Abstract
As therapies involving the modulation, stimulation, and deliberate excitation of the immune system are becoming routine, better methods for monitoring immune responses in human patients are needed. Mass cytometry allows for detailed profiling of all immune cell populations and their functional responses using a simple blood sample. When combined with appropriate computational analyses, the resolution for distinguishing desired responses from unproductive or even adverse reactions to immunotherapeutic interventions increases. Here we describe a core experimental and computational framework for global, systems-level immune monitoring by mass cytometry.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bandura DR, Baranov VI, Ornatsky OI et al (2009) Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry. Anal Chem 81:6813–6822
Bendall SC, Simonds EF, Qiu P et al (2011) Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 332:687–696
Brodin P, Jojic V, Gao T et al (2015) Variation in the human immune system is largely driven by non-heritable influences. Cell 160:37–47
Kaczorowski KJ, Shekhar K, Nkulikiyimfura D et al (2017) Continuous immunotypes describe human immune variation and predict diverse responses. Proc Natl Acad Sci U S A 114:E6097–E6106
Wong MT, Ong DE, Lim FS et al (2016) A high-dimensional atlas of human T cell diversity reveals tissue-specific trafficking and cytokine signatures. Immunity 45:442–456
Newell EW, Sigal N, Nair N et al (2013) Combinatorial tetramer staining and mass cytometry analysis facilitate T-cell epitope mapping and characterization. Nat Biotechnol 31:623–629
Chevrier S, Levine JH, VRT Z et al (2017) An immune atlas of clear cell renal cell carcinoma. Cell 169:736–749 e18
Lavin Y, Kobayashi S, Leader A et al (2017) Innate immune landscape in early lung adenocarcinoma by paired single-cell analyses. Cell 169:750–765 e17
Lakshmikanth T, Olin A, Chen Y et al (2017) Mass cytometry and topological data analysis reveal immune parameters associated with complications after allogeneic stem cell transplantation. Cell Rep 20:2238–2250
Wei SC, Levine JH, Cogdill AP et al (2017) Distinct cellular mechanisms underlie anti-CTLA-4 and anti-PD-1 checkpoint blockade. Cell 170:1120–1133 e17
Phelan MC and Lawler G (2001) Cell counting. Current Protocols in Cytometry 00:A.3A.1–A.3A.4
Shekhar K, Brodin P, Davis MM et al (2014) Automatic classification of cellular expression by nonlinear stochastic embedding (ACCENSE). Proc Natl Acad Sci U S A 111:202–207
Weber LM, Robinson MD (2016) Comparison of clustering methods for high-dimensional single-cell flow and mass cytometry data. Cytometry A 89:1084–1096
Brodin P, Davis MM (2016) Human immune system variation. Nat Rev Immunol 17:21–29
Lou X, Zhang G, Herrera I et al (2007) Polymer-based elemental tags for sensitive bioassays. Angew Chem Int Ed 46:6111–6114
Sumatoh HR, Teng KW, Cheng Y et al (2017) Optimization of mass cytometry sample cryopreservation after staining. Cytometry A 91:48–61
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Lakshmikanth, T., Brodin, P. (2019). Systems-Level Immune Monitoring by Mass Cytometry. In: Pico de Coaña, Y. (eds) Immune Checkpoint Blockade. Methods in Molecular Biology, vol 1913. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8979-9_3
Download citation
DOI: https://doi.org/10.1007/978-1-4939-8979-9_3
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-8978-2
Online ISBN: 978-1-4939-8979-9
eBook Packages: Springer Protocols