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.
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Overview
Number of papers per research area as of 十二月, 2019Number of cumulative papers as of 十二月, 2019 -
Recent
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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
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Proliferation tracing with single-cell mass cytometry optimizes generation of stem cell memory-like T cells
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Research Areas
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Biomarker Screening
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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
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A high-sensitivity lanthanide nanoparticle reporter for mass cytometry: tests on microgels as a proxy for cells
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Data Analysis Methods
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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
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Visualizing Structure and Transitions for Biological Data Exploration
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IO
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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
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Macrophage migration inhibitory factor regulates U1-snRNP immune complex mediated activation of the NLRP3 inflammasome
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Immunology
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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
Gubin, M.M., Esaulova, E., Ward, J.P. et al. Cell (2018): 1,662–70 -
Atherosclerosis in the single-cell era
Winkels, H., Ehinger, E., Ghosheh, Y. et al. Current Opinion in Lipidology (2018): 389–96 -
Identification of an Early Unipotent Neutrophil Progenitor with Pro-tumoral Activity in Mouse and Human Bone Marrow
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A Prospective Clinical Trial Combining Radiation Therapy With Systemic Immunotherapy in Metastatic Melanoma
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NCR1 Expression Identifies Canine Natural Killer Cell Subsets with Phenotypic Similarity to Human Natural Killer Cells
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Defining human cardiac transcription factor hierarchies using integrated single-cell heterogeneity analysis
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Immune and metabolic shifts during neonatal development reprogram liver identity and function
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Mass Cytometry for the Assessment of Immune Reconstitution After Hematopoietic Stem Cell Transplantation
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MYB fusions and CD markers as tools for authentication and purification of cancer stem cells from salivary adenoid cystic carcinoma
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Charting a map through the cellular reprogramming landscape
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Combination Of Mass Cytometry and Imaging Analysis Reveals Origin, Location, and Functional Repopulation of Liver Myeloid Cells in Mice
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Flow Cytometry: Definition, History, and Uses in Biological Research
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