CyTOF Measurement of Immunocompetence Across Major Immune Cell Types

Priyanka B. Subrahmanyam1, Holden T. Maecker2

1 Post‐doctoral Research Fellow, Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, 2 Professor, Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford
Publication Name:  Current Protocols in Cytometry
Unit Number:  Unit 9.54
DOI:  10.1002/cpcy.27
Online Posting Date:  October, 2017
GO TO THE FULL TEXT: PDF or HTML at Wiley Online Library


The central role of the immune system is becoming appreciated in a wide variety of diseases. Cancer immunotherapy is one area that has yielded much recent success, although not all patients benefit equally. At the same time, recent studies have highlighted the heterogeneity of the human immune system. Despite this heterogeneity, we do not routinely measure immune competence in clinical practice, and there are no consensus assays of healthy immune function. Using mass cytometry (CyTOF), we can simultaneously detect ∼40 markers to identify various cell subsets and determine their function by the expression of cytokines, cytotoxicity, and activation markers. This can help assess ‘immunocompetence’ and facilitate better implementation of immunotherapies, both in specific disease settings and perhaps eventually as a prognostic tool in healthy subjects. Here we introduce the concepts behind this assay and provide a protocol that we have successfully implemented to identify possible predictive biomarkers of immunotherapy outcome. © 2017 by John Wiley & Sons, Inc.

Keywords: CyTOF; immunotherapy; immune profiling; biomarkers

PDF or HTML at Wiley Online Library

Table of Contents

  • Reagents and Solutions
  • Commentary
  • Literature Cited
  • Figures
  • Tables
PDF or HTML at Wiley Online Library


Basic Protocol 1:

  • Complete medium (see recipe)
  • Pierce Universal Nuclease, 25 kU (ThermoFisher Scientific, at. no. 88701)
  • Human PBMC sample
  • Stimulation reagents and secretion inhibitors (Table 9.54.2)
  • EDTA, 0.5 M (Gibco, cat. no. 15575)
  • CyFACS (see recipe)
  • Maleimide‐DOTA loaded with 115In, 5 mg/ml (Macrocyclics, cat. no. B‐272)
  • CyPBS (see recipe)
  • Paraformaldehyde, 16% (w/v) (Alfa Aesar, cat. no. 43368)
  • 10× permeabilization buffer (eBioscience, cat. no. 00‐8333‐56)
  • Brefeldin A (Sigma‐Aldrich, cat. no. B7651)
  • Monensin, 1000× (BioLegend, cat. no. 420701)
  • Phorbol 12‐myristate 13‐acetate (PMA; Sigma‐Aldrich, cat. no. P8139)
  • Ionomycin (Sigma‐Aldrich, cat. no. I0634)
  • Cell ID Ir‐Intercalator (193Ir/195Ir), 1000× (Fluidigm, cat. no. 201192A)
  • EQ Four Element calibration beads (Fluidigm, cat. no. 201078)
  • 1.5‐ml, 15‐ml, and 50‐ml conical tubes
  • Centrifuge with adaptors to fit 15‐ml conical tubes and 1.5‐ml microcentrifuge tubes
  • 96‐well U‐bottom plates (Corning Falcon, cat. no. 353077)
  • Centrifugal filter units, 0.1 μm (Millipore, cat. no. UFC30VV00)
  • 5‐ml polystyrene tubes with cell‐strainer caps (Corning Falcon, cat. no. 352235)
  • Additional reagents and equipment for counting cells ( appendix 3A; Phelan & Lawler, )
Table 9.4.2   MaterialsStimulation of Cells

Reagent Intermediate stock dilution Final concentration (unstimulated) Final concentration (PMA + ionomycin)
Brefeldin A (5 mg/ml in DMSO) 1:10 in CyPBS 5 μg/ml 1:100 of intermediate stock 5 μg/ml 1:100 of intermediate stock
Monensin (1000×) 1:10 in CyPBS 1× 1:100 of intermediate stock 1× 1:100 of intermediate stock
PMA (1 mg/ml in DMSO) 1:1000 in CyPBS 10 ng/ml 1:100 of intermediate stock
Ionomycin (1 mg/ml in DMSO) 1:10 in CyPBS 1 μg/ml 1:100 of intermediate stock

NOTE: All solutions should be stored in metal‐free containers. Typically, sterile plasticware, tubes, filters, and new, never‐washed glassware are metal‐free. Glassware used should never have been washed, since soap can cause barium contamination.
PDF or HTML at Wiley Online Library



Literature Cited

Literature Cited
  Amir, E. D., Davis, K. L., Tadmor, M. D., Simonds, E. F., Levine, J. H., Bendall, S. C., … Pe'er, D. (2013). viSNE enables visualization of high dimensional single‐cell data and reveals phenotypic heterogeneity of leukemia. Nature Biotechnology, 31, 545–552. doi: 10.1038/nbt.2594.
  Apoil, P. A., Puissant‐Lubrano, B., Congy‐Jolivet, N., Peres, M., Tkaczuk, J., Roubinet, F., & Blancher, A. (2017). Reference values for T, B and NK human lymphocyte subpopulations in adults. Data in Brief, 12, 400–404. doi: 10.1016/j.dib.2017.04.019.
  Bandura, D. R., Baranov, V. I., Ornatsky, O. I., Antonov, A., Kinach, R., Lou, X., … Tanner, S. D. (2009). Mass cytometry: Technique for real time single cell multitarget immunoassay based on inductively coupled plasma time‐of‐flight mass spectrometry. Analytical Chemistry, 81, 6813–6822. doi: 10.1021/ac901049w.
  Bendall, S. C., Simonds, E. F., Qiu, P., Amir, E. D., Krutzik, P. O., Finck, R., … Nolan, G. P. (2011). Single‐cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science, 332, 687–696. doi: 10.1126/science.1198704.
  Bjornson, Z. B., Nolan, G. P., & Fantl, W. J. (2013). Single‐cell mass cytometry for analysis of immune system functional states. Current Opinion in Immunology, 25, 484–494. doi: 10.1016/j.coi.2013.07.004.
  Brodin, P., & Davis, M. M. (2017). Human immune system variation. Nature Reviews. Immunology, 17, 21–29. doi: 10.1038/nri.2016.125.
  Brodin, P., Jojic, V., Gao, T., Bhattacharya, S., Angel, C. J. L., Furman, D., … Davis, M. M. (2015).Variation in the human immune system is largely driven by non‐heritable influences. Cell, 160, 37–47. doi: 10.1016/j.cell.2014.12.020.
  Bruggner, R. V., Bodenmiller, B., Dill, D. L., Tibshirani, R. J., & Nolan, G. P. (2014). Automated identification of stratifying signatures in cellular subpopulations. Proceedings of the National Academy of Sciences of the United States of America, 111, E2770–7. doi: 10.1073/pnas.1408792111.
  Chang, S., Kohrt, H., & Maecker, H. T. (2014). Monitoring the immune competence of cancer patients to predict outcome. Cancer Immunology, Immunotherapy, 63, 713–719. doi: 10.1007/s00262‐014‐1521‐3.
  Costantini, A., Mancini, S., Giuliodoro, S., Butini, L., Regnery, C. M., Silvestri, G., & Montroni, M. (2003). Effects of cryopreservation on lymphocyte immunophenotype and function. Journal of Immunological Methods, 278, 145–155. doi: 10.1016/S0022‐1759(03)00202‐3.
  Gnjatic, S., Bronte, V., Brunet, L. R., Butler, M. O., Disis, M. L., Galon, J., … Butterfield, L. H. (2017). Identifying baseline immune‐related biomarkers to predict clinical outcome of immunotherapy. Journal for Immunotherapy of Cancer, 5, 44. doi: 10.1186/s40425‐017‐0243‐4.
  Hiniker, S. M., Reddy, S. A., Maecker, H. T., Subrahmanyam, P. B., Rosenberg‐Hasson, Y., Swetter, S. M., … Knox, S. J. (2016). A prospective clinical trial combining radiation therapy with systemic immunotherapy in metastatic melanoma. International Journal of Radiation Oncology, Biology, Physics, 96, 578–588. doi: 10.1016/j.ijrobp.2016.07.005.
  Lin, D., Gupta, S., & Maecker, H. T. (2015). Intracellular cytokine staining on PBMCs using CyTOF mass cytometry. Bio‐protocol, 5, 1370. doi: 10.21769/BioProtoc.1370.
  Lovelace, P., & Maecker, H. T. (2011). Multiparameter intracellular cytokine staining. Methods in Molecular Biology, 699, 165–178. doi: 10.1007/978‐1‐61737‐950‐5_8.
  Maecker, H. T., & Harari, A. (2015). Immune monitoring technology primer: Flow and mass cytometry. Journal for Immunotherapy of Cancer, 3, 44. doi: 10.1186/s40425‐015‐0085‐x.
  Maecker, H. T., Rinfret, A., Souza, P. D’, Darden, J., Roig, E., Landry, C., … Sekaly, R. P. (2005). Standardization of cytokine flow cytometry assays. BMC Immunology, 6, 13. doi: 10.1186/1471‐2172‐6‐13.
  Phelan, M. C., & Lawler, G. (2001). Cell counting. Current Protocols in Cytometry, 00, A.3A.1–A.3A.4. doi: 10.1002/0471142956.cya03as00.
  Qiu, P., Simonds, E. F., Bendall, S. C., Gibbs, K. D., Bruggner, R. V., Linderman, M. D., … Plevritis, S. K. (2011). Extracting a cellular hierarchy from high‐dimensional cytometry data with SPADE. Nature Biotechnology, 29, 886–891. doi: 10.1038/nbt.1991.
  Valiathan, R., Deeb, K., Diamante, M., Ashman, M., Sachdeva, N., & Asthana, D. (2014). Reference ranges of lymphocyte subsets in healthy adults and adolescents with special mention of T cell maturation subsets in adults of South Florida. Immunobiology, 219, 487–496. doi: 10.1016/j.imbio.2014.02.010.
PDF or HTML at Wiley Online Library