Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-848d4c4894-4rdrl Total loading time: 0 Render date: 2024-07-06T04:43:41.141Z Has data issue: false hasContentIssue false

14 - Future Applications of Flow Cytometry and Related Techniques

Published online by Cambridge University Press:  01 February 2018

By
Marie-Christine Béné  and
Francis Lacombe
Edited by
Anna Porwit  and
Marie Christine Béné
Anna Porwit
Affiliation:
Lunds Universitet, Sweden
Marie Christine Béné
Affiliation:
Université de Nantes, France
Get access

Summary

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Multiparameter Flow Cytometry in the Diagnosis of Hematologic Malignancies , pp. 215 - 230
Publisher: Cambridge University Press
Print publication year: 2018

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Fulwyler, M.J.. Electronic separation of biological cells by volume. Science; 150 (1965):910–11.CrossRefGoogle ScholarPubMed
Hulett, H.R., Bonner, W.A., Barrett, J. and Herzenberg, L.A.. Cell sorting: automated separation of mammalian cells as a function of intracellular fluorescence. Science; 166 (1969):747–49.CrossRefGoogle Scholar
Büchner, T., Dittrich, W. and Göhde, W.. Impulse cytophotometry of blood cells and bone marrow cells. Verh Dtsch Ges Inn Med; 77 (1971):416–18.Google ScholarPubMed
Basiji, D. and O'Gorman, M.R.. Imaging flow cytometry. J Immunol Methods; 423 (2015):1–2.CrossRefGoogle Scholar
Basiji, D.A.. Principles of Amnis imaging flow cytometry. Methods Mol Biol; 1389 (2016):13–21.CrossRefGoogle ScholarPubMed
Phanse, Y., Ramer-Tait, A.E., Friend, S.L., et al. Analyzing cellular internalization of nanoparticles and bacteria by multi-spectral imaging flow cytometry. J Vis Exp; 64 (2012):e3884.Google Scholar
Dominical, V., Samsel, L. and Philip McCoy, J. Jr., Masks in imaging flow cytometry. Methods; 112 (2017):9–17.CrossRefGoogle ScholarPubMed
Maguire, O., O'Loughlin, K. and Minderman, H.. Simultaneous assessment of NF-κB/p65 phosphorylation and nuclear localization using imaging flow cytometry. J Immunol Methods; 423 (2015):3–11.CrossRefGoogle ScholarPubMed
Mirabelli, P., Scalia, G., Pascariello, C., et al. ImageStream promyelocytic leukaemia protein immunolocalization: in search of promyelocytic leukaemia cells. Cytometry A; 81 (2012):232–7.Google Scholar
Niswander, L.M., McGrath, K.E., Kennedy, J.C. and Palis, J.. Improved quantitative analysis of primary bone marrow megakaryocytes utilizing imaging flow cytometry. Cytometry A; 85 (2014):302–12.CrossRefGoogle ScholarPubMed
McGrath, K.E.. Utilization of imaging flow cytometry to define intermediates of megakaryopoiesis in vivo and in vitro. J Immunol Methods; 423 (2015 Aug): 45–51.CrossRefGoogle ScholarPubMed
Maguire, O., Wallace, P.K. and Minderman, H.. Fluorescent in situ hybridization in suspension by imaging flow cytometry. Methods Mol Biol; 1389 (2016):111–26.CrossRefGoogle ScholarPubMed
Nolan, G.P. and Condello, D.. Spectral flow cytometry. Curr Protoc Cytom. (2013); Chapter 1:Unit1.27.CrossRefGoogle ScholarPubMed
Wahlstrom, J., Tasian, S.K., Hermiston, M.L., et al. Signal transduction analysis of pediatric leukaemia with a spectral flow cytometer. http://www.sonybiotechnology.com/Uploads/SP6800_Whitepapers_Signal_Transduction_Analysis_of_Pediatric_Leukemia_with_a_Spectral_Flow_Cytometer.pdf. Last accessed August 13, 2017.Google Scholar
Nolan, G.P.. Flow cytometry in the post fluorescence era. Best Pract Res Clin Haematol; 24 (2011):505–8.CrossRefGoogle ScholarPubMed
Irish, J.M. and Doxie, D.B.. High-dimensional single-cell cancer biology. Curr Top Microbiol Immunol; 377 (2014):1–21.Google ScholarPubMed
Fisher, D.A.C. and Oh, S.T.. Applications of single-cell mass cytometry (CyTOF) in hematologic malignancies. The Hematologist; 12 (2015):5 and 14.Google Scholar
Newell, E.W. and Cheng, Y.. Mass cytometry: blessed with the curse of dimensionality. Nat Immunol; 17 (2016):890–5.CrossRefGoogle ScholarPubMed
Bendall, S.C., Simonds, E.F., Qiu, P., et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science; 332 (2011):687–96.CrossRefGoogle Scholar
Becher, B., Schlitzer, A., Chen, J., et al. High-dimensional analysis of the murine myeloid cell system. Nat Immunol; 15 (2014):1181–9.CrossRefGoogle ScholarPubMed
Knapp, D.J., Hammond, C.A., Aghaeepour, N., et al. Distinct signaling programs control human hematopoietic stem cell survival and proliferation. Blood; 129 (2017):307–18.CrossRefGoogle ScholarPubMed
Newell, E.W. and Yun, L.L.. Mass cytometry analysis of human T cell phenotype and function. Methods Mol Biol; 1193 (2014):55–68.CrossRefGoogle Scholar
Newell, E.W., Sigal, N., Bendall, S.C., Nolan, G.P. and Davis, M.M.. Cytometry by time-of-flight shows combinatorial cytokine expression and virus-specific cell niches within a continuum of CD8+ T cell phenotypes. Immunity; 36 (2012):142–52.CrossRefGoogle ScholarPubMed
Fisher, D.A.C., Malkova, O., Fulbright, M.C., et al. Single cell mass cytometry reveals hyperactivated signaling networks in myeloproliferative neoplasms. Blood; 124 (2014):1884.CrossRefGoogle Scholar
Bodenmiller, B., Zunder, E.R., Finck, R., et al. Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators. Nat Biotechnol; 30 (2012):858–67.CrossRefGoogle Scholar
Rosen, D.B., Minden, M.D., Kornblau, S.M., et al. Functional characterization of FLT3 receptor signaling deregulation in acute myeloid leukaemia by single cell network profiling (SCNP). PLoS ONE; 5 (2010):e13543.CrossRefGoogle ScholarPubMed
Wade, D., Daneau, G., Aboud, S., et al. WHO multicenter evaluation of FACSCount CD4 and Pima CD4 T-Cell Count systems: instrument performance and misclassification of HIV-infected patients. J AIDS; 66 (2014):e98–e107.Google ScholarPubMed
Coetzee, L.M., Moodley, K. and Glencross, D.K.. Performance evaluation of the Becton Dickinson FACSPresto™ near-patient CD4 instrument in a laboratory and typical field clinic setting in South Africa. PLoS One; 11 (2016):e0156266.CrossRefGoogle Scholar
Gossez, M., Malcus, C., Demaret, J., et al. Evaluation of a novel automated volumetric flow cytometer for absolute CD4+ T lymphocyte quantitation. Cytometry B Clin Cytom. 25 Jan 2016. [Epub ahead of print]Google Scholar
Wlodkivowic, D. and Darzynkiewicz, Z.. Rise of the micromachines: microfluidics and the future of cytometry. Methods Cell Biol; 102 (2011):105–25.CrossRefGoogle Scholar
Holmes, D. and Gawad, S.. The application of microfluidics in biology. Methods Mol Biol; 583 (2010):55–80.CrossRefGoogle ScholarPubMed
Huh, D., Gu, W., Kamotani, Y., Grotberg, J.B. and Takayama, S.. Microfluidics for flow cytometric analysis of cells and particles. Physiol Meas; 26 (2005):R73–R98.CrossRefGoogle ScholarPubMed
Howell, P.B., Golden, J.P., Hilliard, L.R., et al. Two simple and rugged designs for creating microfluidic sheath flow. Lab Chip; 8 (2008):1097–103.CrossRefGoogle ScholarPubMed
Tung, Y.C., Zhang, M., Lin, C.T., et al. PDMS-based opto-fluidic micro flow cytometer with two-color, multi-angle fluorescence detection capability using PIN photodiodes. Sensors Actuators; B 98 (2004):356–67.Google Scholar
Piyasena, M.E. and Grves, S.W.. The intersection of flow cytometry with microfluidics and microfabrication. Lab Chip; 14 (2014):1044–59.CrossRefGoogle ScholarPubMed
Augustsson, P., Magnusson, C., Nordin, M., et al. Microfluidic, label-free enrichment of prostate cancer cells in blood based on acoustophoresis. Anal Chem; 84 (2012):7954–62.CrossRefGoogle ScholarPubMed
Shields, C.W., Reyes, D. and Lopez, G.P.. Microfluidic sell sorting: a review of the advances in the separation of cells from debulking to rare cell isolation. Lab Chip; 15 (2015):1230–49.Google Scholar
Smith, S.G., Smits, K., Joosten, S.A., et al. TBVI TB Biomarker Working Group. Intracellular cytokine staining and flow cytometry: considerations for application in clinical trials of novel tuberculosis vaccines. PLoS One; 10 (2015):e0138042.CrossRefGoogle Scholar
Whiteside, T.L.. The role of regulatory T cells in cancer immunology. ImmunoTargets and Therapy; 4 (2015):159–71.Google ScholarPubMed
De Meester, J., Calvez, R., Valitutti, S. and Dupré, L.. The Wiskott-Aldrich syndrome protein regulates CTL cytotoxicity and is required for efficient killing of B cell lymphoma targets. J Leukoc Biol; 88 (2010):1031–40.CrossRefGoogle ScholarPubMed
Sakemura, R., Terakura, S., Watanabe, K., et al. A Tet-on inducible system for controlling CD19-chimeric antigen receptor expression upon drug administration. Cancer Immunol Res; 4 (2016):658–68.CrossRefGoogle Scholar
Dekking, E., van der Velden, V.H., Böttcher, S., et al. EuroFlow Consortium (EU-FP6, LSHB-CT-2006-018708). Detection of fusion genes at the protein level in leukaemia patients via the flow cytometric immunobead assay. Best Pract Res Clin Haematol; 23 (2010):333–45.Google ScholarPubMed
Krutzik, P.O., Trejo, A., Schulz, K.R. and Nolan, G.P.. Phospho flow cytometry methods for the analysis of kinase signaling in cell lines and primary human blood samples. Methods Mol Biol; 699 (2011):179–202.CrossRefGoogle Scholar
Bardet, V., Tamburini, J., Ifrah, N., et al. Single cell analysis of phosphoinositide 3-kinase/Akt and ERK activation in acute myeloid leukaemia by flow cytometry. Haematologica; 91 (2006):757–64.Google ScholarPubMed
Irish, J.M., Anensen, N., Hovland, R., et al. Flt3 Y591 duplication and Bcl-2 overexpression are detected in acute myeloid leukaemia cells with high levels of phosphorylated wild-type p53. Blood; 109 (2007):2589–2596.CrossRefGoogle ScholarPubMed
Ilatikhameneh, H., Ameen, T., Novakovic, B., et al. Saving Moore's law down to 1 nm channels with anisotropic effective mass. Sci Rep; 6 (2016):31501.CrossRefGoogle ScholarPubMed
Wu, S., Jin, L., Vence, L. and Radvanyi, L.G.. Development and application of ‘phosphoflow’ as a tool for immunomonitoring. Expert Rev Vaccines; 9 (2010):631–43.CrossRefGoogle ScholarPubMed
Bodenmiller, B., Zunder, E.R., Finck, R., et al. Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators. Nat Biotechnol; 30 (2012):858–67.CrossRefGoogle Scholar
Irish, J.M., Czerwinski, D.K., Nolan, G.P. and Levy, R.. Altered B-cell receptor signaling kinetics distinguish human follicular lymphoma B cells from tumour-infiltrating nonmalignant B cells. Blood; 108 (2006):3135–42.CrossRefGoogle Scholar
Arbab, M., Mahony, S., Cho, H., et al. A multi-parametric flow cytometric assay to analyse DNA-protein interactions. Nucleic Acids Res; 41 (2013):e38.CrossRefGoogle ScholarPubMed
Székvölgyi, L., Bálint, B.L., Imre, L., et al. Chip-on-beads: flow-cytometric evaluation of chromatin immunoprecipitation. Cytometry A; 69 (2006):1086–91.Google ScholarPubMed
Faucher, J.L., Lacronique-Gazaille, C., Frébet, E., et al. ‘6 markers/5 colours’ extended white blood cell differential by flow cytometry. Cytometry A; 71 (2007):934–44.Google ScholarPubMed
Roussel, M., Davis, B.H., Fest, T. and Wood, B.L.. International Council for Standardization in Hematology (ICSH). Toward a reference method for leukocyte differential counts in blood: comparison of three flow cytometric candidate methods. Cytometry A; 81 (2012):973–82.Google Scholar
van de Geijn, G.J., van Rees, V., van Pul-Bom, N., et al. Leukoflow: multiparameter extended white blood cell differentiation for routine analysis by flow cytometry. Cytometry A; 79 (2011):694–706.CrossRefGoogle ScholarPubMed
Kim, J.E., Kim, B.R., Woo, K.S. and Han, J.Y.. Evaluation of the leukocyte differential on a new automated flow cytometry hematology analyzer. Int J Lab Hematol; 34 (2012):547–50.CrossRefGoogle ScholarPubMed
Allou, K., Vial, J.P., Béné, M.C. and Lacombe, F.. The routine leukocyte differential flow cytometry HematoFlow™ method: a new flagging system for automatic validation. Cytometry B Clin Cytom; 88 (2015):375–84.CrossRefGoogle Scholar
Kahng, J., Kim, Y., Kim, M., et al. Flow cytometric white blood cell differential using CytoDiff is excellent for counting blasts. Ann Lab Med; 35 (2015):28–34.CrossRefGoogle ScholarPubMed
Pedreira, C.E., Costa, E.S., Barrena, S., et al. EuroFlow Consortium. Generation of flow cytometry data files with a potentially infinite number of dimensions. Cytometry A; 73 (2008):834–846.CrossRefGoogle Scholar
Lacombe, F., Bernal, E., Bloxham, D., et al. Harmonemia: a universal strategy for flowcytometry immunophenotyping-A European LeukemiaNet WP10 study. Leukaemia; 30 (2016):1769–72.Google Scholar
Jolliffe, I.T.. Principal Component Analysis (Springer, New York, 2002).Google Scholar
Ringnér, M.. What is principal component analysis? Nat Biotechnol; 26 (2008):303–4.CrossRefGoogle ScholarPubMed
Qiu, P., Simonds, E.F., Bendall, S.C., et al. Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE. Nat. Biotechnol; 29 (2011):886.CrossRefGoogle ScholarPubMed
Qiu, P.. Inferring phenotypic properties from single-cell characteristics. PLoS One; 7 (2012):e37038.CrossRefGoogle ScholarPubMed
Mair, F., Hartmann, F.J., Mrdjen, D., et al. The end of gating? An introduction to automated analysis of high dimensional cytometry data. Eur J Immunol; 46 (2016):34–43.CrossRefGoogle ScholarPubMed
Lin, L., Frelinger, J., Jiang, W., et al. Identification and visualization of multidimensional antigen-specific T-cell populations in polychromatic cytometry data. Cytometry A; 87 (2015):675–82.CrossRefGoogle Scholar
Van Gassen, S., Callebaut, B., Van Helden, M.J., et al. FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data. Cytometry A; 87 (2015):636–45.CrossRefGoogle ScholarPubMed
Levine, J.H., Simonds, E.F., Bendall, S.C., et al. Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis. Cell; 162 (2015):184–97.CrossRefGoogle Scholar
Cheng, Y., Wong, M.T., van der Maaten, L. and Newell, E.W.. Categorical analysis of human T cell heterogeneity with one-dimensional soli-expression by nonlinear stochastic embedding. J Immunol; 196 (2016):924–32.CrossRefGoogle Scholar
Bendall, S.C., Davis, K.L., El-Amir, A.D., et al. Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development. Cell; 157 (2014):714–25.CrossRefGoogle ScholarPubMed
Bagwell, C.B., Hunsberger, B.C., Herbert, D.J., et al. Probability state modeling theory. Cytometry A; 87 (2015):646–60.CrossRefGoogle ScholarPubMed
Bruggner, R.V., Bodenmiller, B., Dill, D.L., et al. Automated identification of stratifying signatures in cellular subpopulations. Proc Natl Acad Sci USA; 111 (2014):E2770–7.CrossRefGoogle ScholarPubMed
DiGiuseppe, J.A., Tadmor, M.D., Pe'er, D.. Detection of minimal residual disease in B lymphoblastic leukaemia using viSNE. Cytometry B Clin Cytom; 88 (2015):294–304.CrossRefGoogle Scholar
Maude, S.L., Dolai, S., Delgado-Martin, C., et al. Efficacy of JAK/STAT pathway inhibition in murine xenograft models of early T-cell precursor (ETP) acute lymphoblastic leukaemia. Blood; 125 (2015):1759–67.CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×