymphocyte apoptosis in mouse models of colitis upon ABT-737 treatment is dependent upon BIM expression
      Lutz, C., Mozaffari, M., Tosevski, V. et al. Clinical and Experimental Immunology (2015): 343–56
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    • Human CD4+ lymphocytes for antigen quantification: characterization using conventional flow cytometry and mass cytometry
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    • The transcriptional landscape of αβ T cell differentiation
      Mingueneau, M., Kreslavsky, T., Gray, D. et al. Nature Immunology (2013): 619–32
    • Genetic and environmental determinants of human NK cell diversity revealed by mass cytometry
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    • Antigen-dependent integration of opposing proximal TCR-signaling cascades determines the functional fate of T lymphocytes
      Wolchinsky, R., Hod-Marco, M., Oved, K. et al. Journal of Immunology (2014): 2,109–19
    • Clinical recovery from surgery correlates with single-cell immune signatures
      Gaudillière, B., Fragiadakis, G.K., Bruggner, R.V. et al. Science Translational Medicine (2014): 255ra131
    • Single-cell mass cytometry analysis of human tonsil T cell remodeling by varicella zoster virus
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    • CD161 defines a transcriptional and functional phenotype across distinct human T cell lineages
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    • Human skin is protected by four functionally and phenotypically discrete populations of resident and recirculating memory T cells
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    • Pregnancy Does Not Attenuate the Antibody or Plasmablast Response to Inactivated Influenza Vaccine
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    • Single-cell trajectory projection uncovers progression and regulatory coordination in human B cell development
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    • Adenoviral Vector Vaccination Induces a Conserved Program of CD8+ T Cell Memory Differentiation in Mouse and Man
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    • Large-Scale and Comprehensive Immune Profiling and Functional Analysis of Normal Human Aging
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    • Expansion of inflammatory innate lymphoid cells in patients with common variable immune deficiency
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    • Reversibility of Defective Hematopoiesis Caused by Telomere Shortening in Telomerase Knockout Mice
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    • Expression of specific inflammasome gene modules stratifies older individuals into two extreme clinical and immunological states
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    • Mass spectrometry goes with the flow: mass cytometry and its potentials in regenerative medicine
      Agnetti, G. Circulation: Cardiovascular Genetics (2012): 379–80
    • New tools for classification and monitoring of autoimmune diseases
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    • The Spectrum and Regulatory Landscape of Intestinal Innate Lymphoid Cells Are Shaped by the Microbiome
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    • Deep phenotyping of Tregs identifies an immune signature for idiopathic aplastic anemia and predicts response to treatment
      Kordasti, S., Costantini, B., Seidl, T. et al. Blood (2016): 1,193–205
    • Unsupervised High-Dimensional Analysis Aligns Dendritic Cells across Tissues and Species
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    • Comprehensive mass cytometry analysis of cell cycle, activation and coinhibitory receptors expression in CD4 T cells from healthy and HIV-infected individuals
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    • Isolation and high-dimensional phenotyping of gastrointestinal immune cells
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    • Lymphocyte enrichment using CD81-targeted immunoaffinity matrix
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    • Activation of the reward system boosts innate and adaptive immunity
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    • Impact of the microbial derived short chain fatty acid propionate on host susceptibility to bacterial and fungal infections in vivo
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  • Immunophenotyping

    • Profiling of the human natural killer cell receptor-ligand repertoire
      Vendrame, E., McKechnie, J. L., Ranganath, T. et al. Journal of Visualized Experiments (2021): doi: 10.3791/61912
    • Deep phenotypical characterization of human CD3+CD56+ T cells by mass cytometry
      Romero-Olmedo, A.J., Schulz, A. R., Huber, M. et al. European Journal of Immunology (2020): DOI: 10.1002/eji.202048941
    • SLAMF7 and IL-6R define distinct cytotoxic versus helper memory CD8+ T cells
      Loyal, L., Warth, S., Jürchott, K.et al. Nature Communications (2020): doi.org/10.1007/978-4-431-88315-9_11.
    • Multi‐site reproducibility of a human immunophenotyping assay in whole blood and peripheral blood mononuclear cells preparations using CyTOF technology coupled with Maxpar Pathsetter, an automated data analysis system
      Bagwell, C.B., Hunsberger, B., Hill, B. Cytometry Part B Clinical Cytometry (2019): DOI: 10.1002/cyto.b.21858
    • Maternal obesity is associated with phenotypic alterations in fetal immune cells by single‐cell mass cytometry
      Enninga, E.A.L., Jang, J. S., Hur, B. American Journal of Reproductive Immunology (2020): doi.org/10.1111/aji.13358
    • Mass cytometry reveals global immune remodeling with multi-lineage hypersensitivity to Type I interferon in Down syndrome
      Waugh, K.A., Araya, P., Pandey, A., et al. Cell Reports (2019): 1,893–908.e4
    • Mapping of γ/δ T cells reveals Vδ2+ T cells resistance to senescence
      Xu, W., Monaco, G., Wong, E.H.. et al. EBioMedicine (2019): 44–58
    • Pitfalls in the characterization of circulating and tissue-resident human γδ T cells
      Beucke, N., Wesch, D., Oberg, H.-H., et al Journal of Leukocyte Biology (2020): 1,097-105
    • Inherent immune cell variation within colonic segments presents challenges for clinical trial design
      Tyler, C.J., Guzman, M. Lundborg, L.R. et al. Journal of Crohn's and Colitis (2020): doi: 10.1093/ecco-jcc/jjaa067
    • Distinctive phenotypes and functions of innate lymphoid cells in human decidua during early pregnancy
      Huhn, O., Ivarsson, M.A., Gardner, L. et al. Nature Communications (2020): 381
    • Multi-parameter immune profling of peripheral blood mononuclear cells by multiplexed single-cell mass cytometry in patients with early multiple sclerosis
      Böttcher, C., Fernández-Zapata, C., Schlickeiser, S. et al. Scientific Reports (2019): 19471
    • T-cell phenotyping uncovers systemic features of atopic dermatitis and psoriasis
      Farrera, C., Melchiotti, R., Petrov, N., et al. Journal of Allergy and Clinical Immunology (2019): 31623–9
    • Distinguishing human peripheral blood CD16+ myeloid cells based on phenotypic characteristics
      Fromm, P.D., Silveira, P.A., Hsu, J.L., et al. Journal of Leukocyte Biology (2019): 323-339
    • A high-resolution mass cytometry analysis reveals a delay of cytokines production after TLR4 or TLR7/8 engagements in HIV-1 infected humans
      Leite Pereira, A., Tchitchek, N., Marcos Lopez, E. et al. Cytokine (2018): 97–105
    • Single-cell immune landscape of human atherosclerotic plaques
      Fernandez, D.M., Rahman, A.H., Fernandez, N.F. et al. Nature Medicine (2019): 1,576–88
    • Short-term sleep deprivation in mice induces B cell migration to the brain compartment
      Korin, B., Avraham, S., Azulay-Debby, H. et al. Sleep (2019): doi:10.1093/sleep/zsz222
    • Practical limitations of monocyte subset repartitioning by multiparametric flow cytometry in chronic myelomonocytic leukemia
      Pophali, P.A., Timm, M.M., Mangaonkar, A.A. et al. Blood Cancer Journal (2019): 65
    • Laboratory mice born to wild mice have natural microbiota and model human immune responses
      Rosshart, S.P., Herz, J., Vassalo, B.G. et al. Science (2019): DOI: 10.1126/science.aaw4361
    • Human microglia regional heterogeneity and phenotypes determined by multiplexed single-cell mass cytometry
      Böttcher, C., Schlickeiser, S., Sneeboer, M.A.M. et al. Nature Neuroscience (2018): 78-90
    • High-dimensional single-cell analysis reveals the immune signature of narcolepsy
      Hartmann, F.J., Bernard-Valnet, R., Quériault, C. et al. Journal of Experimental Medicine (2017): 2,621–33
    • High-Dimensional Single-Cell Mapping of Central Nervous System Immune Cells Reveals Distinct Myeloid Subsets in Health, Aging, and Disease
      Mrdjen, D., Pavlovic, A., Hartmann, F.J. et al. Immunity (2018): 380–95
    • Comprehensive immune monitoring of clinical trials to advance human immunotherapy
      Hartmann, F.J., Babdor, J., Gherardini, P.F. et al. Cell Reports (2019): 819-831.E4
    • A unique presentation of infantile-onset colitis and eosinophilic disease without recurrent infections resulting from a novel homozygous CARMIL2 variant
      Kurolap, A., Adiv, O.E., Konnikova, L. et al. Journal of Clinical Immunology (2019): 430-439
    • Validation of CyTOF® against flow cytometry for immunological studies and monitoring of human cancer clinical trials
      Gadalla, R., Noamani, B., MacLeod, B.L. et al. Frontiers in Oncology (2019): 415
    • OMIP-054: Broad Immune Phenotyping of Innate and Adaptive Leukocytes in the Brain, Spleen, and Bone Marrow of an Orthotopic Murine Glioblastoma Model by Mass Cytometry
      Dusoswa, S.A., Verhoeff, J., Garcia-Vallejo, J.J. Cytometry Part A (2019): 422-6
    • Expansion and activation of distinct central memory T lymphocyte subsets in complex regional pain syndrome
      Russo, M.A., Fiore, N.T., van Vreden, C. et al. Journal of Neuroinflammation (2019): doi: 10.1186/s12974-019-1449-9
    • Systems-level immune monitoring by mass cytometry
      Lakshmikanth, T., Brodin, P. Methods in Molecular Biology (2019): doi: 10.1007/978-1-4939-8979-9_3
    • A clinically meaningful metric of immune age derived from high-dimensional longitudinal monitoring
      Alpert ,A., Pickman, Y., Leipold M. et al. Nature Medicine (2019): 487-95
    • Human Monocyte Heterogeneity as Revealed by High-Dimensional Mass Cytometry
      Hamers, A.A.J., Dinh, H.Q., Thomas, G.D. et al. Arteriosclerosis, Thrombosis, and Vascular Biology (2019): 25–36
    • Maturing human CD127+ CCR7+ PDL1+ dendritic cells express AIRE in the absence of tissue restricted antigens
      Fergusson, J.R., Morgan, M., Bruchard, M. et al. Frontiers in Immunology (2018): doi: 10.3389/fimmu.2018.02902
    • Heterogeneity of circulating CD8 T-cells specific to islet, neo-antigen and virus in patients with type 1 diabetes mellitus
      Laban, S., Suwandi, J.S., van Unen, V. et al. PLoS One (2018): e0200818
    • CD56 Expression Marks Human Group 2 Innate Lymphoid Cell Divergence from a Shared NK Cell and Group 3 Innate Lymphoid Cell Developmental Pathway
      Chen, L., Youssef, Y., Robinson, C. et al. Immunity (2018): 464-76
    • Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry
      Baxter, R.M., Kong, D.S., Garcia-Perez, J.E. et al. Journal of Visualized Experiments (2018): doi: 10.3791/57780
    • Circulating Endothelial Progenitor Cells Present an Inflammatory Phenotype and Function in Patients With Alcoholic Liver Cirrhosis
      Kaur, S., Seghal, R., Shastry, S.M. et al. Frontiers in Physiology (2018): doi: 10.3389/fphys.2018.00556
    • Single-cell RNA sequencing to explore immune cell heterogeneity
      Papalexi, E., Satija, R. Nature Reviews Immunology (2018): 35-45
    • Deep Profiling of the CD8+ T cell Compartment identifies Activated cell subsets and Multifunctional Responses Associated with Control of Cytomegalovirus Viremia
      Ferreira, V.H., Kumar, D., Humar, A. Transplantation (2018): doi: 10.1097/TP.0000000000002373
    • Single-Cell Chromatin Modification Profiling Reveals Increased Epigenetic Variations with Aging
      Cheung, P., Vallania, F., Warsinske, H.C. et al. Cell (2018): 1,385-97
    • Single-cell analysis identifies a CD33+ subset of human cord blood cells with high regenerative potential
      Knapp, D.J.H.F., Hammond, C.A., Hui, T. et al. Nature Cell Biology (2018): 710-20
    • Cytometry TOF identifies alveolar macrophage subtypes in acute respiratory distress syndrome
      Morrell, E.D., Wiedeman, A., Long, S.A. et al. JCI Insight (2018): doi: 10.1172/jci.insight.99281
    • Prime and Boost Vaccination Elicit a Distinct Innate Myeloid Cell Immune Response
      Palgen, J.L., Tchitchek, N., Elhmouzi-Younes, J. et al. Scientific Reports (2018): https://doi.org/10.1038/s41598-018-21222-2
    • Proteomic approaches for novel systemic lupus erythematosus (SLE) drug discovery
      Li, Y., Wu, T. Expert Opinion on Drug Discovery (2018): 765-77
    • Immune cell census in murine atherosclerosis: cytometry by time of flight illuminates vascular myeloid cell diversity
      Cole, J.E., Park, I., Ahern, D. et al. Cardiovascular Research (2018): 1,360–71
    • Identity and Diversity of Human Peripheral Th and T Regulatory Cells Defined by Single-Cell Mass Cytometry
      Kunicki, M.A., Amaya Hernandez, L.C., Davis, K.L. et al. Journal of Immunology (2018): 336–46
    • Atlas of the immune cell repertoire in mouse atherosclerosis defined by single-cell RNA-sequencing and mass cytometry
      Winkels, H., Ehinger, E., Vassallo, M. et al. Circulation Research (2018): CIRCRESAHA-117
    • Deep Immune Profiling of an Arginine-Enriched Nutritional Intervention in Patients Undergoing Surgery
      Aghaeepour, N., Kin, C., Ganio, E.A. et al. Journal of Immunology (2017): 2,171–80
    • Single-cell mass cytometry reveals distinct populations of brain myeloid cells in mouse neuroinflammation and neurodegeneration models
      Ajami, B., Samusik, N., Wieghofer, P. et al. Nature Neuroscience (2018): 541–51
    • MAIT cell clonal expansion and TCR repertoire shaping in human volunteers challenged with Salmonella Paratyphi A
      Howson, L.J., Napolitani, G., Shepherd, D. et al. Nature Communications (2018): 253
    • The receptor repertoire and functional profile of follicular T cells in HIV-infected lymph nodes
      Wendel, B.S., Del Alcazar, D., He, C. et al. Science Immunology (2018): eaan8884
    • Mass cytometry analysis of immune cells in the brain
      Korin, B., Dubovik, T., Rolls, A. Nature Protocols (2018): 377–91
    • Mass cytometry reveals innate lymphoid cell differentiation pathways in the human fetal intestine
      Li, N., van Unen, V., Höllt, T. et al. Journal of Experimental Medicine (2018): 1,383–96
    • Broad immune monitoring and profiling of T cell subsets with mass cytometry
      Brodie, T.M., Tosevski, V. Methods in Molecular Biology (2018): 67–82
    • Application of phospho-CyTOF® to characterize immune activation in patients with sickle cell disease in an ex vivo model of thrombosis
      Glassberg, J., Rahman, A.H., Zafar, M. et al. Journal of Immunological Methods (2017): 11–19
    • CyTOF® measurement of immunocompetence across major immune cell types
      Subrahmanyam, P.B., Maecker, H.T. Current Protocols in Cytometry (2017): 9.54.1–12
    • SCREENING: CyTOF®—the next generation of cell detection
      Cheung, R.K., Utz, P.J. Nature Reviews Rheumatology (2011): 502–3
    • OMIP-034: Comprehensive immune phenotyping of human peripheral leukocytes by mass cytometry for monitoring immunomodulatory therapies
      Baumgart, S., Peddinghaus, A., Schulte-Wrede, U. et al. Cytometry Part A (2016): 34–8
    • In depth comparative phenotyping of blood innate myeloid leukocytes from healthy humans and macaques using mass cytometry
      Elhmouzi-Younes, J., Palgen, J.L., Tchitchek, N. et al. Cytometry Part A (2017): 969–82
    • Innate immune landscape in early lung adenocarcinoma by paired single-cell analyses
      Lavin, Y., Kobayashi, S., Leader, A. et al. Cell (2017): 750-65
    • Continuous immunotypes describe human immune variation and predict diverse responses
      Kaczorowski, K.J., Shekhar, K., Nkulikiyimfura, D. et al. Proceedings of the National Academy of Sciences of the United States of America (2017): E6,097–106
    • Multiparameter single cell profiling of airway inflammatory cells
      Yao, Y., Welp, T., Liu, Q. et al. Cytometry Part B, Clinical Cytometry (2016): 12–20
    • Applying mass cytometry to the analysis of lymphoid populations in transplantation
      Krams, S.M., Schaffert, S., Lau, A.H., Martinez O.M. American Journal of Transplantation (2016): 1,992–9
    • Mass cytometry reveals a distinct immunoprofile of operational tolerance in pediatric liver transplantation
      Lau, A.H., Vitalone, M.J., Hass, K. et al. Pediatric Transplantation (2016): 1,072–80
    • Mapping the Fetomaternal Peripheral Immune System at Term Pregnancy
      Fragiadakis, G.K., Baca, Q.J., Gherardini, P.F. et al. The Journal of Immunology (2016): 4,482–92
    • Emerging single-cell technologies in immunology
      Herderschee, J., Fenwick, C., Pantaleo, G. et al. Journal of Leukocyte Biology (2015): 23–32
    • Highly multiparametric analysis by mass cytometry
      Ornatsky, O., Bandura, D., Baranov, V. et al. Journal of Immunological Methods (2010): 1–20
    • Mass cytometry: single cells, many features
      Spitzer, M.H., Nolan, G.P. Cell (2016): 780–91
    • Patient-specific immune states before surgery are strong correlates of surgical recovery
      Fragiadakis, G.K., Gaudillière, B., Ganio, E.A. et al. Anesthesiology (2015): 1,241–55
    • Mass cytometry as a platform for the discovery of cellular biomarkers to guide effective rheumatic disease therapy
      Nair, N., Mei, H.E., Chen, S.Y. et al. Arthritis Research & Therapy (2015): 127
    • Variation in the human immune system is largely driven by non-heritable influences.
      Brodin, P., Jojic, V., Gao, T. et al. Cell (2015): 37–47
    • Distinct immunologic changes in vivo following combination versus individual PD-1 or CTLA-4 checkpoint blockade in human cancer
      Dhodapkar, K., Verma, R., Sznol, M. et al. Journal for ImmunoTherapy of Cancer (2014): O7
    • Combination therapy with anti-CTLA4 and anti-PD1 leads to distinct immunologic changes in-vivo
      Das, R., Verma, R., Sznol, M. et al. Journal of Immunology (2015): 950–9
    • Human NK cell repertoire diversity reflects immune experience and correlates with viral susceptibility
      Strauss-Albee, D.M., Fukuyama, J., Liang, E.C. et al. Science Translational Medicine (2015): 297ra115
    • Decoupling of Tumor-Initiating Activity from Stable Immunophenotype In HoxA9-Meis1 Driven AML
      Gibbs, K.D., Jager, A., Crespo, O. et al. Cell Stem Cell (2013): 210–7
    • Multicenter Systems Analysis of Human Blood Reveals Immature Neutrophils in Males and During Pregnancy
      Blazkova, J., Gupta, S., Liu, Y. et al. Journal of Immunology (2017): 2,479–88
    • Targeting YAP-dependent MDSC infiltration impairs tumor progression
      Wang, G., Lu, X., Dey, P. et al. Cancer Discovery (2016): 80–95
    • Immune Profiles to Predict Response to Desensitization Therapy in Highly HLA-Sensitized Kidney Transplant Candidates
      Yabu, J.M., Siebert, J.C., Maecker, H.T. PLoS One (2016): e0153355
    • Protein networks and activation of lymphocytes
      Helou, Y.A., Salomon, A.R. Current Opinion in Immunology (2015): 78–85
    • Characterization of lung infection-induced TCRγδ T cell phenotypes by CyTOF mass cytometry
      Wanke-Jellinek, L., Keegan, J.W., Dolan, J.W., Lederer, J.A. Journal of Leukocyte Biology (2015): 483–93
    • Characterizing Phenotypes and Signaling Networks of Single Human Cells by Mass Cytometry
      Leelatian, N., Diggins, K.E., Irish, J.M. Methods in Molecular Biology (2015): 99–113
    • New technologies for autoimmune disease monitoring
      Maecker, H.T., Nolan, G.P., Fathman, C.G. Current Opinion in Endocrinology, Diabetes and Obesity (2010): 322–8

  • Infectious Disease/Microbiology

    • A randomized placebo-controlled efficacy study of a prime boost therapeutic vaccination strategy in HIV-1 infected individuals: VRI02 ANRS 149 LIGHT Phase II trial
      Levy, Y., Lacabaratz, C., Lhomme, E. Journal of Virology (2021): DOI: 10.1128/JVI.02165-20
    • The immune landscape in tuberculosis reveals populations linked to disease and latency
      Esaulova, E., Das, S., Singh, D. K. Cell Host & Microbe (2021): 165-178
    • Intrapulmonary vaccination with delta-inulin adjuvant stimulates non-polarised chemotactic signalling and diverse cellular interaction
      Ferrell, K.C. Stewart, E. L., Counoupas, C. Mucosal Immunology (2021): 762–773
    • Immune responses and pathogenesis in persistently PCR‐positive patients with SARS‐CoV‐2 infection
      Yu, H.B., Wang, W-J., MM, S. T. Journal of Medical Virology (2021): doi.org/10.1002/jmv.26287
    • The COVID-19 immune landscape is dynamically and reversibly correlated with disease severity
      Bolouri, H., Speake, C., Skibinski, D. Journal of Clinical Investigation (2021): doi.org/10.1172/JCI143648DS1
    • Infectious Complications Predict Premature CD8 + T-cell Senescence in CD40 Ligand-Deficient Patients
      Shin, J.J., Catanzaro, J., Yonkof, J. R. Journal of Clinical Immunology (2021): 795–806
    • Memory CD8 + T cell heterogeneity is primarily driven by pathogen-specific cues and additionally shaped by the tissue environment
      van der Gracht, E.T.I., Beyrend, G., Abdelaal, T. iScience (2021): doi.org/10.1016/j.isci.2020.101954
    • Gene signature and immune cell profiling by high-dimensional, single-cell analysis in COVID-19 patients, presenting Low T3 syndrome and coexistent hematological malignancies
      Sciacchitano, S., Vitis, C. D., D’Ascanio, M. Journal of Translational Medicine (2021): doi.org/10.1186/s12967-021-02805-6
    • Aging and CMV discordance are associated with increased immune diversity between monozygotic twins
      Yan, Z., Maecker, H.T., Brodin, P. Immunity & Aging (2021): doi.org/10.1186/s12979-021-00216-1
    • Aging and CMV discordance are associated with increased immune diversity between monozygotic twins
      Xu, W., Snell, L.M., Guo, M. Immunity (2021): DOI: 10.1016/j.immuni.2021.01.003
    • Early Use of Corticosteroid May Prolong SARS-CoV-2 Shedding in Non-Intensive Care Unit Patients with COVID-19 Pneumonia: A Multicenter, Single-Blind, Randomized Control Trial
      Tang, X., Feng, Y-M., Ni, J-X. Respiration (2021): 116–126
    • Characterization of pre-existing and induced SARS-CoV-2-specific CD8+ T cells
      Schulien, I., Kemming,J., Neumann-Haefelin, C. Nature Medicine (2021): 78–85
    • Mass cytometry and artificial intelligence define CD169 as a specific marker of SARSCoV2-induced acute respiratory distress syndrome
      Roussel, M., Juillete, F., Florian, R. Cell Reports Medicine - Sneak Peak (2021): doi.org/10.2139/ssrn.3751801
    • Impaired T- and NK-cell reconstitution after haploidentical HCT with posttransplant cyclophosphamide
      Rambaldi, B., Kim, H.T., Reynolds, C. Blood Advances (2021): 352–364
    • SARS-CoV-2–specific CD8+ T cell responses in convalescent COVID-19 individuals
      Kared, H., Redd, A.D., Bloch, E. M. Journal of Clinical Investigation (2021): doi.org/10.1172/JCI145476DS1
    • A streamlined whole blood CyTOF workflow defines a circulating immune cell signature of COVID-19
      Geanon, D., Lee, B., Gonzalez‐Kozlova, E. Cytometry Part A (2021): doi.org/10.1002/cyto.a.24317
    • Down-regulated gene expression spectrum and immune responses changed during the disease progression in COVID-19 patients
      Ouyang, Y., Yin, J., Wang, W. et al. Clinical Infectious Disease (2020): DOI: 10.1093/cid/ciaa462
    • Mass cytometry defines virus-specific CD4 + T cells in influenza vaccination
      Subrahmanyam, P.B., Holmes, T.H., Lin, D. et al. Immunohorizons (2020): 774-788
    • Systems-level immunomonitoring from acute to recovery phase of severe COVID-19
      Rodriguez, L., Pekkarinen, P. T., Lakshmikanth, T. Cell Reports Medicine (2020): doi.org/10.1016/j.xcrm.2020.100078
    • Landscape of coordinated immune responses to H1N1 challenge in humans
      Rahil, Z., Leylek, R., Schürch, C. M. et al. Journal of Clinical Investigation (2020): doi.org/10.1172/JCI137265DS1
    • Phenotypic analysis of the unstimulated in vivo HIV CD4 T cell reservoir
      Neidleman, J., Luo, X., Frouard, J.et al. eLife (2020): doi.org/10.1038/nm.4113
    • A distinct innate immune signature marks progression from mild to severe COVID-19
      Chevrier, S., Zurbuchen, Y., Cervia, C. et al. Cell Reports Medicine (2020): DOI:https://doi.org/10.1016/j.xcrm.2020.100166
    • Dysregulation of the immune response affects the outcome of critical COVID‐19 patients
      Wei, L.L., Wang, W.J., Chen, D.X. et al. Journal of Medical Virology (2020): doi.org/10.1002/jmv.26181
    • HIV infection is associated with loss of anti-inflammatory alveolar macrophages
      Neff, C.P., Atif, S. M., Logue, E. C. et al. Journal of Immunology (2020): DOI: 10.4049/jimmunol.2000361
    • High CD45 expression of CD8+ and CD4+ T cells correlates with the size of HIV-1 reservoir in blood
      Petkov, S., Bekele, Y., Lakshmikanth, T. et al. Scientific Reports (2020): doi.org/10.1093/cid/ciaa809
    • Helminth infections drive heterogeneity in human type 2 and regulatory cells
      de Ruiter, K., Jochems, S.P., Tahapary, D.L. Science Translational Medicine (2020): DOI: 10.1126/scitranslmed.aaw3703
    • Comprehensive immunoprofiling of pediatric Zika reveals key role for monocytes in the acute phase and no effect of prior dengue virus infection
      Michlmayr, D., Kim, E.-Y., Rahman, A.H. Cell Reports (2020): 107569.
    • Innate and secondary humoral responses are improved by increasing the time between MVA vaccine immunizations
      Palgen, J.-L., Tchitchek, N., Rodriguez-Pozo, A. npj Vaccines (2020): 24.
    • Zika virus mucosal infection provides protective immunity
      Martínez, L.E., Garcia, G. Jr., Contreras, D. Journal of Virology (2020): DOI: 10.1128/JVI.00067-20
    • Mapping the extent of heterogeneity of human CCR5+ CD4 T-cells in peripheral blood and lymph nodes
      Zaunders, J., Munier, C.M.L., McGuire, H. M. AIDS (2020): DOI: 10.1097/QAD.0000000000002503
    • TIGIT is upregulated by HIV-1 infection and marks a highly functional adaptive and mature subset of natural killer cells
      Vendrame, E., Seiler, C., Ranganath, T. AIDS (2020): DOI: 10.1097/QAD.0000000000002488
    • SARS-CoV-2 infection is associated with a pro-thrombotic platelet phenotype
      Bongiovanni, D., Klug, M., Lazareva. O. Cell Death & Disease (2021): doi.org/10.1182/blood.2020007214
    • Novel multiparameter correlates of Coxiella burnetii infection and vaccination identified by longitudinal deep immune profiling
      Reeves, P.M., Paul, S. R., Baeten, L. Scientific Reports (2021): doi: 10.1038/s41598-020-69327-x
    • The inhibition of IL-2/IL-2R gives rise to CD8+ T cell and lymphocyte decrease through JAK1-STAT5 in critical patients with COVID-19 pneumonia
      Shi, H., Wang, W., Yin, J. Cell Death & Disease (2021): doi.org/10.1101/2020.02.10.20021832
    • Cutting edge: characterization of human tissue-resident memory T Cells at different infection sites in patients with tuberculosis
      Yang, Q. , Zhang, M., Chen, Q. Journal of Immunology (2020): DOI: 10.4049/jimmunol.1901326
    • Modulation of cell surface receptor expression by modified vaccinia virus Ankara in leukocytes of healthy and HIV-infected individuals
      Leite Pereira, A., Jouhault, Q., Lopez, E. M. Frontiers in Immunology (2020): doi.org/10.3389/fimmu.2020.02096
    • Immunologic timeline of Ebola virus disease and recovery in humans
      McElroy, A.K., Akondy, R. S., Mcllwain, D. R. JCI Insight (2020): doi.org/10.1172/jci.insight.137260DS1
    • A network of immune and microbial modifications underlies viral persistence in the gastrointestinal tract
      Macleod, B.L., Elsaesser, H. J., Snell, L. M. Journal of Experimental Medicine (2020): doi.org/10.1084/jem.20191473
    • HIV efficiently infects T cells from the endometrium and remodels them to promote systemic viral spread
      Ma, T., Luo, X., George, A. F. eLife (2020): DOI: 10.7554/eLife.55487
    • Single-cell profiling of Ebola virus disease in vivo reveals viral and host dynamics
      Kotliar, D., Lin, A. E., Logue, J. Cell (2020): doi.org/10.1016/j.cell.2020.10.002
    • Multidimensional proteomic approach of endothelial progenitors demonstrate expression of KDR restricted to CD19 cells
      Guerin, C.L., Guyonnet, L., Goudot, G. Stem Cell Reviews and Reports (2020): doi.org/10.1016/j.cell.2020.09.034
    • Mapping systemic inflammation and antibody responses in multisystem inflammatory syndrome in children (MIS-C)
      Gruber, C., Patel, R. S., Trachtman, R. Cell (2020): doi.org/10.1016/j.cell.2020.09.034
    • The potential role of immune alteration in the cancer–COVID19 equation—a prospective longitudinal study
      Goshen-Lago, T., Szwarcwort-Cohen, M., Benguigui, M. Cancers (2020): doi.org/10.3390/cancers12092421
    • Ontogeny of different subsets of yellow fever virus-specific circulatory CXCR5+ CD4+ T cells after yellow fever vaccination
      DeGottardi, Q., Gates, T. J., Yang, J. Scientific Reports (2020): doi.org/10.1002/cyto.a.22348
    • Natural killer cell phenotype is altered in HIV-exposed seronegative women
      Zhao, N.Q., Vendrame, E., Ferreira, A. M. PLOS One (2020): doi.org/10.1371/journal.pone.0238347
    • Treated HIV infection alters phenotype but not HIV-specific function of peripheral blood natural killer cells
      Zhao, N.Q., Ferreira, A. M., Grant, P. M. Frontiers in Immunology (2020): doi: 10.3389/fimmu.2020.00829
    • Unbiased profiling reveals compartmentalization of unconventional T-cells within the intestinal mucosa irrespective of HIV infection
      Magnoumba, M., Singh, A., Ogongo, P. Frontiers in Immunology (2020): doi: 10.1038/ni.3298
    • Vi-vaccinations induce heterogeneous plasma cell responses that associate with protection from typhoid fever
      Cross, D.L., Verheul, M. K., Leipold, M. D. Frontiers in Immunology (2020): doi: 10.1093/cid/cis359
    • Metformin enhances anti-mycobacterial responses by educating CD8+ T-cell immunometabolic circuits
      Bohme, J., Martinez, N., Li, S. Nature Communications (2020): doi.org/10.1101/2020.03.06.978791.
    • Altered immune response to the annual influenza A vaccine in patients with myeloproliferative neoplasms
      Alimam, S., Timms , J.A., Harrison, C.N. British Journal of Haematology (2020): doi.org/10.1111/bjh.17096
    • High-dimensional single-cell analysis reveals the immune characteristics of COVID-19
      Shi, W., Liu, X., Ma, P. American Journal of Physiology (2020): doi.org/10.1152/ajplung.00355.2020
    • Mass cytometry analysis of the NK cell receptor–ligand repertoire reveals unique differences between dengue-infected children and adults
      McKechnie, J.L., Beltrán, Davis., Ferreira, A-M. M. ImmunoHorizons (2020): doi.org/10.4049/immunohorizons.2000074
    • Augmenting emergency granulopoiesis with CpG conditioned mesenchymal stromal cells in murine neutropenic sepsis
      Ng, J., Guo, F., Marneth, A.E. Blood Advances (2020): doi.org/10.1182/bloodadvances.2020002556
    • Salmonella enterica serovar Typhi exposure elicits ex vivo cell-type-specific epigenetic changes in human gut cells
      Sztein, M.B., Bafford, A.C., Salerno-Goncalves, R. Scientific Reports (2020): doi.org/10.1101/cshperspect.a029546
    • Innate and adaptive immune correlates of chronic and self-limiting Epstein-Barr Virus (EBV) DNAemia in solid-organ transplant recipients
      Ferreira, V.H., Batist, J., Humar, A. Transplantation (2020): DOI: 10.1097/TP.0000000000003130
    • IRF5 promotes influenza-induced inflammatory responses in human iPSC-derived myeloid cells and murine models
      Forbester, J.L., Clement, M., Wellington, D. Journal of Virology (2020): e00121-20
    • T-bet+ memory B vells link to local cross-reactive IgG upon human rhinovirus infection
      Eccles, J.D., Turner, R.B., Kirk, N.A. Cell Reports (2020): doi.org/10.1016/j.celrep.2019.12.027
    • A human circulating immune cell landscape in aging and COVID-19
      Zheng, Y., Liu, X., Le, W. Protein & Cell (2020): doi.org/10.1007/s13238-020-00762-2
    • Complex autoinflammatory syndrome unveils fundamental principles of JAK1 kinase transcriptional and biochemical function
      Gruber, C.N., Calis, J. J. A., Buta, S. Immunity (2020): doi.org/10.1016/j.immuni.2020.07.006
    • Systems biological assessment of immunity to mild versus severe COVID-19 infection in humans
      Arunachalam, P.S., Wimmers, F., Mok, C. K. P. Science (2020): DOI: 10.1126/science.abc6261
    • Rapidly expanded partially HLA DRB1–matched fungus-specific T cells mediate in vitro and in vivo antifungal activity
      Castellellano-González, G., McGuire, H.M., Luciani, F. Blood Advances (2020): doi.org/10.1182/bloodadvances.2020001565
    • Genetically detoxified pertussis toxin displays near identical structure to its wild-type and exhibits robust immunogenicity.
      Ausar, S.F., Zhu, S., Duprez, J. Communications Biology (2020): doi.org/10.1038/s42003-020-01153-3
    • Suppressive myeloid cells are a hallmark of severe COVID-19
      Schulte-Shrepping, J., Reusch, N., Paclik, D. Cell (2020): doi.org/10.1016/j.cell.2020.08.001
    • Programing of an intravascular immune firewall by the gut microbiota protects against pathogen dissemination during infection
      McDonald, B., Zucoloto, A.Z., Yu, I.L. Cell Host & Microbe (2020): DOI: 10.1016/j.chom.2020.07.014
    • High-dimensional immune profiling by mass cytometry revealed immunosuppression and dysfunction of immunity in COVID-19 patients
      Wang, W., Su, B., Pang, L. Cellular & Molecular Immunology (2020): doi.org/10.1016/S1473-3099
    • SARS-CoV-2-specific T cells exhibit unique features characterized by robust helper function, lack of terminal differentiation, and high proliferative potential
      Neidleman, J., Luo, X., Frouard, J. Cell Reports Medicine (2020): doi: 10.1016/j.xcrm.2020.100081
    • Impaired type I interferon activity and inflammatory responses in severe COVID-19 patients
      Hadjadj, J., Yatim, N., Barnabei, L. Science (2020): DOI: 10.1126/science.abc6027
    • Immunocyte single cell analysis of vaccine‐induced narcolepsy
      Lind, A., Salami, F., Landtblom, A.M. European Journal of Immunology (2020): doi.org/10.1002/eji.202048633
    • Effects of hepatitis B surface antigen on virus-specific and global T cells in patients with chronic HBV infection
      Le Bert, N., Gill, U.S., Hong, M. et al. Gastroenterology (2020): 30492-3.
    • Transplantation of ACE2- mesenchymal stem cells improves the outcome of patients with COVID-19 pneumonia
      Leng, Z., Zhu, R., Hou, W. et al. Aging and Disease (2020): 216–228
    • Single cell immune profiling of dengue virus patients reveals intact immune responses to Zika virus with enrichment of innate immune signatures
      Zhao, Y., Amodio, M., Vander Wyk, B. et al. PLOS Neglected Tropical Diseases (2020): DOI: 10.1371/journal.pntd.0008112
    • The FluPRINT dataset, a multidimensional analysis of the influenza vaccine imprint on the immune system
      Tomic, A., Tomic, I., Dekker, C.L. et al. Scientific Data (2019): 214
    • B cell profiling in malaria reveals expansion and remodelling of CD11c+ B cell subsets
      Sundling, C., Rönnberg, C., Yman, V. et al. JCI Insight (2019): 126492
    • Molecular signatures of dengue virus-specific IL-10/IFN-γ co-producing CD4 T cells and their association with dengue disease
      Tian, Y., Seumois, G., De-Oliveira-Pinto, L.M. et al. Cell Reports (2019): 4482-4495.e4
    • Large-scale HLA tetramer tracking of T cells during dengue infection reveals broad acute activation and differentiation into two memory cell fates
      Chng, M.H.Y., Lim, M.Q., Rouers, A., et al. Immunity (2019): 1,119-1,135.e5
    • Mass cytometry analysis reveals complex cell-state modifications of blood myeloid cells during HIV infection
      Coindre, S., Tchitchek, N., Alaoui, L. et al. Frontiers in Immunology (2019): doi: 10.3389/fimmu.2019.02677
    • A multi-cohort study of the immune factors associated with M. tuberculosis infection outcomes
      Roy Chowdhury, R., Vallania, F., Yang, Q. et al. Nature (2018): 644–48
    • Dengue-specific CD8+ T cell subsets display specialized transcriptomic and TCR profiles
      Tian, Y., Babor, M., Lane, J. et al. Journal of Clinical Investigation (2019): 1,727–41
    • Pregnancy-induced alterations in NK cell phenotype and function
      Le Gars, M., Seiler, C., Kay, A.W. et al. Frontiers in Immunology (2019): 10.3389/fimmu.2019.02469
    • Characterization of leukocytes from HIV-ART patients using combined cytometric profiles of 72 cell markers
      Pereira, A.L., Tchitchek, N., Lambotte, O. et al. Frontiers in Immunology (2019): 1,777
    • Lymph node migratory dendritic cells modulate HIV-1 transcription through PD-1 engagement
      Banga, R., Rebecchini, C., Procopio, F.A. et al. PLOS Pathogens (2019): 10.1371/journal.ppat.1007918
    • Individual liver plasmacytoid dendritic cells are capable of producing IFNα and multiple additional cytokines during chronic HCV infection
      Doyle, E.H., Rahman, A., Aloman, C. et al. PLOS Pathogens (2019): doi: 10.1371/journal.ppat.1007935
    • Innate and adaptive nasal mucosal immune responses following experimental human pneumococcal colonization
      Jochems, S.P., de Ruiter, K., Solórzano, C. et al. Journal of Clinical Investigation (2019): doi: 10.1172/JCI128865
    • Differential induction of IFN-α and modulation of CD112 and CD54 expression govern the magnitude of NK cell IFN-γ response to influenza A viruses
      Kronstad, L.M., Seiler, C., Vergara, R. et al. Journal of Immunology (2018): 2,117-2,131
    • An optimized and validated method for isolation and characterization of lymphocytes from HIV+ human gut biopsies
      Trapecar, M., Khan, S., Roan, N.R., et al. AIDS Research and Human Retroviruses (2017): S31–S39.
    • Host sirtuin 1 regulates mycobacterial immunopathogenesis and represents a therapeutic target against tuberculosis
      Cheung, C.Y., Gutierrez, N.M., Marzuki, M.B. et al. Science Immunology (2017): eaaj1789
    • Life-threatening primary varicella zoster virus infection with haemophagocytic lymphohistiocytosis-like disease in GATA2 haploinsufficiency accompanied by expansion of double negative T-lymphocyte
      Prader, S., Felber, M., Volkmer, B. et al. Frontiers in Immunology (2018): doi: 10.3389/fimmu.2018.02766
    • Mass cytometry reveals the immaturity of circulating neutrophils during SIV infection
      Lemaitre,J., Cosma, A., Desjardins, D. et al. Journal of Innate Immunity (2019): doi: 10.1159/000499841
    • PD1+CCR2+CD8+ T cells infiltrate the central nervous system during acute Japanese Encephalitis Virus infection
      Zhang, F., Qi, L., Li, X. et al. Virologica Sinica (2019): 1-11
    • Altered monocyte and NK cell phenotypes correlate with post-trauma infection
      Seshadri, A., Brat, G.A., Yorkgitis, B.K. et al. Journal of Trauma and Acute Care Surgery (2019): doi: 10.1097/TA.0000000000002264
    • Human natural killer cells mediate adaptive immunity to viral antigens
      Nikzad, R., Angelo, L.S., Aviles-Padilla, K. et al. Journal of Science Immunology (2019): eaat8116
    • Distinct phenotype and function of circulating Vδ1+ and Vδ2+ γδT-cells in acute and chronic hepatitis B
      Chang, K.M, Traum, D., Park, J.J. et al. PLOS Pathogens (2019): e1007715
    • Aedes aegypti AgBR1 antibodies modulate early Zika virus infection of mice
      Uraki, R., Hastings, A.K., Marin-Lopez, A. et al. Nature Microbiology (2019): doi: 10.1038/s41564-019-0385-x
    • Diversity of Salmonella Typhi-responsive CD4 and CD8 T cells before and after Ty21a typhoid vaccination in children and adults
      Rudolph, M.E., McArthur, M.A., Magder, L.S. et al. International Immunology (2019): doi: 10.1093/intimm/dxz011
    • Age-Associated Heterogeneity of Ty21a-Induced T Cell Responses to HLA-E Restricted Salmonella Typhi Antigen Presentation
      Rudolph, M.E., McArthur, M.A., Magder, L.S. et al. Frontiers in Immunology (2019): doi: 10.3389/fimmu.2019.00257
    • Identification of NK Cell Subpopulations That Differentiate HIV-Infected Subject Cohorts with Diverse Levels of Virus Control
      Pohlmeyer, C.W., Gonzalez, V.D., Irrinki, A. et al. Journal of Virology (2019): doi: 10.1128/JVI.01790-18
    • A functional subset of CD8+ T cells during chronic exhaustion is defined by SIRPα expression
      Myers, L.M., Tal, M.C., Torrez Dulgeroff, L.B. et al. Nature Communications (2019): 794
    • Upregulation of Chitinase I in alveolar macrophages of HIV-infected smokers
      Logue, E.C., Neff, C.P., Mack, D.G. et al. Journal of Immunology (2019): 1,363-72
    • Metformin alters human host responses to Mycobacterium tuberculosis in healthy subjects
      Lachmandas, E., Eckold, C., Böhme, J. et al. Journal of Infectious Diseases (2019): doi: 10.1093/infdis/jiz064
    • High-Dimensional Characterization of IL-10 Production and IL-10–Dependent Regulation during Primary Gammaherpesvirus Infection
      Kimball, A.K., Oko, L.M., Kaspar, R.E. et al. ImmunoHorizons (2019): 94-109
    • Multifactorial heterogeneity of virus-specific T cells and association with the progression of human chronic hepatitis B infection
      Cheng, Y., Zhu, Y.O., Becht, E. et al. Science Immunology (2019): doi: 10.1126/sciimmunol.aau6905
    • Mass cytometry identifies distinct CD4+ T cell clusters distinguishing HIV-1-infected patients according to antiretroviral therapy initiation
      Bekele, Y., Lakshmikanth, T., Chen, Y. et al. JCI Insight (2019): doi: 10.1172/jci.insight.125442
    • Allogeneic BK Virus-Specific T Cells for Progressive Multifocal Leukoencephalopathy
      Muftuoglu, M., Olson, A., Marin, D. et al. New England Journal of Medicine (2018): 1,443–51
    • CD32+ and PD-1+ Lymph Node CD4 T Cells Support Persistent HIV-1 Transcription in Treated Aviremic Individuals
      Noto, A., Procopio, F.A., Banga, R. et al. Cell (2018): doi: 10.1128/JVI.00901-18
    • IL-15 regulates susceptibility of CD4+ T cells to HIV infection
      Manganaro, L. Hong, P., Hernandez, M.M. et al. PNAS (2018): E9659-67
    • Identification of functionally primitive and immunophenotypically distinct subpopulations in secondary acute myeloid leukemia by mass cytometry
      Bandyopadhyay, S., Fowles, J.S., Yu, L. et al. Cytometry Part B: Clinical Cytometry (2018): doi: 10.1002/cyto.b.21743
    • Identification of enhanced IFN-γ signaling in polyarticular juvenile idiopathic arthritis with mass cytometry
      Throm, A.A., Moncrieffe, H., Orandi, A.B. et al. JCI Insight (2018): e121544
    • Application and utility of mass cytometry in vaccine development
      Reeves, P.M., Sluder, A.E., Paul, S.R. et al. FASEB Journal (2018): 5–15
    • Anti-α4β7 therapy targets lymphoid aggregates in the gastrointestinal tract of HIV-1–infected individuals
      Uzzan, M., Tokuyama, M., Rosenstein, A.K. et al. Science Translational Medicine (2019): 461
    • A large, international study on post-transplant glomerular diseases: the TANGO project
      Uffing, A., José Pérez-Sáez, M., La Manna, G. et al. BMC Nephrology (2018): 229
    • Comprehensive innate immune profiling of chikungunya virus infection in pediatric cases
      Michlmayr, D., Pak, T.R., Rahman, A.H. et al. Molecular Systems Biology (2018): e7862
    • Role of immune aging in susceptibility to West Nile virus
      Yao, Y., Montgomery, R.R. Methods in Molecular Biology (2016): 235–47
    • The natural killer cell response to West Nile virus in young and old individuals with or without a prior history of infection
      Yao, Y., Strauss-Albee, D.M., Zhou, J.Q. et al. PLoS One (2017): e0172625
    • Impact of CD4+ T Cell Responses on Clinical Outcome following Oral Administration of Wild-Type Enterotoxigenic Escherichia coli in Humans
      McArthur, M.A., Chen, W.H., Magder, L. et al. PLoS Neglected Tropical Diseases (2017): e0005291
    • Combinatorial tetramer staining and mass cytometry analysis facilitate T-cell epitope mapping and characterization
      Newell, E.W., Sigal, N., Nair, N. et al. Nature Biotechnology (2013): 623–9
    • The Split Virus Influenza Vaccine rapidly activates immune cells through Fcγ receptors
      O'Gorman, W.E., Huang, H., Wei, Y.L. et al. Vaccine (2014): 5,989–97
    • High-dimensional immune profiling of total and rotavirus VP6-specific intestinal and circulating B cells by mass cytometry
      Nair, N., Newell, E.W., Vollmers, C. et al. Mucosal Immunology (2015): 68–82
    • Activation of Salmonella Typhi-Specific Regulatory T Cells in Typhoid Disease in a Wild-Type S. Typhi Challenge Model
      McArthur, M.A., Fresnay, S., Magder, L.S. et al. PLoS Pathogens (2015): e1004914
    • Brief Report: Chikungunya viral arthritis in the United States: A mimic of seronegative rheumatoid arthritis
      Miner, J.J., Aw Yeang, H.X., Fox, J.M. et al. Arthritis and Rheumatology (2015): 1,214–20
    • A human vaccine strategy based on chimpanzee adenoviral and MVA vectors that primes, boosts, and sustains functional HCV-specific T cell memory
      Swadling, L., Capone, S., Antrobus, R.D. et al. Science Translational Medicine (2014): 261ra153
    • Cytometry by time-of-flight shows combinatorial cytokine expression and virus-specific cell niches within a continuum of CD8+ T cell phenotypes
      Newell, E.W., Sigal, N., Bendall, S.C. et al. Immunity (2012): 142–52
    • Identification of vaccine-altered circulating B cell phenotypes using mass cytometry and a two-step clustering analysis
      Pejoski, D., Tchitchek, N., Rodriguez, P. A. et al. The Journal of Immunology (2016): 4,814–31
    • FHL2 Regulates Natural Killer Cell Development and Activation during Streptococcus pneumoniae Infection
      Baranek, T., Morello, E., Valayer, A. et al. Frontiers in Immunology (2017): 123
    • Single cell mass cytometry reveals remodeling of human T cell phenotypes by varicella zoster virus
      Sen, N., Mukherjee, G., Arvin, A.M. Methods (2015): 85–94
    • High-dimensional CyTOF® analysis of dengue virus-infected human DCs reveals distinct viral signatures
      Hamlin, R.E., Rahman, A., Pak, T.R. et al. Journal of Clinical Investigation Insight (2017): e92424
    • Hepatitis B virus–specific T cells associate with viral control upon nucleos(t)ide-analogue therapy discontinuation
      Rivino, L., Le Bert, N., Gill, U.S. et al. Journal of Clinical Investigation (2018): 668–81
    • Mass cytometric analysis of HIV entry, replication, and remodeling in tissue CD4+ T cells
      Cavrois, M., Banerjee, T., Mukherjee, G. et al. Cell Reports (2017): 984–98
    • Baseline immune profile by CyTOF can predict response to an investigational adjuvanted vaccine in elderly adults
      Lingblom, C.M.D., Kowli, S., Swaminathan, N. et al. Journal of Translational Medicine (2018): 153
    • Adaptive NKG2C+CD57+ Natural Killer Cell and Tim-3 Expression During Viral Infections
      Kared, H., Martelli, S., Tan, S.W. et al. Frontiers in Immunology (2018): 686
    • Mass Cytometry Analysis Reveals the Landscape and Dynamics of CD32a+ CD4+ T Cells From Early HIV Infection to Effective cART
      Coindre, S., Tchichek, N., Alaoui, L. et al. Frontiers in Immunology (2018): doi: 10.3389/fimmu.2018.01217
    • In-depth phenotypic characterization of reticulocyte maturation using mass cytometry
      Thomson-Luque, R., Wang, C., Ntumngia, F.B. et al. Blood Cells, Molecules, and Diseases (2018): 22-33
    • Clonal analysis of Salmonella-specific effector T cells reveals serovar-specific and cross-reactive T cell responses
      Napolitani, G., Kurupati, P., Teng, K.W.W. et al. Nature Immunology (2018): doi: 10.1038/s41590-018-0133-z
    • Identification and characterization of HIV-specific resident memory CD8+ T cells in human lymphoid tissue
      Buggert, M., Nguyen, S., Salgado-Montes de Oca, G. et al. Science Immunology (2018): doi: 10.1126/sciimmunol.aar4526
    • High-Dimensional Analysis Delineates Myeloid and Lymphoid Compartment Remodeling during Successful Immune-Checkpoint Cancer Therapy
      Gubin, M.M., Esaulova, E., Ward, J.P. et al. Cell (2018): doi: 10.1016/j.cell.2018.09.030
    • Pushing the frontiers of T-cell vaccines: accurate measurement of human T-cell responses
      Saade, F., Gorski, S.A., Petrovsky, N. Expert Review of Vaccines (2012): 1,459–70

  • Liquid Biopsy

    • Multiplex protein detection on circulating tumor cells from liquid biopsies using Imaging Mass Cytometry
      Gerdtsson, E., Pore, M., Thiele, J.A. et al. Convergent Science Physical Oncology (2018): 015002

  • Method Development

    • Utilising mass cytometry with CD45 barcoding and standardised leucocyte phenotyping for immune trajectory assessment in critically ill patients
      Fish, M., Ellis, R., Bishop, C. British Journal of Anaesthesia (2021): doi.org/10.1016/j.bja.2021.01.006
    • Alternative methods of viability determination in single cell mass cytometry
      Devine, R.D., Alkhalaileh, H. S., Lyberger, J. M. Cytometry A (2021): doi.org/10.1002/cyto.a.24308
    • Mass-tag barcoding for multiplexed analysis of human synaptosomes and other anuclear events
      Gajera, C. R., Fernandez , R., Montine, K.S. Cytometry Part A : The Journal of the International Society for Analytical Cytology (2021): doi.org/10.1002/cyto.a.24340
    • Training novices in generation and analysis of high‐dimensional human cell phospho‐flow cytometry data
      Roe, C.E., Hayes, M. J., Barone, S. M. et al. Current Protocols in Cytometry (2020): DOI: 10.1002/cpcy.71
    • High-throughput mass cytometry staining for immunophenotyping clinical samples
      Thrash, E.M., Kleinsteuber, K., Hathaway, E.S. et al. STAR Protocols (2020): doi.org/10.1016/j.xpro.2020.100055
    • Toward high‐dimensional single‐cell analysis of graphene oxide biological impact: tracking on immune cells by single‐cell mass cytometry
      Orrecchioni, M., Bordoni, V., Fuoco, C. et al. Small (2020): DOI: 10.1002/smll.202000123
    • High-throughput single-cell analysis of exosome mediated dual drug delivery, in vivo fate and synergistic tumor therapy
      Wang, J., Li, G., Tu, C. et al. Nanoscale (2020): DOI: 10.1039/d0nr02344b
    • Multiplexed probing of proteolytic enzymes using mass cytometry-compatible activity-based probes
      Poreba, M., Groborz , K. M., Rut, W. et al. Journal of American Chemical Society (2020): DOI: 10.1021/jacs.0c06762
    • Stabilization of human whole blood samples for multi‐center and retrospective immunophenotyping studies
      Rybakowska, P., Burbano, C., Gassen, S. V. et al. Cytometry Part A (2020): DOI: 10.1002/cyto.a.24241
    • Enabling indium channels for mass cytometry by using reinforced cyclam-based chelating polylysine
      Grenier, L., Beyler, M., Closson, T. Bionconjugate Chemistry (2020): DOI: 10.1021/acs.bioconjchem.0c00267
    • Nonspecific binding correction for single-cell mass cytometric analysis of autophagy and myoblast differentiation
      Brown, H.M.G, Kuhns, M. M., Maxwel, Z. et al. Analytical Chemistry (2020): doi.org/10.1021/acs.analchem.0c03211
    • Single cell detection of the p53 protein by mass cytometry
      Fagerholt, O.H.E., Hellesøy, M., Gullaksen , S. E. Cancers (2020): doi.org/10.3390/cancers12123699
    • Metal-encoded polystyrene microbeads as a mass cytometry calibration/normalization standard covering channels from yttrium (89 amu) to bismuth (209 amu)
      Liu, J., Jarzabek, J., Majonis, D. Analytical Chemistry (2020): 999-1,006
    • Mass cytometric study on the heterogeneity in cellular association and cytotoxicity of silver nanoparticles in primary human immune cells
      Ha, M.K., Choi, J.-S., Kwon, S.J. Environmental Science: Nano (2020): 1102-1114.
    • Platelet mass cytometry: Optimization of sample, reagent, and analysis parameters
      Spurgeon, B.E., Michelson, A. D., Frelinger, A. L. Cytometry Part A (2021): doi: 10.1002/cyto.a.24300
    • Network for biomarker immunoprofiling for cancer immunotherapy: Cancer Immune Monitoring and Analysis Centers and Cancer Immunologic Data Commons (CIMAC-CIDC)
      Chen, H.X., Song, M., Maecker, H. T. Clinical Cancer Research (2021): DOI: 10.1158/1078-0432.CCR-20-3241
    • Immunophenotyping and intracellular staining of fixed whole blood for mass cytometry (CyTOF)
      Kowli, S., Maecker, H. Bio-101 (2020): DOI:10.21769/BioProtoc.5004
    • Effects of processing conditions on stability of immune analytes in human blood
      Gottfried-Blackmore, A., Rubin, S. J. S., Bai, L. Scientific Reports (2020): doi.org/10.1038/s41598-020-74274-8
    • Tantalum oxide nanoparticle-based mass tag for mass cytometry
      Zhang, Y., Zabinyakov, N., Majonis, D. Analytical Chemistry (2020): doi: 10.1021/acs.analchem.9b04970
    • Heterogenous Internalization of Nanoparticles at Ultra-Trace Concentration in Environmental Individual Unicellular Organisms Unveiled by Single-Cell Mass Cytometry
      Wu, Q., Shi, J., Ji, X. ACS Nano (2020): DOI: 10.1021/acsnano.0c03587
    • Application of an activity-based probe to determine proteolytic activity of cell surface cathepsin G by mass cytometry data acquisition
      Gärtner, F., Knippschild, U., Burster, T. ACS Omega (2020): doi.org/10.1021/acsomega.0c04092
    • Loading of metal isotope-containing intercalators for mass cytometry-based high-throughput quantitation of exosome uptake at the single-cell level
      Wang, J., Tu, C., Zhang, H. Biomaterials (2020): DOI: 10.1016/j.biomaterials.2020.120152
    • Graphene, other carbon nanomaterials and the immune system: toward nanoimmunity-by-design
      Gazzi, A., Fusco, L., Orecchioni, M. JPhys Materials (2020): DOI: 10.1182/blood.2020006619
    • Kupffer cell characterization by mass cytometry
      Blériot, C.,Li, S.,Newell, E. Methods in Molecular Biology (2020): DOI: 10.1007/978-1-0716-0704-6_10
    • Labeling antibodies using europium
      Berg, E.A.,Fishman, J. B. Cold Spring Harbor Protocols (2020): DOI: 10.1101/pdb.prot099325
    • Engineering of nebulized metal–phenolic capsules for controlled pulmonary deposition for controlled pulmonary deposition
      Ju, Y., Cortez-Jugo, C., Chen, J. et al. Advanced Science (2020): 1902650.
    • Mass cytometry and single‐cell RNA‐seq profiling of the heterogeneity in human peripheral blood mononuclear cells interacting with silver nanoparticles
      Ha, M.K., Kwon, S.J., Choi, J.-S. et al. Small (2020): e1907674.
    • A carrier strategy for mass cytometry analysis of small numbers of cells
      Jia, X., Zhou, X., Zheng, H. et al. Methods in Molecular Biology (2020): 21-33
    • Macromolecular approach for targeted radioimmunotherapy in non-Hodgkin's lymphoma
      Hee, C., Ho, D., Karton, A., et al. Chemical Communications (2019): 14,506-14,509
    • Signal amplification for Imaging Mass Cytometry
      Rana, R., Gómez-Biagi, R.F., Bassan, J., et al. Bioconjugate Chemistry (2019): 2,805-2,810
    • Ratiometric Barcoding for Mass Cytometry
      Wu, X., DeGottardi, Q., Wu, I.C. et al. Analytical Chemistry (2018): 10,688–94
    • Quantifying Heterogeneity of Individual Organelles in Mixed Populations via Mass Cytometry
      Brown, H.M.G., Arriaga, E.A. Analytical Chemistry (2018): 13,315–21
    • Method for tagging antibodies with metals for mass cytometry experiments
      Chang, S.G. and Guidos, C.J. Mass Cytometry: Methods and Protocols (2019): 47–54
    • Multiplexed profiling of RNA and protein expression signatures in individual cells using flow or mass cytometry
      Duckworth, A.D., Gherardini, P.F., Sykorova, M. et al. Nature Protocols (2019): 901–20
    • Quantitative measurement of cell-nanoparticle interactions using mass cytometry
      Mitchell, A.J., Ivask, A., and Ju, Y. Mass Cytometry: Methods and Protocol (2019): 227–41
    • Lanthanide nanoparticles for high sensitivity multiparameter single cell analysis
      Pichaandi, J., Zhao, G., Bouzekri, A. et al. Chemical Science (2019): 2,965–74
    • Scalable conjugation and characterization of immunoglobulins with stable mass isotope reporters for single-cell mass cytometry analysis
      Hartmann, F.J., Simonds, E.F., Vivanco, N. et al. Mass Cytometry: Methods and Protocols (2019): 55–81
    • Significant interference in mass cytometry from medicinal iodine in human lung
      Keller, B.C., Presti, R.M., Byers, D.E. et al. American Journal of Respiratory Cell and Molecular Biology (2016): 150–1
    • Surface barcoding of live PBMC for multiplexed mass cytometry
      Schulz, A.R. and Mei, H.E. Mass Cytometry: Methods and Protocols (2019): 93–108
    • Automated cell processing for mass cytometry experiments
      Mikes, J., Olin, A., Lakshmikanth, T. et al. Mass Cytometry: Methods and Protocols (2019): 111–23
    • Clickable and High-Sensitivity Metal-Containing Tags for Mass Cytometry
      Allo, B., Lou, X., Bouzekri, A.. et al. Bioconjugate Chemistry (2018): 2,028–38
    • High-parameter immune profiling with CyTOF
      Sahaf, B., Rahman, A., Maecker, H.T. et al. Biomarkers for Immunotherapy of Cancer (2019): 351–68.
    • Live cell barcoding for efficient analysis of small samples by mass cytometry
      Wagar, L.E. Mass Cytometry: Methods and Protocols (2019): 125–35
    • A β-galactosidase probe for the detection of cellular senescence by mass cytometry
      Lumba, M.A., Willis, L.M., Santra, S. et al. Organic & Biomolecular Chemistry (2017): 6,388–92
    • Titration of mass cytometry reagents
      van Vreden, C., Niewold, P., McGuire, H.M. et al. Mass Cytometry: Methods and Protocols (2019): 83–92
    • Simultaneous determination of proteins using an element-tagged immunoassay coupled with ICP-MS detection
      Quinn, Z.A., Baranov, V.I., Tanner, S.D. et al. Journal of Analytical Atomic Spectrometry (2002): 892–96
    • Multiplex MHC class I tetramer combined with intranuclear staining by mass cytometry
      Simoni, Y., Fehlings, M., and Newell, E.W. Mass Cytometry: Methods and Protocols (2019): 147–58.
    • Single-Cell Mass Cytometry of Archived Human Epithelial Tissue for Decoding Cancer Signaling Pathways
      Scurrah, C.R., Simmons, A.J., Lau, K.S. Methods in Molecular Biology (2018): 215–29
    • Mass cytometry enables absolute and fast quantification of silver nanoparticle uptake at the single cell level
      López-Serrano, O.A., Haase, A., Peddinghaus, A. et al. Analytical Chemistry (2019): 11,514–19.
    • Immunophenotyping by mass cytometry
      Behbehani, G.K. Methods in Molecular Biology (2019): 31–51
    • Platelet surface marker analysis by mass cytometry
      Blair, T.A. and Frelinger, A.L. Platelets (2019): 1–8
    • Staining of phosphorylated signalling markers protocol for mass cytometry
      Shinko, D., Ashhurst, T.M., McGuire, H.M. et al. Mass Cytometry: Methods and Protocols (2019): 139–46
    • Whole blood preservation methods alter chemokine receptor detection in mass cytometry experiments
      Sakkestad, S.T., Skavland, J., and Hanevik, K. Journal of Immunological Methods (2019): doi: 10.1016/j.jim.2019.112673
    • A Modified Injector and Sample Acquisition Protocol Can Improve Data Quality and Reduce Inter‐Instrument Variability of the Helios Mass Cytometer
      Lee, B.H., Kelly, G., Bradford, S. et al. Cytometry Part A (2019): 1,019–30
    • Highly stable and inert complexation of Indium(III) by reinforced cyclam dipicolinate and a bifunctional derivative for bead encoding in mass cytometry
      Grenier, L., Beyler, M., Platas-Iglesias, C. et al. Chemistry (2019): doi: 10.1002/chem.201903969
    • DNA-conjugated gold nanoparticles as high-mass probes in Imaging Mass Cytometry
      Malile, B., Brkic, J., Bouzekri, A. et al. ACS Applied Bio Materials (2019): doi: 10.1021/acsabm.9b00574
    • A metal-chelating polymer for chelating zirconium and its use in mass cytometry
      Cho, H., Liu, P., Pichaandi, J. et al. European Polymer Journal (2019): doi: 10.1016/j.eurpolymj.2019.08.002
    • Glutathione might attenuate cadmium-induced liver oxidative stress and hepatic stellate cell activation
      Ren, L., Qi, K., Zhang, L. et al. Biological Trace Element Research (2019): 443-452.
    • Multidimensional profiling of drug‐treated cells by Imaging Mass Cytometry
      Bouzekri, A., Esch, A., and Ornatsky, O. FEBS Open Bio (2019): doi:10.1002/2211-5463.12692
    • An updated debarcoding tool for mass cytometry with cell type-specific and cell sample-specific stringency adjustment
      Fread, K.I., Strickland, W.D., Nolan, G.P. et al. Pacific Symposium on Biocomputing (2017): 588-598
    • Analytical figures of merit for a novel tissue imaging system
      Straus, R.N., Carew, A., Sandkujil, D. et al. Journal of Analytical Atomic Spectrometry (2017): 1,044–51
    • Sample preparation for mass cytometry analysis
      McCarthy, R.L., Duncan, A.D., and Barton, M.C. Journal of Visualized Experiments (2017): 54394
    • Rapid monoisotopic cisplatin based barcoding for multiplexed mass cytometry
      McCarthy, R.L., Mak, D.H., Burks, J.K. et al. Scientific Reports (2017): 3,779
    • Single cell level quantification of nanoparticle-cell interactions using mass cytometry
      Ivask, A., Mitchell, A.J., Hope, C.M. et al. Analytical Chemistry (2017): 8,228-8,232
    • Self-assembled nanoparticles from phenolic derivatives for cancer therapy
      Dai, Y., Guo, J., Wang, T.Y. et al. Advanced Healthcare Materials (2017): 1700467
    • Imaging Mass Cytometry
      Chang, Q., Ornatsky, O.I., Siddiqui, I. et al. Cytometry Part A (2017): 160–9
    • Ruthenium Counterstaining for Imaging Mass Cytometry
      Catena, R., Montuenga, L.M., Bodenmiller, B. Journal of Pathology (2018): 479–84
    • Multiplexed protease assays using element-tagged substrates
      Lathia, U.S., Ornatsky, O., Baranov, V., Nitz, M. Analytical Biochemistry (2011): 157–9
    • Development of inductively coupled plasma-mass spectrometry-based protease assays
      Lathia, U.S., Ornatsky, O., Baranov, V., Nitz, M. Analytical Biochemistry (2010): 93–8
    • ICP-MS-based multiplex profiling of glycoproteins using lectins conjugated to lanthanide-chelating polymers
      Leipold, M.D., Herrera, I., Ornatsky, O. et al. Journal of Proteome Research (2009): 443–9
    • Mass cytometric cell cycle analysis
      Behbehani, G. Mass Cytometry: Methods and Protocols (2019): 193-215
    • Unlabeled competitor antibody to reduce nonlinear signal spillover in mass cytometry
      Sekhri,P., Kim, M.Y., and Behbehani,G.K. Cytometry Part A (2019): doi: 10.1002/cyto.a.23793
    • Stabilizing antibody cocktails for mass cytometry
      Schulz,A.R., Baumgart,S., Schulze,J. et al. Cytometry Part A (2019): doi: 10.1002/cyto.a.23781.
    • Evaluation of mass cytometry in the clinical laboratory
      Ravkov, E.V., Charlton,C.M., Barker, A.P. et al. Cytometry Part B Clinical Cytometry (2019): doi:10.1002/cyto.b.21791
    • Titrating complex mass cytometry panels
      Gullaksen, S.E., Bader, L., Hellesoy, M. et al. Cytometry Part A (2019): doi: 10.1002/cyto.a.23751
    • Isolation and staining of mouse skin keratinocytes for cell cycle specific analysis of cellular protein expression by mass cytometry
      Fernandez, J. and Torchia, E.C. Journal of Visual Experiments (2019): doi:10.3791/59353
    • Osmium-labeled microspheres for bead-based assays in mass cytometry
      Budzinski, L., Schulz, A.R., Baumgart, S. et al. Journal of Immunology (2019): 3,103–3,112
    • TePhe, a tellurium-containing phenylalanine mimic, allows monitoring of protein synthesis in vivo with mass cytometry
      Bassan, J., Willis, L.M. Vellanki, R.N. et al. Proceedings of the National Academy of Sciences (2019): doi: 10.1073/pnas.1821151116
    • Proliferation tracing with single-cell mass cytometry optimizes generation of stem cell memory-like T cells
      Good, Z., Borges, L., Vivanco Gonzalez, N. et al. Nature Biotechnology (2019): 259–66
    • The anatomy of single cell mass cytometry data
      Olsen, L.R., Leipold, M.D., Pedersen, C.B. et al. Cytometry Part A: Journal of the ISAC (2018): 156–72
    • Isotopologous Organotellurium Probes Reveal Dynamic Hypoxia In Vivo with Cellular Resolution
      Edgar, L.J., Vellanki, R.N., McKee, T.D. et al Angewandte Chemie International Edition (2016): 13,159–63
    • In-Depth Characterization of Monocyte-Derived Macrophages using a Mass Cytometry-Based Phagocytosis Assay
      Schulz, D., Severin, Y., Zanotelli, V.R.T. et al. Scientific Reports (2019): 1,925
    • Parallel analysis of tri-molecular biosynthesis with cell identity and function in single cells
      Kimmey, S.C., Borges, L., Baskar, R. et al. Nature Communications (2019):
    • Implementation of Mass Cytometry for Immunoprofiling of Patients with Solid Tumors
      Poláková, I., Pelák, O., Thürner, D. et al. Journal of Immunology Research (2019): doi: 10.1155/2019/6705949
    • A mass-ratiometry-based CD45 barcoding methods for mass cytometry detection
      Meng, H., Warden, A., Zhang, L. et al. SLAS Technology (2019): doi: 10.1177/2472630319834057
    • Optimization of Receptor Occupancy Assays in Mass Cytometry: Standardization Across Channels with QSC Beads
      Bringeland, G.H., Bader, L., Blaser, N. et al. Cytometry Part A (2019): 314-22
    • Metal-isotope-tagged monoclonal antibodies for high-dimensional mass cytometry
      Han, G., Spitzer, M.H., Bendall, S.C. et al. Nature Protocols (2018): 2,121-48
    • Single-Cell Protein Assays: A Review
      Fan, B., Wang, J., Xu, Y. et al. Methods in Molecular Biology (2018): 293-309
    • Mass Spectrometry Imaging and Integration with Other Imaging Modalities for Greater Molecular Understanding of Biological Tissues
      Porta Siegel, T., Hamm, G., Bunch, J. et al. Molecular Imaging and Technology (2018): 888-901
    • Effect of storage time and temperature on cell cycle analysis by mass cytometry
      Devine, R.D., Sekhri, P., Behbehani, G.K. Cytometry Part A: Journal of the ISAC (2018): 1,141-9
    • Methods for high-dimensonal analysis of cells dissociated from cyropreserved synovial tissue
      Donlin, L., Rao, D., Wei, K. et al. Arthritis Research and Therapy (2018): 139
    • Protein Barcodes Enable High-Dimensional Single-Cell CRISPR Screens
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      Shaklee, J., Srivastava, K., Brown, H. et al. Scientific Reports (2018): 6,657
    • Lanthanide-coordinated semiconducting polymer dots used for flow cytometry and mass cytometry
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    • Cell cycle analysis by mass cytometry
      Behbehani, G.K. Methods in Molecular Biology (2017): 105–24
    • Synthetically modified viral capsids as versatile carriers for use in antibody-based cell targeting
      ElSohly, A.M., Netirojjanakul, C., Aanei, I.L. et al. Bioconjugate Chemistry (2015): 1,590–6
    • Mass cytometric analysis reveals viable activated caspase-3+ luminal progenitors in the normal adult human mammary gland
      Knapp, D.J.H.F., Kannan, N., Pellacani, D. et al. Cell Reports (2017): 1,116–26
    • A Universal Live Cell Barcoding-Platform for Multiplexed Human Single Cell Analysis
      Hartmann, F.J., Simonds, E.F., Bendall, S.C. Scientific Reports (2018): 10,770
    • Tellurium-based mass cytometry barcode for live and fixed cells
      Willis, L.M., Park, H., Watson, M.W.L. et al. Cytometry Part A: Journal of the ISAC (2018): doi: 10.1002/cyto.a.23495
    • Simultaneous Detection of Protein and mRNA in Jurkat and KG-1a Cells by Mass Cytometry
      Mavropoulos, A., Allo, B., He, M. et al. Cytometry Part A (2017): 1,200–8
    • Advances in Proteomic Techniques for Cytokine Analysis: Focus on Melanoma Research
      Skalnikova, H.K., Cizkova, J., Cervenka, J. et al. International Journal of Molecular Sciences (2017): 2,697
    • Multiplex peptide-MHC tetramer staining using mass cytometry for deep analysis of the influenza-specific T-cell response in mice
      Fehlings, M., Chakarov, S., Simoni, Y. et al. Journal of Immunological Methods (2017): 30–6
    • Aptamer-facilitated mass cytometry
      Mironov, G.G., Bouzekri, A., Watson, J. et al. Analytical and Bioanalytical Chemistry (2018): 3,047–51
    • Comparison of CyTOF^® assays across sites: results of a six-center pilot study
      Leipold, M.D., Obermoser, G., Fenwick, C. et al. Journal of Immunological Methods (2018): 37–43
    • Engineered Tumor-Targeted T Cells Mediate Enhanced Anti-Tumor Efficacy Both Directly and through Activation of the Endogenous Immune System
      Avanzi, M.P., Yeku, O., Li, X. et al. Cell Reports (2018): 2,130–41
    • Phenotyping of live human PBMC using CyTOF® mass cytometry
      Leipold, M.D., Maecker, H.T. Bio-protocol (2015): e1382
    • Automation of sample preparation for mass cytometry barcoding in support of clinical research: protocol optimization
      Nassar, A.F., Wisnewski, A.V., Raddassi, K. Analytical and Bioanalytical Chemistry (2017): 2,363–72
    • Cytometry-based single-cell analysis of intact epithelial signaling reveals MAPK activation divergent from TNF-α-induced apoptosis in vivo
      Simmons, A.J., Banerjee, A., McKinley, E.T. et al. Molecular Systems Biology (2015): 835
    • Cytokine-stimulated phosphoflow of PBMC using CyTOF® mass cytometry
      Fernandez, R., Maecker, H. Bio-protocol (2016): e1496
    • Atomic mass tag of bismuth-209 for increasing the immunoassay multiplexing capacity of mass cytometry
      Han, G., Chen, S-Y., Gonzalez, V.D. et al. Cytometry Part A (2017): 1,150–63
    • Mass cytometry moving forward in support of clinical research: advantages and considerations
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    • Research techniques made simple: experimental methodology for single-cell mass cytometry
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    • CyTOF® mass cytometry for click proliferation assays
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    • CyTOF® supports efficient detection of immune cell subsets from small samples
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    • Mass cytometry assays for antigen-specific T cells using CyTOF®
      Lin, D., Maecker, H.T. Flow Cytometry Protocols (2017): 37–47
    • Metallofluorescent nanoparticles for multimodal applications
      Delgado-Gonzalez, A., Garcia-Fernandez, E., Valero, T. et al. ACS Omega (2018): 144-53
    • An optimized method to measure human FOXP3+ regulatory T cells from multiple tissue types using mass cytometry
      Dawson, N.A.J., Lam, A.J., Cook, L. et al. European Journal of Immunology (2018): doi: 10.1002/eji.201747407
    • xCell: digitally portraying the tissue cellular heterogeneity landscape
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    • High-dimensional single-cell analysis with mass cytometry
      Brodie, T.M., Tosevksi, V. Current Protocols in Immunology (2017): 5.11.1–5.11.25
    • viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia
      Amir, el-A.D., Davis, K.L., Tadmor, M.D. et al. Nature Biotechnology (2013): 545–52
    • Silver nanoparticles for the detection of cell surface antigens in mass cytometry
      Schulz, A.R., Stanislawiak, S., Baumgart, S. et al. Cytometry Part A (2016): 25–33
    • Staining of Frozen and Formalin-Fixed, Paraffin-Embedded Tissues with Metal-Labeled Antibodies for Imaging Mass Cytometry Analysis
      Chang, Q., Ornatsky, O., Hedley, D. Current Protocols in Cytometry (2017): 12.47.1–12.47.8
    • High-throughput quantitation of inorganic nanoparticle biodistribution at the single-cell level using mass cytometry
      Yang, Y.S., Atukorale, P.U., Moynihan, K.D. et al. Nature Communications (2017): 14,069
    • Analysis of Signaling Networks at the Single-Cell Level Using Mass Cytometry
      Bandyopadhyay, S., Fischer, D.A.C., Malkova, O. et al. Methods in Molecular Biology (2017): 371–92
    • Preparing Viable Single Cells from Human Tissue and Tumors for Cytomic Analysis
      Leelatian, N., Doxie, D.B., Greenplate, A.R. et al. Current Protocols in Molecular Biology (2017): 25C.1.1–25C.1.23
    • Mass Cytometry for Detection of Silver at the Bacterial Single Cell Level
      Guo, Y., Baumgart, S., Stärk, H.J. et al. Frontiers in Microbiology (2017): 1,326
    • Dual-labelled antibodies for flow and mass cytometry: A new tool for cross-platform comparison and enrichment of target cells for mass cytometry
      Baumgart, S., Schulz, A.R., Peddinghaus, A. et al. European Journal of Immunology (2017): 1,377–85
    • Optimization of mass cytometry sample cryopreservation after staining
      Sumatoh, H.R., Teng, K.W., Cheng, Y. et al. Cytometry Part A (2017): 48–61
    • Influence of node abundance on signaling network state and dynamics analyzed by mass cytometry
      Lun, X.K., Zanotelli, V.R., Wade, J.D. et al. Nature Biotechnology (2017): 164–72
    • Liposome-Encapsulated NaLnF4 Nanoparticles for Mass Cytometry: Evaluating Nonspecific Binding to Cells
      Pichaandi, J., Tong, L., Bouzekri, A. et al. Chemistry of Materials (2017): 4,980–90
    • Categorizing Cells on the Basis of their Chemical Profiles: Progress in Single-Cell Mass Spectrometry
      Comi, T.J., Do, T.D., Rubakhin, S.S. et al. Journal of the American Chemical Society (2017): 3,920–9
    • Next generation ligand binding assays—review of emerging technologies’ capabilities to enhance throughput and multiplexing
      Mora, J., Chunyk, A.G., Dysinger, M. et al. American Association of Pharmaceutical Scientists Journal (2014): 1,175–84
    • AutoGate: automating analysis of flow cytometry data
      Meehan, S., Walther, G., Moore, W. et al. Immunologic Research (2014): 218–23
    • COMPASS identifies T-cell subsets correlated with clinical outcomes
      Lin, L., Finak, G., Ushey, K. et al. Nature Biotechnology (2015): 610–6
    • Review of methods to probe single cell metabolism and bioenergetics
      Vasdekis, A.E., Stephanopoulos, G. Metabolic Engineering (2015): 115–35
    • The influence of PEG macromonomers on the size and properties of thermosensitive aqueous microgels
      Pich, A., Berger, S., Ornatsky, O et al. Colloid and Polymer Science (2009): 269–275
    • Hybrid nanogels by encapsulation of lanthanide-doped LaF3 nanoparticles as elemental tags for detection by atomic mass spectrometry
      Berger, S., Ornatsky, O., Baranov, V. et al. Journal of Material Chemistry (2010): 5,141–50
    • Algorithmic tools for mining high-dimensional cytometry data
      Chester, C., Maecker, H.T. Journal of Immunology (2015): 773–9
    • Mass cytometry panel optimization through the designed distribution of signal interference
      Takahashi, C., Au-Yeung, A., Fuh, F. et al. Cytometry Part A (2016): 39–47
    • On the relationship between cell cycle analysis with ergodic principles and age-structured cell population models
      Kuritz, K., Stöhr, D., Pollak, N., Allgöwer, F. Journal of Theoretical Biology (2016): 91–102
    • Meeting the challenges of measuring human immune regulation
      Martino, D., Allen, K. Journal of Immunological Methods (2015): 1–6
    • Cytokine-stimulated phosphoflow of whole blood using CyTOF mass cytometry
      Fernandez, R., Maecker, H. Bio-protocol (2015): e1495
    • Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators
      Bodenmiller, B., Zunder, E.R., Finck, R. et al. Nature Biotechnology (2012): 858–67
    • Singlet gating in mass cytometry
      Lai, L., Yeo, J.G., Albani, S. Cytometry Part A (2017): 170–2
    • Cell size assays for mass cytometry
      Stern, A.D., Rahman, A.H., Birtwhistle, M.R. Cytometry Part A (2016): 14–24
    • Bio-Functional, Lanthanide-Labeled Polymer Particles by Seeded Emulsion Polymerization and their Characterization by Novel ICP-MS Detection
      Thickett, S.C., Abdelrahman, A.I., Ornatsky, O. et al. Journal of Analytical Atomic Spectrometry (2010): 269–81
    • Synthesis of a functional metal-chelating polymer and steps toward quantitative mass cytometry bioassays
      Majonis, D., Herrera, I., Ornatsky, O. et al. Analytical Chemistry (2010): 8,961–9
    • Multiplexed epitope-based tissue imaging for discovery and healthcare applications
      Bodenmiller, B. Cell Systems (2016): 225–38
    • Mass cytometry: a highly multiplexed single-cell technology for advancing drug development
      Atkuri, K.R., Stevens, J.C., Neubert, H.. Drug Metabolism Disposition (2015): 227–33
    • Another step on the path to mass cytometry standardization
      Leopold, M.D. Cytometry Part A (2015): 380–2
    • Multiplexed peptide-MHC tetramer staining with mass cytometry
      Leong, M.L., Newell, E.W. Methods in Molecular Biology (2015): 115–31
    • Emerging proteomic technologies for elucidating context-dependent cellular signaling events: a big challenge of tiny proportions
      Parker, S.J., Raedschelders. K., Van Eyk, J.E. Proteomics (2015): 1,486–502
    • Characterization by mass cytometry of different methods for the preparation of muscle mononuclear cells
      Spada, F., Fuoco, C., Pirrò, S. et al. New Biotechnology (2016): 514–23
    • Highly multiplexed simultaneous detection of RNAs and proteins in single cells
      Frei, A.P., Bava, F.A., Zunder, E.R. et al. Nature Methods (2016): 269–75
    • Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm
      Zunder, E.R., Finck, R., Amir, el-A.D. et al. Nature Protocols (2015): 316–33
    • Organotellurium scaffolds for mass cytometry reagent development
      Park, H., Edgar, L.J., Lumba, M.A. et al. Organic and Biomolecular Chemistry (2015): 7,027–33
    • Barcoding of live human peripheral blood mononuclear cells for multiplexed mass cytometry
      Mei, H.E., Leipold, M.D., Schulz, A.R. et al. Journal of Immunology (2015): 2,022–31
    • Evaluating the efficiency of isotope transmission for improved panel design and a comparison of the detection sensitivities of mass cytometer instruments
      Tricot, S., Meyrand, M., Sammicheli, C. et al. Cytometry, Part A (2015): 357–68
    • Identification of hypoxic cells using an organotellurium tag compatible with mass cytometry
      Edgar, L.J., Vellanki, R.N., Halupa, A. et al. Angewandte Chemie (2014): 11,473–7
    • Metal-Containing Polystyrene Beads as Standards for Mass Cytometry
      Abdelrahman, A.I., Ornatsky, O., Bandura, D. et al. Journal of Analytical Atomic Spectrometry (2010): 260–8
    • Metal-chelating polymers by anionic ring-opening polymerization and their use in quantitative mass cytometry
      Illy, N., Majonis, D., Herrera, I. et al. Biomacromolecules (2012): 2,359–69
    • A platinum-based covalent viability reagent for single-cell mass cytometry
      Fienberg, H.G., Simonds, E.F., Fantl, W.J. et al. Cytometry, Part A (2012): 467–75
    • Flow cytometer with mass spectrometer detection for massively multiplexed single-cell biomarker assay
      Tanner, S.D., Bandura, D.R., Ornatsky, O. et al. Pure and Applied Chemistry (2008): 2,627–41
    • Transient partial permeabilization with saponin enables cellular barcoding prior to surface marker staining
      Behbehani, G.K., Thom, C., Zunder, E.R. et al. Cytometry, Part A (2014): 1,011–9
    • Normalization of mass cytometry data with bead standards
      Finck, R., Simonds, E.F., Jager, A. et al. Cytometry, Part A (2013): 483–94
    • Single-cell mass cytometry adapted to measurements of the cell cycle
      Behbehani, G.K., Bendall, S.C., Clutter, M.R. et al. Cytometry, Part A (2012): 552–66
    • Improving lanthanide nanocrystal colloidal stability in competitive aqueous buffer solutions using multivalent PEG-phosphonate ligands
      Cao, P., Tong, L., Hou, Y. et al. Langmuir (2012): 12,861–70
    • Effect of pendant group structure on the hydrolytic stability of polyaspartamide polymers under physiological conditions
      Lu, Y., Chau, M., Boyle, A.J. et al. Biomacromolecules (2012): 1,296–306
    • Development of mass cytometry methods for bacterial discrimination
      Leipold, M.D., Ornatsky, O., Baranov, V. et al. Analytical Biochemistry (2011): 1–8
    • Synthesis and mass cytometric analysis of lanthanide-encoded polyelectrolyte microgels
      Lin, W., Ma, X., Qian, J. et al. Langmuir (2011): 7,265–75
    • Surface Functionalization Methods to Enhance Bioconjugation in Metal-Labeled Polystyrene Particles
      Abdelrahman, A.I., Thickett, S.C., Liang, Y. et al. Macromolecules (2011): 4,801–13
    • Element-tagged immunoassay with ICP-MS detection: evaluation and comparison to conventional immunoassays
      Razumienko, E., Ornatsky, O., Kinach, R. et al. Journal of Immunological Methods (2008): 56–63
    • Development of analytical methods for multiplex bio-assay with inductively coupled plasma mass spectrometry
      Ornatsky, O.I., Kinach, R., Bandura, D.R. et al. Journal of Analytical Atomic Spectrometry (2008): 463–9
    • Biocompatible Hybrid Nanogels
      Pich, A., Zhang, F., Shen, L. et al. Small (2008): 2,171–5
    • Multiple cellular antigen detection by ICP-MS
      Ornatsky, O., Baranov, V.I., Bandura, D.R. et al. Journal of Immunological Methods (2006): 68–76
    • Polymer-Based Elemental Tags for Sensitive Bioassays
      Lou, X., Zhang, G., Herrera, I. et al. Angewandte Chemie (2007): 6,111–4
    • Study of cell antigens and intracellular DNA by identification of element-containing labels and metallointercalators using inductively coupled plasma mass spectrometry
      Ornatsky, O.I., Lou, X., Nitz, M. et al. Analytical Chemistry (2008): 2,539–47
    • Lanthanide-containing polymer nanoparticles for biological tagging applications: nonspecific endocytosis and cell adhesion
      Vancaeyzeele, C., Ornatsky, O., Baranov, V. et al. Journal of the American Chemical Society (2007): 13,653–60
    • Synthesis of Uniform NaLnF4 (Ln: Sm to Ho) Nanoparticles for Mass Cytometry
      Tong, L., Lu, E., Pichaandi, J. et al. Journal of Physical Chemistry (2016): 6,269–80
    • Single cell analysis of human tissues and solid tumors with mass cytometry
      Leelatian, N., Doxie, D.B., Greenplate, A.R. et al. Cytometry, Part B (2017): 68–78
    • Barcoding of live human PBMC for multiplexed mass cytometry
      Mei, H.E., Leipold, M.D., Schulz, A.R. et al. The Journal of Immunology (2015): 2,022–31
    • Standardization and quality control for high-dimensional mass cytometry studies of human samples
      Kleinsteuber, K., Corleis, B., Rashidi, N. et al. Cytometry Part A (2016): 903–13
    • Lanthanide-containing polymer microspheres by multiple-stage dispersion polymerization for highly multiplexed bioassays
      Abdelrahman, A.I., Dai, S., Thickett, S.C. et al. Journal of the American Chemical Society (2009): 15,276–83
    • Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry
      Bandura, D.R., Baranov, V.I., Ornatsky, O.I. et al. Analytical Chemistry (2009): 6,813–22
    • Hybrid Imaging Labels: Providing the Link Between Mass Spectrometry-Based Molecular Pathology and Theranostics
      Buckle, T., van der Wal, S., van Malderen, S.J.M. et al. Theranostics (2017): 624–33
    • Brief introduction to mass cytometry
      Cosma, A., Le Grand, R. Medecine/Sciences (2011): 1,072–4
    • Multiparameter Phenotyping of Human PBMCs Using Mass Cytometry
      Leipold, M.D., Newell, E.W., Maecker, H.T. Methods in Molecular Biology (2015): 81–95
    • Enhanced multiplexing in mass cytometry using osmium and ruthenium tetroxide species
      Catena, R., Özcan, A., Zivanovic, N., Bodenmiller, B. Cytometry Part A (2016): 491–7
    • Single-cell gene expression profiling and cell state dynamics: collecting data, correlating data points and connecting the dots
      Marr, C., Zhou, J.X., Huang, S. Current Opinion in Biotechnology (2016): 207–14
    • The potential for elemental analysis in biotechnology
      Baranov, V.I., Quinn, Z.A., Bandura, D.R., Tanner, S.D. Journal of Analytical Atomic Spectrometry (2002): 1,148–52
    • The numerology of T cell functional diversity
      Haining, W.N. Immunity (2012): 10–2
    • A Deep Profiler’s Guide to Cytometry
      Bendall, S.C., Nolan, G.P., Roederer, M., Chattopadhyay, P.K. Trends in Immunology (2012): 323–32
    • Multiplex bio-assay with inductively coupled plasma mass spectrometry: Towards a massively multivariate single-cell technology
      Tanner, S.D., Ornatsky, O., Bandura, D.R., Baranov, V.I. Spectrochimica Acta Part B: Atomic Spectroscopy (2007): 188–95
    • The synthesis and characterization of lanthanide-encoded poly(styrene-co-methacrylic acid) microspheres
      Liang, Y., Abdelrahman, A.I., Baranov, V., Winnik, M.A. Polymer (2011): 5,040–52
    • Curious results with palladium- and platinum-carrying polymers in mass cytometry bioassays and an unexpected application as a dead cell stain
      Majonis, D., Ornatsky, O., Kinach, R., Winnik, M.A. Biomacromolecules (2011): 3,997–4,010
    • The release and extraction of lanthanide ions from metal-encoded poly (styrene-co-methacrylic acid) microspheres
      Liang, Y., Abdelrahman, A.I., Baranov, V., Winnik, M.A. Polymer (2012): 998–1,004
    • A sensitive and quantitative element-tagged immunoassay with ICPMS detection
      Baranov, V.I., Quinn, Z., Bandura, T.R., Tanner, S.D. Analytical Chemistry (2002): 1,629–36
    • Mass cytometry: protocol for daily tuning and running cell samples on a CyTOF mass cytometer
      Leipold, M.D., Maecker, H.T. Journal of Visualized Experiments (2012): e4398
    • Platinum-conjugated antibodies for application in mass cytometry
      Mei, H.E., Leipold, M.D., Maecker, H.T. Cytometry, Part A (2015): 292–300
    • Single-cell methods
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    • Immune monitoring technology primer: flow and mass cytometry
      Maecker, H.T., Harari, A. Journal for ImmunoTherapy of Cancer (2015): 44
    • Dual-purpose polymer labels for fluorescent and mass cytometric affinity bioassays
      Majonis, D., Ornatsky, O., Weinrich, D., Winnik, M.A. Biomacromolecules (2013): 1,503–13

  • Neurology

    • Mapping microglia states in the human brain through the integration of high-dimensional techniques
      Sankowski, R., Böttcher, C., Masuda, T., et al. Nature Neuroscience (2019): 2,098-2,110
    • The landscape of myeloid and astrocyte phenotypes in acute multiple sclerosis lesions
      Park, C., Ponath, G., Levine-Ritterman, M. et al. Acta Neuropathologica Communications (2019): 130
    • Pro-inflammatory, IL-17 pathways dominate the architecture of the immunome in pediatric refractory epilepsy
      Kumar, P., Shih, D.C.W., Lim, A. et al. JCI Insight (2019): doi: 10.1172/jci.insight.126337

  • Oncology

    • Phenotypic Characterization by Mass Cytometry of the Microenvironment in Ovarian Cancer and Impact of Tumor Dissociation Methods
      Anandan, S., Thompson, L. C. V., Gullaksen, S. E. Cancers (2021): doi.org/10.3390/cancers13040755
    • CyTOF Analysis Reveals a Distinct Immunosuppressive Microenvironment in IDH Mutant Anaplastic Gliomas
      Fu, W., Wang, W., Li. H. Frontiers in Oncology (2021): doi.org/10.3389/fonc.2020.560211
    • Multiplexed single‐cell mass cytometry reveals distinct inhibitory effects on intracellular phosphoproteins by midostaurin in combination with chemotherapy in AML cells
      Rörby, E., Adolfsson, J., Hultin, E. Experimental Hematology & Oncology (2021): doi.org/10.1186/s40164-021-00201-w
    • Circulating Myeloid Regulatory Cells: Promising Biomarkers in B-Cell Lymphomas
      Ferrant, J., Lhomme, F., Gallou, S. L. Frontiers in Immunology (2021): doi.org/10.3389/fimmu.2020.623993
    • Immunological Hallmarks for Clinical Response to BCG in Bladder Cancer
      Lim, C.J., Nguyen, P. H. D., Wasser, M. Frontiers in Immunology (2021): doi.org/10.3389/fimmu.2020.615091
    • Successful identification of predictive profiles for infection utilising systems-level immune analysis: a pilot study in patients with relapsed and refractory multiple myeloma
      Doerflinger, M., Garnham, A. L., Freytag, S. Clinical & Translational Immunology (2021): doi.org/10.1002/cti2.1235
    • Defining phenotypic and functional heterogeneity of glioblastoma stem cells by mass cytometry
      Galdieri, L., Jash, A., Malkava, O. JCI Insight (2021): doi.org/10.1172/jci.insight.128456.
    • High-dimensional immunotyping of tumors grown in obese and non-obese mice
      Wogsland, C.E., Lien, H. E., Pedersen, L. Disease Models & Mechanisms (2021): doi.org/10.1242/dmm.048977
    • A combination of ssGSEA and mass cytometry identifies immune microenvironment in muscle‐invasive bladder cancer
      Wang, X., Pan, L., Lu, Q. Journal of Clinical Laboratory Analysis (2021): doi.org/10.1002/jcla.23754
    • Group-2 Innate Lymphoid Cells Promote Hepatocellular Carcinoma Progression via CXCL2-Neutrophil Induced Immunosuppression
      Xu, X., Ye, L., Zhang, Q. Hepatology (2021): doi.org/10.1002/hep.31855
    • Single-cell atlas reveals complexity of the immunosuppressive microenvironment of initial and recurrent glioblastoma
      Fu, W., Wang, W., Li, H. et al. Frontiers in Immunology (2021): doi.org/10.3389/fimmu.2020.00835
    • An autochthonous mouse model of Myd88- and BCL2-driven diffuse large B-cell lymphoma reveals actionable molecular vulnerabilities
      Flümann, R. , Rehkämper, T., Nieper, P. et al. Blood Cancer Discovery (2021): DOI: 10.1158/2643-3230.BCD-19-0059
    • Potentiality of multiple modalities for single‑cell analyses to evaluate the tumor microenvironment in clinical specimens
      Kashima, Y., Togashi, Y., Fukuoka, S. et al. Scientific Reports (2021): doi.org/10.1038/s12276-020-00499-2
    • Human tumor-infiltrating MAIT cells display hallmarks of bacterial antigen recognition in colorectal cancer
      Li, S.B., Simoni, Y., Becht, E. Cell Reports Medicine (2021): doi.org/10.1016/j.xcrm.2020.100039
    • The Tumor Profiler Study: integrated, multi-omic, functional tumor profiling for clinical decision support
      Irmisch, A., Bonilla. X., Chevrier , S. Cancer Cell (2021): DOI: 10.1016/j.ccell.2021.01.004
    • Quantification of Immune Variables from Liquid Biopsy in Breast Cancer Patients Links Vδ2+ γδ T Cell Alterations with Lymph Node Invasion
      Fattori, S., Gorvel , L., Granjeaud, S. Cancers (2021): doi.org/10.3390/cancers13030441
    • TBL1XR1 mutations drive extranodal lymphoma by inducing a pro-tumorigenic memory fate
      Venturutti, L., Teater, M., Zhai, A. et al. Cell (2020): doi.org/10.1016/j.cell.2020.05.049
    • A systemic protein deviation score linked to PD-1+ CD8+ T cell expansion that predicts overall survival in diffuse large B cell lymphoma
      Ask, E.H., Tschan-Plessl, A., Gjerdingen, T. J. et al. Med (Cell Press) (2020): doi.org/10.1016/j.medj.2020.10.006
    • Exploration of the personalized immune checkpoint atlas of plasma cell dyscrasias patients using high‑dimensional single‑cell analysis
      Tu, C., Zheng, Y., Zhang, H. et al. Oncology Reports (2020): 224-240
    • Host genetics and tumor environment determine the functional impact of neutrophils in mouse tumor models
      Van Elsas, M., Kleinovink, J. W., Moerland, M.et al. Journal for ImmunoTherapy of Cancer (2020): doi.org/10.1136/jitc-2020-000877
    • Hyperion imaging system reveals heterogeneous tumor microenvironment of oral squamous cell carcinoma patients at T1N0M0 stage
      Xie, S., Shan, X. F., Yau, V. et al. Annals of Translational Medicine (2020): doi: 10.21037/atm-20-7194
    • Inhibitory interplay of SULT2B1b sulfotransferase with AKR1C3 aldo-keto reductase in prostate cancer
      Park, S., Song, C. S., Lin, C. L. et al. Endocrinology (2020): DOI: 10.1210/endocr/bqz042
    • Targeting the MET receptor tyrosine kinase as a strategy for radiosensitization in loco-regionally advanced head and neck squamous cell carcinoma
      Nisa, L., Francica, P., Giger, R. Molecular Cancer Therapeutics (2019): DOI: 10.1158/1535-7163.MCT-18-1274
    • Autoreactive CD8+ T cell exhaustion distinguishes subjects with slow type 1 diabetes progression
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      Chang, Q., Ornatsky, O.I., Koch, C.J. et al. International Journal of Cancer (2015): 1202–9
    • Mass cytometry analysis shows that a novel memory phenotype B cell is expanded in multiple myeloma
      Hansmann, L., Blum, L., Ju, C.H. et al. Cancer Immunology Research (2015): 650–60
    • Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis
      Levine, J.H., Simonds, E.F., Bendall, S.C. et al. Cell (2015): 184–97
    • Myelodysplastic Syndrome Revealed by Systems Immunology in a Melanoma Patient Undergoing Anti-PD-1 Therapy
      Greenplate, A.R., Johnson, D.B., Roussel, M. et al. Cancer Immunology Research (2016): 474–80
    • High-Dimensional Analysis of Acute Myeloid Leukemia Reveals Phenotypic Changes in Persistent Cells during Induction Therapy
      Ferrell, P.B. Jr., Diggins, K.E., Polikowsky, H.G. et al. PLoS One (2016): e0153207
    • Anti-apoptotic ARC protein confers chemoresistance by controlling leukemia-microenvironment interactions through a NFκB/IL1β signaling network
      Carter, B.Z., Mak, P.Y., Chen, Y. et al. Oncotarget (2016): 20,054–67
    • Expansion and Activation of CD103(+) Dendritic Cell Progenitors at the Tumor Site Enhances Tumor Responses to Therapeutic PD-L1 and BRAF Inhibition
      Salmon, H., Idoyaga, J., Rahman, A. et al. Immunity (2016): 924–38
    • Impaired coordination between signaling pathways is revealed in human colorectal cancer using single-cell mass cytometry of archival tissue blocks
      Simmons, A.J., Scurrah, C.R., McKinley, E.T. et al. Science Signaling (2016): rs11
    • BET protein bromodomain inhibitor-based combinations are highly active against post-myeloproliferative neoplasm secondary AML cells
      Saenz, D.T., Fiskus, W., Manshouri, T. et al. Leukemia (2016): 678–87
    • A Prospective Clinical Trial Combining Radiation Therapy With Systemic Immunotherapy in Metastatic Melanoma
      Hiniker, S.M., Reddy, S.A., Maecker, H.T. et al. International Journal of Radiation Oncology Biology Physics (2016): 578–88
    • Mass cytometry of follicular lymphoma tumors reveals intrinsic heterogeneity in proteins including HLA-DR and a deficit in non-malignant plasmablast and germinal center B cell populations
      Wogsland, C.E., Greenplate, A.R., Kolstad, A. et al. Cytometry Part B Clinical Cytometry (2016): 79–87
    • Human Melanoma-Derived Extracellular Vesicles Regulate Dendritic Cell Maturation
      Maus, R.L.G., Jakub, J.W., Nevala, W.K. et al. Frontiers in Immunology (2017): 358
    • Interlesional diversity of T cell receptors in melanoma with immune checkpoints enriched in tissue-resident memory T cells
      Boddupalli, C.S., Bar, N., Kadaveru, K. et al. JCI Insight (2016): e88955
    • Effect of cryopreservation on delineation of immune cell subpopulations in tumor specimens as determinated by multiparametric single cell mass cytometry analysis
      Kadić, E., Moniz, R.J., Huo, Y. et al. BMC Immunology (2017): 6
    • MLN0128, a novel mTOR kinase inhibitor, disrupts survival signaling and triggers apoptosis in AML and AML stem/ progenitor cells
      Zeng, Z., Wang, R.Y., Qiu, Y.H., et al. Oncotarget (2016): 55,083–97
    • NCR1 Expression Identifies Canine Natural Killer Cell Subsets with Phenotypic Similarity to Human Natural Killer Cells
      Foltz, J.A., Somanchi, S.S., Yang, Y. et al. Frontiers in Immunology (2016): 521
    • Comprehensive characterization of VISTA expression in patients with acute myeloid leukemia
      Lamble, A., Kosaka, Y., Huang, F. et al. Journal of Clinical Oncology (2016): e14546
    • Mass Cytometry: A High-Throughput Platform to Visualize the Heterogeneity of Acute Myeloid Leukemia
      Do, P., Byrd, J.C. Cancer Discovery (2015): 912–4
    • From single cells to deep phenotypes in cancer
      Bendall, S.C., Nolan, G.P. Nature Biotechnology (2012): 639–47
    • From mass cytometry to cancer prognosis
      Winter, D.R., Ledegor, G., Amit, I. Nature Biotechnology (2015): 931–2

  • Review

    • 2020 White Paper on Recent Issues in Bioanalysis: BAV Guidance, CLSI H62, Biotherapeutics Stability, Parallelism Testing, CyTOF and Regulatory Feedback (Part 2A – Recommendations on Biotherapeutics Stability, PK LBA Regulated Bioanalysis, Biomarkers Assays, Cytometry Validation & Innovation Part 2B – Regulatory Agencies’ Inputs on Bioanalysis, Biomarkers, Immunogenicity, Gene & Cell Therapy and Vaccine)
      Spitz, S., Zhang, Y., Fischer, S. Bioanalysis (2021): doi.org/10.4155/bio-2021-0005
    • Characterizing Highly Cited Papers in Mass Cytometry through H-Classics
      Di Zeo-Sánchez, D.E., Sánchez-Núñez, P., Stephens, C. Biology (2021): doi.org/10.3390/biology10020104
    • Tumor Microenvironment Features as Predictive Biomarkers of Response to Immune Checkpoint Inhibitors (ICI) in Metastatic Clear Cell Renal Cell Carcinoma (mccRCC)
      Simonaggio, A., Epaillard, N., Pobe, C. Cancers (2021): doi.org/10.3390/cancers13020231
    • A high-dimensional window into the micro-environment of triple negative breast cancer
      Nederlof, I., Horlings, H.M, Curtis, C. Cancers (2021): doi.org/10.3390/cancers13020316
    • The science and medicine of human immunology
      Pulendran, B. and Davis, M. M. Science (2020): DOI: 10.1126/science.aay4014
    • Changing the landscape of tumor immunology: novel tools to examine T cell specificity
      Rahman, M.A., Murata, K., Burt, B. D. Current Opinion in Immunology (2021): doi.org/10.1016/j.coi.2020.11.003
    • Mass cytometry tags: Where chemistry meets single-cell analysis
      Delgado-Gonzalez, A., Sanchez-Martin, R. M. Analytical Chemistry (2021): doi.org/10.1021/acs.analchem.0c03560
    • Deciphering the heterogeneity of myeloid cells during neuroinflammation in the single-cell era
      Borst, K., Prinz, M. Brain Pathology (2021): DOI: 10.1111/bpa.12910
    • Are lupus animal models useful for understanding and developing new therapies for human SLE?
      Moore, E., Putterman, C. Journal of Autoimmunity (2021): DOI: 10.1016/j.jaut.2020.102490
    • Single-cell technologies applied to HIV-1 research: reaching maturity
      Sannier, G., Dube, M., Kaufmann, D. E. Frontiers in Microbiology (2021): doi.org/10.3389/fmicb.2020.00297
    • Progress and applications of mass cytometry in sketching immune landscapes
      Zhang, T., Warden, A. R., Li, Y. Clinical and Translational Medicine (2020): doi.org/10.1002/ctm2.206
    • High-dimensional analysis of circulating and tissue-derived myeloid-derived suppressor cells from patients with glioblastoma
      Alban, T.J., Bayik, D., Alvarado, A. G. Myeloid-Derived Suppressor Cells. Methods in Molecular Biology (2020): 157-175
    • High-dimensional phenotyping of human myeloid-derived suppressor cells/tumor-associated macrophages in tissue by mass cytometry
      Ferrant, J., Gallou, S. L., Manson, G. Myeloid-Derived Suppressor Cells. Methods in Molecular Biology (2020): 57-66
    • Use of mass cytometry to profile human T cell exhaustion
      Winkler, F., Bengsch, B. Frontiers in Immunology (2020): doi.org/10.3389/fimmu.2019.03039
    • Recent advances in single-cell ultra-trace analysis
      Wei, X., Lu, Y., Zhang, X. TrAC Trends in Analytical Chemistry (2020): doi.org/10.1016/j.trac.2020.115886
    • The use of single cell mass cytometry to define the molecular mechanisms of Varicella-Zoster virus lymphotropism
      Sen, N., Mukherjee, G., Arvin, A.M. Frontiers in Microbiology (2020): doi.org/10.3389/fmicb.2020.01224
    • Key steps and methods in the experimental design and data analysis of highly multi-parametric flow and mass cytometry
      Paulina Rybakowska ,Marta E.Alarcón-Riquelme, Concepción Marañón Computational and Structural Biotechnology Journal (2020): https://doi.org/10.1016/j.csbj.2020.03.024
    • Mass cytometry and Type 1 diabetes research in the age of single-cell data science
      Adeeb H Rahman, Dirk Homann Current Opinion in Endocrinology, Diabetes and Obesity (2020): DOI: 10.1097/MED.0000000000000549
    • Exploration of T-cell diversity using mass cytometry
      Kaitlin C O'Boyle, Takuya Ohtani, Sasikanth Manne Methods in Molecular Biology (2020): DOI: 10.1007/978-1-0716-0266-9_1
    • Microglia heterogeneity in the single-cell era
      Masuda,T., Sankowski,R., Staszewski,O. Cell Reports (2020): DOI:https://doi.org/10.1016/j.celrep.2020.01.010
    • Mass cytometry provides unprecedented insight into the role of B cells during the pathogenesis of multiple sclerosis
      Marsh-Wakefield, F., Byrne, S.N., Hawke, S. Advances in Clinical Neuroscience and Rehabilitation (2020): doi: 10.1016/S0140-6736(11)61649-8.
    • From Bivariate to Multivariate Analysis of Cytometric Data: Overview of Computational Methods and Their Application in Vaccination Studies
      Lucchesi, S.,Furini, S.,Medaglini, D. Vaccines (2020): 138
    • Recent Advances in Computer-Assisted Algorithms for Cell Subtype Identification of Cytometry Data
      Liu, P., Liu, S., Fang, Y. Frontiers in Cell and Developmental Biology (2020): doi.org/10.3389/fcell.2020.00234
    • The role of single-cell technology in the study and control of infectious diseases
      Lin, W.N., Tay, M. Z., Lu, R. Cells (2020): doi.org/10.3390/cells9061440
    • A cancer biologist’s primer on machine learning applications in high-dimensional cytometry”
      Keyes, T.J, Domizi, P., Yu-Chen, Lo Cytometry Part A (2020): doi: 10.1002/cyto.a.24158
    • Mass Cytometry of Hematopoietic Cells
      Jager, A., Sarno, J., Davis, K. L. Leukemia Stem Cells (2020): 65-76
    • The use and limitations of single‐cell mass cytometry for studying human microglia function
      Fernández‐Zapata, C., Leman, J. K. H., Priller, J. Brain Pathology (2020): doi.org/10.1111/bpa.12909
    • Mass cytometry—A tool for the curious Networking in Berlin
      Burns, M., Schulz , A. R., Kunkel, D. Cytometry A (2020): doi.org/10.1002/cyto.a.24015
    • Technologies for assessing vaccine responses in the very young
      Brodin, P. Current Opinion in Immunology (2020): doi.org/10.1016/j.coi.2020.03.011
    • Rigor and reproducibility of cytometry practices for immuno‐oncology: a multifaceted challenge
      Laskowski, T.J., Hazen, A.L., Collazo, R.S. et al. Cytometry Part A (2020): 116-125
    • Peptide‐MHC class I and class II tetramers: From flow to mass cytometry
      Christophersen, A. HLA Immune Response Genetics (2019): DOI: 10.1111/tan.13789
    • Deciphering immunity at high plexity and resolution
      Domínguez Conde, C. and Teichmann, S. Nature Reviews Immunology (2019): 77-78
    • Immune monitoring using mass cytometry and related high-dimensional imaging approaches
      Hartmann, F.J. and Bendall, S.C. Nature Reviews Rheumatology (2020): 87-99
    • Using single-cell technologies to map the human immune system — implications for nephrology
      Stewart, B.J., Ferdinand, J.R., Clatworthy, M.R., et al. Nature Reviews Nephrology (2020): 112-128
    • WS05: How to ensure robustness and reproducibility when using mass cytometry for clinical trials
      Escobar, D.L.B., Estevam, J., Leipold, M., et al. Cyt-Geist: Current and Future Challenges in Cytometry: Reports of the CYTO 2019 Conference Workshops (2019): 1,264-1,268
    • The islets of Langerhans continue to reveal their secrets
      Bonner-Wei, S. Nature Reviews Endocrinology (2019): 73-74
    • Mass cytometry imaging for the study of human diseases – applications and data analysis strategies
      Baharlou, H., Canete, N.P., Cunningham, A.L. et al. Frontiers in Immunology (2019): doi: 10.3389/fimmu.2019.02657
    • Deciphering host immunity to malaria using systems immunology
      Loiseau, C., Cooper, M.M., and Doolan, D.L. (2019): doi: 10.1111/imr.12814
    • Data-driven flow cytometry analysis
      Wang, S. and Brinkman, R.R. Mass Cytometry: Methods and Protocols (2019): 245-265
    • Proteomic tools and new insights for the study of B-cell precursor acute lymphoblastic leukemia
      Citalan-Madrid, A.F., Cabral-Pacheco, G.A., Martinez-de-Villarreal, L.E. et al. Hematology (2019): 637-650
    • Multimodal single-cell approaches shed light on T cell heterogeneity
      Nathan, A., Baglaenko, Y., Fonseka, C.Y. et al. Current Opinion in Immunology (2019): 17-25
    • Importance of multi-parametric evaluation of immune-related T-cell markers in renal cell carcinoma
      Kawashima, A., Uemura, M., and Nonomura, N. Clinical Genitourinary Cancer (2019): doi: 10.1016/j.clgc.2019.07.021.
    • Systems immunology allows a new view on human dendritic cells
      Schultze, J.L. and Aschenbrenner, A.C. Seminars in Cell & Developmental Biology (2019): 15-23.
    • Single-cell high-throughput technologies in cerebrospinal fluid research and diagnostics
      Lanz, T.V., Pröbstel, A.K., Mildenberger, I. et al. Frontiers in Immunology (2019): 1302
    • Human microglia seize the chance to be different
      Brewster, A.L. Epilepsy Currents (2019): 190-192.
    • Advancing systems immunology through data-driven statistical analysis
      Fong, L.E., Muñoz-Rojas, A.R., Miller-Jensen, K. Current Opinion in Biotechnology (2018): 109-115
    • High‐resolution interrogation of biological systems via mass cytometry
      Brown, H.M.G., Kuhns, M.M., and Arriaga, E.A. Proteomics for Biological Discovery (2019): 215-246
    • The role of systems biology approaches in determining molecular signatures for the development of more effective vaccines
      Pezeshki, A., Ovsyannikova, I.G., McKinney, B.A. et al. Expert Review of Vaccines (2019): 253-267
    • An introduction to mass cytometry: fundamentals and applications
      Tanner, S.D., Baranov, V.I., Ornatsky, O.I. et al. Cancer Immunology, Immunotherapy (2013): 955–65
    • New assays for monitoring residual HIV burden in effectively treated individuals
      Strain, M.C, Richman, D.D. Current Opinion in HIV & AIDS (2013): 106–110
    • Higher Throughput Methods of Identifying T Cell Epitopes for Studying Outcomes of Altered Antigen Processing and Presentation
      Newell, E.W. Frontiers in Immunology (2013): 430
    • Inductively coupled plasma mass spectrometry-based immunoassay: a review
      Liu, R., Wu, P., Yang, L. et al. Mass Spectrometry Reviews (2014): 373–93
    • Cracking the code of human T-cell immunity
      Harvey, C.J., Wucherpfennig, K.W. Nature Biotechnology (2013): 609–10
    • Single cell mass cytometry for analysis of immune system functional states
      Bjornson, Z.B., Nolan, G.P., Fantl, W.J. Current Opinion in Immunology (2013): 484–94
    • A practical guide to multiplexed mass cytometry
      Zivanovic, N., Jacobs, A., Bodenmiller, B. Current Topics in Microbiology and Immunology (2014): 95–109
    • High-dimensional analysis of human CD8(+) T cell phenotype, function, and antigen specificity
      Newell, E.W., Lin, W. Current Topics in Microbiology and Immunology (2013): 61–84
    • Beyond model antigens: high-dimensional methods for the analysis of antigen-specific T cells
      Newell, E.W., Davis, M.M. Nature Biotechnology (2014): 149–57
    • Different subsets of natural killer T cells may vary in their roles in health and disease
      Kumar, V., Delovitch, T.L. Immunology (2014): 321–36
    • Twenty (forward looking) questions
      Hassell, L.A., Wagar, E.A. Journal of Pathology Informatics (2014): 27
    • Mass cytometry to decipher the mechanism of nongenetic drug resistance in cancer
      Fienberg, H.G., Nolan, G.P. Current Topics in Microbiology and Immunology (2014): 85–94
    • Shooting movies of signaling network dynamics with multiparametric cytometry
      Claassen, M. Current Topics in Microbiology and Immunology (2014): 177–89
    • Monitoring the Immune Competence of Cancer Patients to Predict Outcome
      Chang, S., Kohrt, H., Maecker, H.T. Cancer Immunology, Immunotherapy (2014): 713–9
    • The reconstructed natural history of type 1 diabetes mellitus
      Pozzilli, P. and Signore, A. Nature Reviews Endocrinology (2019): 256-257
    • Considerations for immunohistochemistry
      Balaji, S., Li, H., Steen, E. et al. Success in Academic Surgery: Basic Science (2019): 105-144
    • Monitoring of the immune dysfunction in cancer patients
      Santegoets, S.J.A.M., Welters, M.J.P. and van der Burg, S.H. Vaccines (Basel) (2016): 29
    • Retracing the in vivo haematopoietic tree using single-cell methods
      Perié, L. and Duffy, K.R. FEBS Letters (2016): 4,068-4,083
    • Mass cytometry: Blessed with the curse of dimensionality
      Newell, E.W. and Cheng, Y. Nature Immunology (2016): 890-895
    • High standards for high dimensional investigations
      Montgomery, R.R. Cytometry Part A (2016): 886-888
    • Single-cell proteomics: potential implications for cancer diagnostics
      Gavasso, S., Gullaksen, S.E., Skavland, J. et al. Expert Review of Molecular Diagnostics (2016): 579-589
    • Natural killer cell diversity in viral infection: Why and how much?
      Blish, C.A. Pathogens and Immunity (2016): 165-192
    • Single cell proteomics in biomedicine: high-dimensional data acquisition, visualization and analysis
      Su, Y., Shi, Q., and Wei, W. Proteomics (2017): 10
    • Regulatory myeloid cells: an underexplored continent in B-cell lymphomas
      Roussel, M., Irish, J.M., Menard, C. et al. Cancer Immunology Immunotherapy (2017): 1,103-1,111
    • Integral membrane proteins: bottom-up, top-down and structural proteomics
      Karr, U., Simonian, M. and Whitelegge, J.P. Expert Review of Proteomics (2017): 715-723
    • Current advances in highly multiplexed antibody-based single-cell proteomic measurements
      Huang, L., Michael, S.A., Chen, Y. et al. Chemistry an Asian Journal (2017): 1,680-1,691
    • How many subsets of innate lymphoid cells do we need?
      Ealey, K.N. and Koyasu, S. Immunity (2017): 10-13
    • Human immune system variation
      Brodin, P. and Davis. M.M. Nature Reviews Immunology (2017): 21-29
    • Nolan Lab Profiles Small-Molecule Inhibitors Using New Multiplexing Method for DVS Sciences' CyTOF
      Bonislawski, A. Genome Web (2012):
    • Application of single cell sequencing in cancer
      Yu, L., Zhao, H., Meng, L. et al. Single Cell Biomedicine (2018): 135-148
    • Data analysis to modeling to building theory in NK cell biology and beyond: How can computational modeling contribute?
      Das, J., and Lanier., L.L. Journal of Leukocyte Biology (2019): 1,305-1,1317.
    • Setting up mass cytometry in a shared resource lab environment
      Warth, S. and Kunkel, D. Mass Cytometry: Methods and Protocols (2019): 3-11
    • Expanding the clinical cytometry toolbox—Receptor occupancy by mass cytometry
      Huse, K. Cytometry Part A (2019): doi: 10.1002/cyto.a.23784
    • In silico methods for studying T cell biology
      Grzesik, K., Eng, K., Crauste, F. et al. International Review of Cell and Molecular Biology (2019): 265-304
    • The end of omics? High dimensional single cell analysis in precision medicine
      Galli, E., Friebel, E., Ingelfinger, F. et al. European Journal of Immunology (2019): 212-220.
    • CyTOF®: A new tool to decipher the immunomodulatory activity of daratumumab
      Castella, B., Mina, R., and Gay, F. Cytometry Part A (2019): doi: 10.1002/cyto.a.23752
    • Visualization of mass cytometry signal background to enable optimal core panel customization and signal threshold gating
      Au-Yeung, A., Takahashi, C., Mathews, W.R. et al. Mass Cytometry: Methods and Protocols (2019): 35-45
    • Diagnostic tools for inborn errors of human immunity (primary immunodeficiencies and immune dysregulatory diseases)
      Richardson, A.M., Moyer, A.M., Hasadsri, L. et al. Current Allergy and Asthma Reports (2018): 19
    • Meeting the challenges of high-dimensional single-cell data analysis in immunology
      Palit, S., Heuser, C., de Almeida, G.P. et al. Frontiers in Immunology (2019): doi: 10.3389/fimmu.2019.01515.
    • Single-cell technologies in reproductive immunology
      Vazquez, J., Ong, I.M., Stanic, A.K. et al. American Journal of Reproductive Immunology (2019): e13157
    • The spatial and genomic hierarchy of tumor ecosystems revealed by single-cell technologies
      Smith, E.A. and Hodges, H.C. Trends in Cancer (2019): 411-425
    • WS10: Best practices for development and implementation of a CyTOF® core
      Rayanki,R., Ashhurst,T.M., van Vreden, C. et al. Cyt-Geist: Current and Future Challenges in Cytometry: Reports of the CYTO 2018 Conference Workshops (2019): 619–621.
    • The role of proteomics in assessing beta-cell dysfunction and death in type 1 diabetes
      Nakayasu, E.S., Qian, W.J., Evans-Molina, C. et al. Expert Review of Proteomics (2019): 569-582
    • Appreciating what’s unique about every stem cell
      Kruger, R.P. Cell (2019): 1,663-1,665
    • Immunophenotyping of human peripheral blood mononuclear cells by mass cytometry
      Heck, S., Bishop, C.J. and Ellis, R.J. Methods in Molecular Biology. Single Cell Methods: Sequencing and Proteomics (2019): 285-303
    • Single-cell technologies — studying rheumatic diseases one cell at a time
      Cheung, P., Khatri, P., Utz, P.J. et al. Nature Reviews Rheumatology (2019): 340-354
    • Single-cell protein secretion detection and profiling
      Chen, Z., Chen, J.J., and Fan, R. Annual Review of Analytical Chemistry (2019): 431-449
    • Recent trends in analysis of nanoparticles in biological matrices
      Gajdosechova, Z., Zoltan Mester, Z. Analytical and Bioanalytical Chemistry (2019): 1-16
    • Immune Profiling and Precision Medicine in Systemic Lupus Erythematosus
      Nagafuchi, Y., Shoda, H., Fujio, K. Cell (2019): doi: 10.3390/cells8020140
    • Mass spectrometry and proteomics in hematology
      Rolland, D.C.M., Lim, M.S., Elenitoba-Johnson, K.S.J. Seminars in Hematology (2019): 52-7
    • Getting the Most from Your High-Dimensional Cytometry Data
      Olsen, L.R., Pedersen, C.B., Leipold, M.D. et al. Immunity (2019): 535-6
    • Single cell immune profiling in transplantation research
      Higdon, L.E., Schaffert, S., Khatri, P. et al. American Journal of Transplantation (2019): 598
    • Flow Cytometry
      Blair, T., Frelinger III, A.L., Michelson, A.D. et al. Platelets (2019): 627-51
    • Integrative diagnosis of cancer by combining CTCs and associated peripheral blood cells in liquid biopsy
      Zhang, W.W., Rong, Y., Liu, Q. et al. Clinical and Translational Oncology (2018): doi: 10.1007/s12094-018-02004-8
    • Human intestinal lymphoid tissue in time and space
      Spencer, J., Siu, J.H.Y., Montorsi, L. Mucosal Immunology (2018): doi: 10.1038/s41385-018-0120-6
    • Enabling drug discovery and development through single-cell imaging
      Pomerantz, A.K., Sari-Sarraf, F., Grove, K.J. et al. Expert Opinion on Drug Discovery (2018): 1-11
    • Beyond the message: advantages of snapshot proteomics with single-cell mass cytometry in solid tumors
      Mistry, A.M., Greenplate, A.R., Ihrie, R.A. et al. FEBS Journal (2018): doi: 10.1111/febs.14730
    • Ushering in Integrated T Cell Repertoire Profiling in Cancer
      Jiang, N., Schonnesen, A.A., Ma, K.Y. Trends in Cancer (2018): doi: 10.1016/j.trecan.2018.11.005
    • The role of automated cytometry in the new era of cancer immunotherapy
      Danova, M., Torchio, M, Comolli, G. et al. Molecular and Clinical Oncology (2018): 355-61
    • Single-Cell Resolution of T Cell Immune Responses
      Buchholz, V.R., Flossdorf, M. Advances in Immunology (2018): doi: 10.1016/bs.ai.2017.12.001
    • Heterogeneity of Metazoan Cells and Beyond: To Integrative Analysis of Cellular Populations at Single-Cell Level
      Barteneva, N.S., Vorobjev, I.A. Methods in Molecular Biology (2018): doi: 10.1007/978-1-4939-7680-5_1
    • Impact of recent innovations in the use of mass cytometry in support of drug development
      Nassar, A.F., Ogura, H., Wisnewski, A.V. Drug Discovery Today (2015): 1,169–75
    • Cytometry: Measure for measure
      Kling, J. Nature (2015): 439–43
    • Mass cytometry: a powerful tool for dissecting the immune landscape
      Simoni, Y., Chng, M.H.Y., Li, S. et al. Current Opinion in Immunology (2018): 187–96
    • Technology to watch in 2018
      Powell, K. Nature (2018):

  • Stem Cell

    • Microenvironment immune reconstitution patterns correlate with outcomes after autologous transplant in multiple myeloma
      Parmar, H., Gertz, M., Kumar, S. Blood advances (2021): 1797–1804.
    • Maturation and phenotypic heterogeneity of human CD4+ regulatory T cells from birth to adulthood and after allogeneic stem cell transplantation
      Matos, T.R., Hirakawa, M., Alho, A.C. Frontiers in Immunology (2021): doi.org/10.3389/fimmu.2020.570550
    • Mass cytometry reveals immune signatures associated with cytomegalovirus (CMV) control in recipients of allogeneic haemopoietic stem cell transplant and CMV-specific T cells
      McGuire, H.M., Rizzetto, I., Withers, B. P. Clinical & Translational Immunology (2020): doi: 10.1002/cti2.1149
    • Mesenchymal stem cells alleviate LPS-induced acute lung injury by inhibiting the proinflammatory function of Ly6C+ CD8+ T cells
      Zhu, J., Feng, B., Xu, Y. Cell Death & Disease (2020): doi.org/10.1038/s41419-020-03036-1
    • Activation of the receptor tyrosine kinase RET improves long-term hematopoietic stem cell outgrowth and potency
      Grey, W., R, Chauhan.,Piganeau, M. Blood (2020): DOI: 10.1182/blood.2020006302
    • Characterization of mesoangioblast cell fate and improved promyogenic potential of a satellite cell-like subpopulation upon transplantation in dystrophic murine
      Mavoungoua, L.O., Neuenschwander, S., Pham, U. et al. Stem Cell Research (2019): 101,619
    • Mass cytometry-based single-cell analysis of human stem cell reprogramming uncovers differential regulation of specific pluripotency markers
      Im, I., Son, Y.S, Jung, K.B. et al. Journal of Biological Chemistry (2019): doi: 10.1074/jbc.RA119.009061
    • Human lymphoid organ cDC2 and macrophages play complementary roles in T follicular helper responses
      Durand, M., Walter, T., Pirnay, T. et al. Journal of Experimental Medicine (2019): 1,561-1,581
    • Stress-induced changes in bone marrow stromal cell populations revealed through single-cell protein expression mapping
      Severe, N., Karabacak, N.M., Gustafsson, K. et al. Cell Stem Cell (2019): doi: 10.1016/j.stem.2019.06.003.
    • High-dimensional single-cell cartography reveals novel skeletal muscle-resident cell populations
      Giordani, L., He, G.J., Negroni, E. et al. Molecular Cell (2019): 609-621.e6
    • Glucose metabolism drives histone acetylation landscape transitions that dictate muscle stem cell function
      Yucel, N., Wang, Y.X., Mai, T. et al. Cell Reports (2019): 3,939-3,955.E6
    • Pro-inflammatory aorta-associated macrophages are involved in embryonic development of hematopoietic stem cells
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