CyTOF & Helios Publications

Since the debut of CyTOF® technology in 2008, mass cytometry has catalyzed the revolution of single-cell proteomics, enabling the most comprehensive understanding of cell phenotypes, signaling pathways and function. Our complete mass cytometry system, anchored by the Helios™ instrument, combines data analysis, instrumentation, reagents and a comprehensive catalog of preconjugated antibodies to offer high-parameter single-cell protein research.

Browse our catalog of CyTOF-related publications to see how Helios and mass cytometry empower researchers to make breakthrough discoveries. Download a complete bibliography of publications.

• Overview

  Number of papers per research area as of March, 2019

  Number of cumulative papers as of March, 2019

• Recent

  • 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): doi: 10.1038/s41587-019-0033-2.
  • 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): doi: 10.1002/cyto.a.23621
  • 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
  • Cdh1 and Pik3ca Mutations Cooperate to Induce Immune-Related Invasive Lobular Carcinoma of the Breast
    An, Y., Adams, J.R., Hollern, D.P. et al. Cell Reports (2018): 702–14
  • 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

• Research Areas

  • Biomarker Screening

    • 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

    • Visualizing Structure and Transitions for Biological Data Exploration
      Moon, K.R., van Dijk, D., Wang, Z. et al. Cell (2018): doi: 10.2139/ssrn.3155891
    • 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
    • Advanced imaging technology applications in cytology
      Pantanowitz, L., Preffer, F., Wilbur, D.C. Nature Communications (2019): 5–14
    • 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
    • Mass synaptometry: High-dimensional multi parametric assay for single synapses
      Gajera, C.R., Fernandez, R., Postupna, N. et al. Journal of Neuroscience Methods (2019): 73–83
    • 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
    • Robust prediction of clinical outcomes using cytometry data
      Hu, Z., Glicksberg, B.S., Butte, A.J. Bioinformatics (2018): doi: 10.1093/bioinformatics/bty768
    • 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

  • IO

    • Macrophage migration inhibitory factor regulates U1-snRNP immune complex mediated activation of the NLRP3 inflammasome
      Shin, M.S., Kang, Y., Wahl, E.R. et al. Arthritis and Rheumatology (2018): 109–20
    • High-Dimensional Phenotyping Identifies Age-Emergent Cells in Human Mammary Epithelia
      Pelissier Vatter, F. A., Schapiro, D., Chang, H. et al. Cell Reports (2018): 1,205–19
    • Genetic Inactivation of CD33 in Hematopoietic Stem Cells to Enable CAR T Cell Immunotherapy for Acute Myeloid Leukemia
      Kim, M.Y., Yu, K.R., Kenderian, S.S. et al. Cell (2018): 1,439–53
    • SRC/ABL inhibition disrupts CRLF2-driven signaling to induce cell death in B-cell acute lymphoblastic leukemia
      Sarno, J., Savino, A.M., Buracchi, C. et al. Oncotarget (2018): 22,872–85
    • Anti-PD-1-induced high-grade hepatitis associated with corticosteroid-resistant T cells: a case report
      McGuire, H.M., Shklovskaya, E., Trevillian, P.R. et al. Cancer Immunology, Immunotherapy (2018): 563–73
    • Application of single-cell sequencing in human cancer
      Rantalainen, M. Briefings in Functional Genomics (2018): 273–82
    • Disruption of Wnt/β-Catenin Exerts Antileukemia Activity and Synergizes with FLT3 Inhibition in FLT3-Mutant Acute Myeloid Leukemia
      Jiang, X., Mak, P.Y., Mu, H. et al. Clinical Cancer Research (2018): 2,417–29
    • Dual PD1/LAG3 immune checkpoint blockade limits tumor development in a murine model of chronic lymphocytic leukemia
      Wierz, M., Pierson, S., Guyonnet, L. et al. Blood (2018): 1,617–21
    • Dynamic molecular monitoring reveals that SWI-SNF mutations mediate resistance to ibrutinib plus venetoclax in mantle cell lymphoma
      Agarwal, R., Chan, Y.C., Tam, C.S. et al. Nature Medicine (2018): 119–29
    • The Anatomical Location Shapes the Immune Infiltrate in Tumors of Same Etiology and Affects Survival
      Santagoets, S.J., van Ham, V.J., Ehsan, I. et al. Clinical Cancer Research (2019): 240–52
    • NKG2A Blockade Potentiates CD8 T Cell Immunity Induced by Cancer Vaccines
      van Montfoort, N., Borst, L., Korrer, M.J. et al. Cell (2018): 1,744–55
    • Venetoclax with azacitidine disrupts energy metabolism and targets leukemia stem cells in patients with acute myeloid leukemia
      Pollyea, D.A., Stevens, B.M., Jones, C.L. et al. Nature Medicine (2018): 1,859–66
    • The FGFR1 V561M Gatekeeper Mutation Drives AZD4547 Resistance Through STAT3 Activation and EMT
      Ryan, M.R., Sohl, C.D., Luo, B. et al. Molecular Cancer Research (2018): doi: 10.1158/1541-7786.MCR-18-0429
    • Fibrinogen-like Protein 1 Is a Major Immune Inhibitory Ligand of LAG-3
      Wang, J., Sanmamed, M.F., Datar, I. et al. Cell (2019): 334–47
    • Tumor-specific MHC-II expression drives a unique pattern of resistance to immunotherapy via LAG-3/FCRL6 engagement
      Johnson, D.B., Nixon, M.J., Wang, Y. et al. JCI Insight (2018): e120360
    • Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment
      Azizi, E., Carr, A.J., Plitas, G. et al. Cell (2018): 1,293–308
    • A Pilot Trial of the Combination of Transgenic NY-ESO-1-reactive Adoptive Cellular Therapy with Dendritic Cell Vaccination With or Without Ipilimumab
      Nowicki, T.S., Berent-Maoz, B., Cheung-Lau, G.C. et al. Clinical Cancer Research (2018): doi: 10.1158/1078-0432.CCR-18-3496
    • High-parameter mass cytometry evaluation of relapsed/refractory multiple myeloma patients treated with daratumumab demonstrates immune modulation as a novel mechanism of action
      Adams, H.C., Stevenart, F., Krejcik, J. et al. Cytometry Part A: Journal of the ISAC (2018): doi: 10.1002/cyto.a.23693
    • Melanoma Immunotherapy: Next-Generation Biomarkers
      Hogan, S.A., Levesque, M.P., Cheng, P.F. Frontiers in Oncology (2018): 178
    • High-dimensional mass cytometry analysis revealed microenvironment complexity in chronic lymphocytic leukemia
      Wierz, M., Janji, B., Berchem, G. et al. OncoImmunology (2018): e1465167
    • Global immune fingerprinting in glioblastoma patient peripheral blood reveals immune-suppression signatures associated with prognosis
      Alban, T.J., Alvarado, A.G., Sorensen, M.D. et al. JCI Insight (2018): e122264
    • CSF1R inhibitors exhibit anti-tumor activity in acute myeloid leukemia by blocking paracrine signals from support cells
      Chen, Y., Lakshmikanth, T., Olin, A. et al. Blood (2018): pii: blood-2018-03-838946
    • Mass cytometry of Hodgkin lymphoma reveals a CD4+ regulatory T-cell-rich and exhausted T-effector microenvironment
      Cader, F.Z., Schackmann, R.C.J., Hu, X. et al. Blood (2018): 825–36
    • T cell-directed IL-17 production by lung granular γδ T cells is coordinated by a novel IL-2 and IL-1β circuit
      Ménoret, A., Buturla, J.A., Xu, M.M. et al. Mucosal Immunology (2018): doi: 10.1038/s41385-018-0037-0
    • Multidimensional analyses reveal distinct immune microenvironment in hepatitis B virus-related hepatocellular carcinoma
      Lim, C.J., Lee, Y.H., Pan, L. et al. Gut (2018): doi: 10.1136/gutjnl-2018-316510
    • Anti-CTLA-4 immunotherapy does not deplete FOXP3+ regulatory T cells (Tregs) in human cancers
      Sharma, A., Subudhi, S.K., Blando, J. et al. Clinical Cancer Research (2018): DOI: 10.1158/1078-0432.CCR-18-0762
    • Resistance to radiotherapy and PD-L1 blockade is mediated by TIM-3 upregulation and regulatory T-cell infiltration
      Oweida, A., Hararah, M., Phan, A.V. et al. Clinical Cancer Research (2018): DOI: 10.1158/1078-0432.CCR-18-1038
    • Characterizing human head and neck tumors and cancer cell lines with mass cytometry
      Brodie, T.M., Tosevski, V., Medová, M. Cytometry Part A: Journal of the ISAC (2018): 406–10
    • Eradication of Triple-Negative Breast Cancer Cells by Targeting Glycosylated PD-L1
      Li, C.W., Lim, S.O., Chung, E.M. et al. Cancer Cell (2018): 187–201.e10
    • Functional screening of FGFR4-driven tumorigenesis identifies PI3K/mTOR inhibition as a therapeutic strategy in rhabdomyosarcoma
      McKinnon, T., Venier, R., Yohe, M. et al. Oncogene (2018): 2,630–44
    • Single-cell developmental classification of B cell precursor acute lymphoblastic leukemia at diagnosis reveals predictors of relapse
      Good, Z., Sarno, J., Jager, A. et al. Nature Medicine (2018): 474–83
    • Sensitive and frequent identification of high avidity neo-epitope specific CD8+ T cells in immunotherapy-naive ovarian cancer
      Bobisse, S., Genolet, R., Roberti, A. et al. Nature Communications (2018): 1,092
    • Intratumoral HPV16-specific T-cells constitute a type 1 oriented tumor microenvironment to improve survival in HPV16-driven oropharyngeal cancer
      Welters, M.J.P., Ma, W., Santegoets, S.J. et al. Clinical Cancer Research (2017): 634–47
    • Integrated functional and mass spectrometry-based flow cytometric phenotyping to describe the immune microenvironment in acute myeloid leukemia
      Lamble, A.J., Dietz, M., Laderas, T. et al. Journal of Immunological Methods (2017): 44–52
    • 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

    • 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
    • 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 (2019): 609-18
    • 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
    • Identification and Analysis of Islet Antigen-Specific CD8+ T Cells with T Cell Libraries
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  • Immunophenotyping

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    • A high-resolution mass cytometry analysis reveals a delay of cytokines production after TLR4 or TLR7/8 engagements in HIV-1 infected humans
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    • Single-cell RNA sequencing to explore immune cell heterogeneity
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    • Single-cell analysis identifies a CD33+ subset of human cord blood cells with high regenerative potential
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    • 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
    • High-dimensional single-cell analysis reveals the immune signature of narcolepsy
      Hartman, F.J., Bernard-Valnet, R., Quériault, C. et al. Journal of Experimental Medicine (2017): 2,621–33
    • 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
    • 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
    • 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

    • 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
    • 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
    • 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

  • Inherited Disease

    • B cell alterations during BAFF inhibition with belimumab in SLE
      Ramsköld, D., Parodis, I., Lakshmikanth, T. et al. EBioMedicine (2018): doi: 10.1016/j.ebiom.2018.12.035
    • Dysregulated NK cell PLCγ2 signaling and activity in juvenile dermatomyositis
      Throm, A.A., Alinger, J.B., Pingel, J.T. et al. JCI Insight (2018): e123236
    • 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
    • Mass cytometry reveals distinct platelet subtypes in healthy subjects and novel alterations in surface glycoproteins in Glanzmann thrombasthenia
      Blair, T.A., Michelson, A.D., Frelinger III, A.L. Scientific Reports (2018): 10,300
    • Leveraging blood and tissue CD4+ T cell heterogeneity at the single cell level to identify mechanisms of disease in rheumatoid arthritis
      Fonseka, C.Y., Rao, D.A., Raychaudhuri, S. Current Opinion in Immunology (2017): 27–36
    • Application of phospho-CyTOF® to characterize immune activation in patients with sickle cell anemia in an ex vivo model of thrombosis
      Glassberg, J., Rahman, A.H., Zafar, M. et al. Journal of Immunological Methods (2018): 11–19
    • STING-associated vasculopathy develops independently of IRF3 in mice
      Warner, J.D., Irizarry-Caro, R.A., Bennion, B.G. et al. Journal of Experimental Medicine (2017): 3,279–92
    • β-Cells are not uniform after all-Novel insights into molecular heterogeneity of insulin-secreting cells
      Avrahami, D., Wang, Y.J., Klochendler, A. et al. Diabetes, Obesity and Metabolism (2017): 147–52
    • Dietary gluten triggers concomitant activation of CD4+ and CD8+ αβ T cells and γδ T cells in celiac disease
      Han, A., Newell, E.W., Glanville, J. et al. Proceedings of the National Academy of Sciences (2013): 13,073–8

  • Method Development

    • 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
    • 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
    • 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 (2019): 215-229
    • 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
    • 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): doi: 10.1002/cyto.a.23621
    • Protein Barcodes Enable High-Dimensional Single-Cell CRISPR Screens
      Wroblewska, A., Dhainaut, M., Ben-Zvi, B. et al. Cell (2018): doi: 10.1016/j.cell.2018.09.022
    • Development of a click-chemistry reagent compatible with mass cytometry
      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
      Wu, X., DeGottardi, Q., Wu, I.C. et al. Angewandte Chemie (2017): 14,908–12
    • 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
    • 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
    • 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
      Nassar, A.F., Wisnewiski, A.V., Raddassi, K. Bioanalysis (2016): 255–7
    • Research techniques made simple: experimental methodology for single-cell mass cytometry
      Matos, T.R., Liu, H., Ritz, J. Journal of Investigative Dermatology (2017): e31–8
    • A CD45-based barcoding approach to multiplex mass-cytometry (CyTOF®)
      Lai, L., Ong, R., Li, J., Albini, S. Cytometry, Part A (2015): 369–74
    • CyTOF® mass cytometry for click proliferation assays
      Tosevski, V., Ulashchik, E., Trovato, A. et al. Current Protocols in Cytometry (2017): 7.50.1–14
    • CyTOF® supports efficient detection of immune cell subsets from small samples
      Yao, Y., Liu, R., Shin, M.S. et al. Journal of Immunological Methods (2014): 1–5
    • 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
      Aran, D., Hu, Z., Butte, A.J. Genome Biology (2017): 220
    • 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
    • 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 (2008): 443–9
    • 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
    • Inductively coupled plasma mass spectrometry-based immunoassay: a review
      Liu, R., Wu, P., Yang, L. et al. Mass Spectrometry Reviews (2014): 373–93
    • Multiple cellular antigen detection by ICP-MS
      Ornatsky, O., Baranov, V.I., Bandura, D.R. et al. Journal of Immunological Methods (2006): 68–76
    • 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
    • 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
    • A practical guide to multiplexed mass cytometry
      Zivanovic, N., Jacobs, A., Bodenmiller, B. Current Topics in Microbiology and Immunology (2014): 95–109
    • 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
    • Development of inductively coupled plasma-mass spectrometry-based protease assays
      Lathia, U.S., Ornatsky, O., Baranov, V., Nitz, M. Analytical Biochemistry (2009): 93–8
    • Twenty (forward looking) questions
      Hassell, L.A., Wagar, E.A. Journal of Pathology Informatics (2014): 27
    • Multiplexed protease assays using element-tagged substrates
      Lathia, U.S., Ornatsky, O., Baranov, V., Nitz, M. Analytical Biochemistry (2010): 157–9
    • 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
      de Souza, N. Nature Methods (2012): 35
    • Analysis, Isolation, and Activation of Antigen-Specific CD4+ and CD8+ T Cells by Soluble MHC-Peptide Complexes
      Schmidt, J., Dojcinovic, D., Guillaume, P., Luescher, I. Frontiers in Immunology (2013): 218
    • 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

  • Oncology

    • Expression of PD-1 by T cells in malignant glioma patients reflects exhaustion and activation
      Davidson, T.B., Lee, A.H., Hsu, M. et al. Cliniical Cancer Research (2018): doi: 10.1158/1078-0432.CCR-18-1176
    • Cdh1 and Pik3ca Mutations Cooperate to Induce Immune-Related Invasive Lobular Carcinoma of the Breast
      An, Y., Adams, J.R., Hollern, D.P. et al. Cell Reports (2018): 702–14
    • Antigen-mediated regulation in monoclonal gammopathies and myeloma
      Nair, S., Sng, J., Boddupalli, C.S. et al. JCI Insight (2018): doi: 10.1172/jci.insight.98259
    • Targeting small molecule drugs to T cells with antibody-directed cell-penetrating gold nanoparticles
      Yang, Y.S., Moynihan, K.D., Bekdemir, A. et al. Biomaterials Science (2018): 240-52
    • Intratumoral HPV16-Specific T Cells Constitute a Type I-Oriented Tumor Microenvironment to Improve Survival in HPV16-Driven Oropharyngeal Cancer
      Welters, M.J.P., Ma., W., Santegoets, S.J.A.M. et al. Clinical Cancer Research (2018): 634-47
    • EPH Profiling of BTIC Populations in Glioblastoma Multiforme Using CyTOF
      Hu, A.X., Adams, J.J., Vora, P. et al. Brain Tumor Stem Cells (2018): 155-68
    • DRUG-NEM: Optimizing drug combinations using single-cell perturbation response to account for intratumoral heterogeneity
      Anchang, B., Davis, K.L., Fienberg, H.G. et al. PNAS (2018): E4294–303
    • Activation of the Receptor Tyrosine Kinase AXL Regulates the Immune Microenvironment in Glioblastoma
      Sadahiro, H., Kang, K.D., Gibson, J.T. et al. Cancer Research (2018): 3,002-13
    • Characterization of TRKA signaling in acute myeloid leukemia
      Hebrich, S.M., Kannan, S., Nolo, R.M. et al. Oncotarget (2018): 30,092–105
    • Co-targeting ephrin receptor tyrosine kinases A2 and A3 in cancer stem cells reduces growth of recurrent glioblastoma
      Qazi, M.A., Vora, P., Venugopal, C. et al. Cancer Research (2018): doi: 10.1158/0008-5472.CAN-18-0267
    • Ovarian cancer cells cisplatin sensitization agents selected by mass cytometry target ABCC2 inhibition
      Comsa, E., Nguyen, K.A., Loghin, F. et al. Future Medicinal Chemistry (2018): 1,349-60
    • Regulatory T cells in ovarian cancer are characterized by a highly activated phenotype distinct from that in melanoma
      Toker, A., Nguyen, L.T., Stone, S.C. et al. Clinical Cancer Research (2018): DOI: 10.1158/1078-0432.CCR-18-0554
    • BRAF and MEK inhibitor therapy eliminates Nestin-expressing melanoma cells in human tumors
      Doxie, D.B., Greenplate, A.R., Gandelman, J.S. et al. Pigment Cell and Melanoma Research (2018): doi: 10.1111/pcmr.12712
    • Clonal diversity revealed by morphoproteomic and copy number profiles of single prostate cancer cells at diagnosis
      Malihi, P.D., Morikado, M., Welter, L. et al. Convergent Science Physical Oncology (2018): doi: 10.1088/2057-1739/aaa00b
    • Combined inhibition of β-catenin and Bcr-Abl synergistically targets tyrosine kinase inhibitor-resistant blast crisis chronic myeloid leukemia blasts and progenitors in vitro and in vivo
      Zhou, H., Mak, P.Y., Mu, H. et al. Leukemia (2017): 2,065–74
    • High-dimensional single cell mapping of cerium distribution in the lung immune microenvironment of an active smoker
      Rahman, A.H., Lavin, Y., Kobayashi, S. et al. Cytometry Part B: Clinical Cytometry (2017): doi: 10.1002/cyto.b.21545
    • Cholesterol esterification inhibition and imatinib treatment synergistically inhibit growth of BCR-ABL mutation-independent resistant chronic myelogenous leukemia
      Bandyopadhyay, S., Li, J., Traer, E. et al. PLoS One (2017): e0179558
    • Discovery of human cell selective effector molecules using single cell multiplexed activity metabolomics
      Earl, D.C., Ferrell, P.B. Jr., Leelatian, N. et al. Nature Communications (2018): 39
    • Macrophages orchestrate breast cancer early dissemination and metastasis
      Linde, N., Casanova-Acebes, M., Sosa, M.S. et al. Nature Communications (2018): 21
    • Apatinib exhibits anti-leukemia activity in preclinical models of acute lymphoblastic leukemia
      Deng, M., Zha, J., Jiang, Z. et al. Journal of Translational Medicine (2018): 47
    • Recent advances and opportunities in proteomic analyses of tumour heterogeneity
      Bateman, N.W., Conrads, T.P. The Journal of Pathology (2018): 628–37
    • SOX11 augments BCR signaling to drive MCL-like tumor development
      Kuo, P.Y., Jatiani, S.S., Rahman, A.H. et al. Blood (2018): 2,247–55
    • Deep Profiling of the Immune System of Multiple Myeloma Patients Using Cytometry by Time-of-Flight (CyTOF)
      Smets, T., Stevenaert, F., Adams, H. et al. Methods in Molecular Biology (2018): 47–54
    • Single-cell mass cytometry reveals intracellular survival/proliferative signaling in FLT3-ITD-mutated AML stem/progenitor cells
      Han, L., Qiu, P., Zeng, Z. et al. Cytometry, Part A (2015): 346–56
    • Defining Renal Neoplastic Disease, One Cell at a Time: Mass Cytometry, a New Tool for the Study of Kidney Biology and Disease
      Nelson, P.J., Kretzler, M. American Journal of Kidney Diseases (2017): 758–61
    • Pregnane X receptor is associated with unfavorable survival and induces chemotherapeutic resistance by transcriptional activating multidrug resistance-related protein 3 in colorectal cancer
      Dong, Y., Wang, Z., Xie, G.F. et al. Molecular Cancer (2017): 71
    • Checkpoint blockade immunotherapy reshapes the high-dimensional phenotypic heterogeneity of murine intratumoural neoantigen-specific CD8+ T cells
      Fehlings, M., Simoni, Y., Penny, H.L. et al. Nature Communications (2017): 562
    • Single cell immune profiling by mass cytometry of newly diagnosed chronic phase chronic myeloid leukemia treated with nilotinib
      Gullaksen, S.E., Skavland, J., Gavasso, S. et al. Haematologica 1,361–7
    • Expression of LAG-3 defines exhaustion of intratumoral PD-1+ T cells and correlates with poor outcome in follicular lymphoma
      Yang, Z.Z., Kim, H.J., Villasboas, J.C. et al. Oncotarget (2017): 61,425–39
    • Novel BET protein proteolysis-targeting chimera exerts superior lethal activity than bromodomain inhibitor (BETi) against post-myeloproliferative neoplasm secondary (s) AML cells
      Saenz, D.T., Fiskus, W., Qian, Y. et al. Leukemia (2017): 1,951–61
    • Colony Lysate Arrays for Proteomic Profiling of Drug-Tolerant Persisters of Cancer Cell
      Kume, Kohei, Nishizuka, S.S. Analytical Chemistry (2017): 8,626–31
    • Mass cytometry analysis reveals hyperactive NF Kappa B signaling in myelofibrosis and secondary acute myeloid leukemia
      Fisher, D.A., Malkova, O., Engle, E.K. et al. Leukemia (2017): 1,962–74
    • Phenotypic and functional characterization of a bortezomib-resistant multiple myeloma cell line by flow and mass cytometry
      Baughn, L.B., Sachs, Z., Noble-Orcutt, K.E. et al. Leukemia and Lymphoma (2017): 1,931–40
    • PARP inhibitor upregulates PD-L1 expression and enhances cancer-associated immunosuppression
      Jiao, S., Xia, W., Yamaguchi, H. et al. Clinical Cancer Research (2017): 3,711–20
    • Cytokine-induced memory-like natural killer cells exhibit enhanced responses against myeloid leukemia
      Romee, R., Rosario, M., Berriern-Elliott, M.M. et al. Science Translational Medicine (2016): 357
    • The novel BMI-1 inhibitor PTC596 downregulates MCL-1 and induces p53-independent mitochondrial apoptosis in acute myeloid leukemia progenitor cells
      Nishida, Y., Maeda, A., Kim, M.J. et al. Blood Cancer Journal (2017): e527
    • Overexpression of the human antigen R suppresses the immediate paradoxical proliferation of melanoma cell subpopulations in response to suboptimal BRAF inhibition
      Fernandez, M., Sutterlüty‐Fall, H., Schwärzler, C. et al. Cancer Medicine (2017): 1,652–64
    • Emerging understanding of multiscale tumor heterogeneity
      Gerdes, M.J., Sood, A., Sevinsky, C. et al. Frontiers in Oncology (2014): 366
    • Unraveling cell populations in tumors by single-cell mass cytometry
      Di Palma S., Bodenmiller B. Current Opinion in Biotechnology (2015): 122–9
    • Mass cytometric functional profiling of acute myeloid leukemia defines cell-cycle and immunophenotypic properties that correlate with known responses to therapy
      Behbahni, G.K., Samusik, N., Bjornson, Z.B. et al. Cancer Discovery (2015): 988–1,003
    • Eradication of CML stem cells
      Carter, B.Z., Andreeff, M. Oncoscience (2016): 313–5
    • NRASG12V oncogene facilitates self-renewal in a murine model of acute myelogenous leukemia
      Sachs, Z., LaRue, R.S., Nguyen, H.T. et al. Blood (2014): 3,274–83
    • Dasatinib changes immune cell profiles concomitant with reduced tumor growth in several murine solid tumor models
      Hekim, C., Ilander, M., Yan, J. et al. Cancer Immunology Research (2017): 157–69
    • Mutant IDH1 Downregulates ATM and Alters DNA Repair and Sensitivity to DNA Damage Independent of TET2
      Inoue, S., Li, W.Y., Tseng, A. et al. Cancer Cell (2016): 337–48
    • PD-1 marks dysfunctional regulatory T cells in malignant gliomas
      Lowther, D.E., Goods, B.A., Lucca, L.E. et al. Journal of Clinical Investigation (2016): e85935
    • Single-cell measurement of the uptake, intratumoral distribution and cell cycle effects of cisplatin using mass cytometry
      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
    • Messenger RNA Detection in Leukemia Cell lines by Novel Metal-Tagged in situ Hybridization using Inductively Coupled Plasma Mass Spectrometry
      Ornatsky, O., Baranov, V.I., Bandura, D.R. et al. Translational Oncogenomics (2014): 1–9
    • 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
    • Isotopologous Organotellurium Probes Reveal Dynamic Hypoxia In Vivo with Cellular Resolution
      Edgar, L.J., Vellanki, R.N., McKee, T.D. et al Angewandte Chemie (2016): 13,159–63
    • 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
    • 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
    • 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
    • Characterization of phosphorus content of biological samples by ICP-DRC-MS: potential tool for cancer research
      Bandura, D.R., Ornatsky, O.I., Liao, L. Journal of Analytical Atomic Spectrometry (2014): 96–100
    • Monitoring the Immune Competence of Cancer Patients to Predict Outcome
      Chang, S., Kohrt, H., Maecker, H.T. Cancer Immunology, Immunotherapy (2014): 713–9

  • Review

    • 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
    • Advancing systems immunology through data-driven statistical analysis
      Fong, L.E., Muñoz-Rojas, A.R., Miller-Jensen, K. Current Opinion in Biotechnology (2018): 109-15
    • 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

    • 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): doi: 10.1038/s41587-019-0033-2.
    • Serial transplantation reveals a critical role for endoglin in hematopoietic stem cell quiescence
      Borges, L, Oliveira, V.K.P., Baik, J. et al. Blood (2018): doi: 10.1182/blood-2018-09-874677
    • Tumor Platinum Concentrations and Pathological Responses Following Cisplatin-Containing Chemotherapy in Gastric Cancer Patients
      Cao, Y., Chang, Q., Cabanero, M. et al. Journal of Gastrointestinal Cancer (2018): doi: 10.1007/s12029-018-0153-9
    • The impact of ischemia-reperfusion injuries on skin resident murine dendritic cells
      Goh, C.C., Evrard, M., Chong, S.Z. et al. European Journal of Immunology (2018): 1,014-9
    • Single Cell Proteomics for Molecular Targets in Lung Cancer: High-Dimensional Data Acquisition and Analysis
      Wang, Z., Zhang, X. Advances in Experimental and Medical Biology (2018): 73-87
    • Single Cell Genetics and Epigenetics in Early Embryo: From Oocyte to Blastocyst
      Wei, Y., Zhang, H., Wang, Q. et al. Advances in Experimental and Medical Biology (2018): 103-17
    • Structural Remodeling of the Human Colonic Mesenchyme in Inflammatory Bowel Disease
      Kinchen, J., Chen, H.H., Parikh, K. et al. Cell Reports (2018): 372-86
    • Thrombopoietin Metabolically Primes Hematopoietic Stem Cells to Megakaryocyte-Lineage Differentiation
      Nakamura-Ishizu, A., Matsumura, T., Stumpf, P.S. et al. Cell Reports (2018): 1,772-85
    • Human Intestinal Allografts Contain Functional Hematopoietic Stem and Progenitor Cells that Are Maintained by a Circulating Pool
      Fu, J., Zuber, J., Martinez, M. et al. Cell Stem Cell (2018): doi: 10.1016/j.stem.2018.11.007
    • Defining human cardiac transcription factor hierarchies using integrated single-cell heterogeneity analysis
      Churko, J.M., Garg, P., Treutlein, B. et al. Nature Communications (2018): 4,906
    • Immune and metabolic shifts during neonatal development reprogram liver identity and function
      Nakagaki, B.N., Mafra, K., de Carvalho, É. et al. Journal of Hepatology (2018): 1,2394-307
    • Mass Cytometry for the Assessment of Immune Reconstitution After Hematopoietic Stem Cell Transplantation
      Stern, L., McGuire, H., Avdic, S. et al. Frontiers in Immunology (2018): 1672
    • High-Dimensional Phenotypic Mapping of Human Dendritic Cells Reveals Interindividual Variation and Tissue Specialization
      Alcántara-Hernández M., Leylek, R., Wagar, L.E. et al. Immunity (2017): 1,037–50
    • MYB fusions and CD markers as tools for authentication and purification of cancer stem cells from salivary adenoid cystic carcinoma
      Panaccione, A., Zhang, Y., Ryan, M. et al. Stem Cell Research (2017): 160-6
    • Reconstitution of immune cell populations in multiple sclerosis patients after autologous stem cell transplantation
      Karnell, F.G., Lin, D., Motley, S. et al. Clinical and Experimental Immunology (2017): 268–78
    • Pathologically expanded peripheral T helper cell subset drives B cells in rheumatoid arthritis
      Rao, D.A., Gurish, M.F., Marshall, J.L. et al. Nature (2017): 110–4
    • Proceedings: immune tolerance and stem cell transplantation: a CIRM mini-symposium and workshop report
      Talib, S., Millan, M.T., Jorgenson, R.L., Shepard, K.A. Stem Cells Translational Medicine (2015): 4–9
    • Charting a map through the cellular reprogramming landscape
      Wen, L., Tang, F. Cell Stem Cell (2016): 215–6
    • High-resolution myogenic lineage mapping by single-cell mass cytometry
      Porpiglia, E., Samusik, N., Van Ho, A.T. et al. Nature Cell Biology (2017): 558–67
    • A continuous molecular roadmap to iPSC reprogramming through progression analysis of single-cell mass cytometry
      Zunder, E.R., Lujan, E., Goltsev, Y. et al. Cell Stem Cell (2015): 323–37
    • Early reprogramming regulators identified by prospective isolation and mass cytometry
      Lujan, E., Zunder, E.R., Ng, Y.H. et al. Nature (2015): 352–6
    • Cell expansion during directed differentiation of stem cells toward the hepatic lineage
      Raju, R., Chau, D., Cho, D.S. et al. Stem Cells and Development (2016): 274–84
    • Distinct signaling programs control human hematopoietic stem cell survival and proliferation
      Knapp, D.J., Hammond, C.A., Aghaeepour, N. et al. Blood (2016): 307–18
    • Combination Of Mass Cytometry and Imaging Analysis Reveals Origin, Location, and Functional Repopulation of Liver Myeloid Cells in Mice
      David, B.A., Rezende, R.M., Antunes, M.M. et al. Gastroenterology (2016): 1,176–91
    • High-dimensional analysis of the murine myeloid cell system
      Becher, B., Schlitzer, A., Chen, J. et al. Nature Immunology (2014): 1,181–9
    • Low-dose IL-2 selectively activates subsets of CD4+ Tregs and NK cells
      Hirakawa, M., Matos, T., Liu, H. et al. JCI Insight (2016): e89278
    • Studying hematopoiesis using single-cell technologies
      Ye, F., Huang, W., Guo, G. Journal of Hematology and Oncology (2017): 27

  • Other

    • Flow Cytometry: Definition, History, and Uses in Biological Research
      Bonnevier, J., Hammerbeck, C., Goetz, C. et al. Flow Cytometry Basics for the Non-Expert (2018): DOI: 10.1007/978-3-319-98071-3_1
    • Activation of S6 signaling is associated with cell survival and multinucleation in hyperplastic skin after epidermal loss of AURORA-A Kinase
      Ryan, W.K., Fernandez, J., Peterson, M.K. et al. Cell Death and Differentiation (2018): doi: 10.1038/s41418-018-0167-7
    • Single-cell technologies are revolutionizing the approach to rare cells
      Proserpio, V., Lönnberg, T. Immunology & Cell Biology (2016): 225–9
    • Applications of mass cytometry in clinical medicine: the promise and perils of clinical CyTOF^®
      Behbehani, G.K. Clinics in Laboratory Medicine (2017): 945–64
    • CyTOF® analysis of anti-tumor responses
      Dempsey, L.A. Nature Immunology (2017): 254
    • Diverse continuum of CD4+ T-cell states is determined by hierarchical additive integration of cytokine signals
      Eizenberg-Magar, I., Rimer, J., Zaretsky, I. et al. Proceedings of the National Academy of Sciences of the United States of America (2017): E6447–56
    • Cytometry: today’s technology and tomorrow’s horizons
      Chattopadhyay, P., Roederer, M. Methods (2012): 251–8
    • Protein Ontology: a controlled structured network of protein entities
      Natale, D.A., Arighi, C.N., Blake, J.A. et al. Nucleic Acids Research (2013): D415–D421
    • Immunology. Flow cytometry, amped up
      Benoist, C., Hacohen, N. Science (2011): 677–8
    • Methods for discovery and characterization of cell subsets in high dimensional mass cytometry data
      Diggins, K.E., Ferrell, P.B. Jr., Irish, J.M. Methods (2015): 55–63
    • A mine is a terrible thing to waste: high content, single cell technologies for comprehensive immune analysis
      Chattopadhyay, P.K., Roederer, M. American Journal of Transplantation (2015): 1,155–61
    • Systems Biology Analysis of Heterocellular Signaling
      Tape, C.J. Trends in Biotechnology (2016): 627–37
    • SWIFT—Scalable Clustering for Automated Identification of Rare Cell Populations in Large, High-Dimensional Flow Cytometry Datasets, Part 2: Biological Evaluation
      Mosmann, T.R., Naim, I., Rebhahn, J. et al. Cytometry Plan A (2014): 422–33
    • Coordinated Surgical Immune Signatures Contain Correlates of Clinical Recovery
      Gaudillière, B., Fragiadakis, G.K., Bruggner, R.V. et al. Science Translational Medicine (2014): 131
    • The road ahead: Implementing mass cytometry in clinical studies, one cell at a time
      Baca, Q., Cosma, A., Nolan, G. et al. Cytometry Part B: Clinical Cytometry (2016): 10–11
    • Next-generation flow cytometry
      Janes, M.R., Rommel, C. Nature Biotechnology (2011): 602–4
    • Cycling into Future: Mass Cytometry for the Cell-Cycle Analysis
      Darzynkiewicz, Z. Cytometry, Part A (2012): 546–8
    • A flow cytometry revolution
      Doerr, A. Nature Methods (2011): 531