Cancer Immunology, Immunotherapy

, Volume 64, Issue 5, pp 585–598 | Cite as

Data analysis as a source of variability of the HLA-peptide multimer assay: from manual gating to automated recognition of cell clusters

  • Cécile GouttefangeasEmail author
  • Cliburn Chan
  • Sebastian Attig
  • Tania T. Køllgaard
  • Hans-Georg Rammensee
  • Stefan Stevanović
  • Dorothee Wernet
  • Per thor Straten
  • Marij J. P. Welters
  • Christian Ottensmeier
  • Sjoerd H. van der Burg
  • Cedrik M. Britten
Original Article


Multiparameter flow cytometry is an indispensable method for assessing antigen-specific T cells in basic research and cancer immunotherapy. Proficiency panels have shown that cell sample processing, test protocols and data analysis may all contribute to the variability of the results obtained by laboratories performing ex vivo T cell immune monitoring. In particular, analysis currently relies on a manual, step-by-step strategy employing serial gating decisions based on visual inspection of one- or two-dimensional plots. It is therefore operator dependent and subjective. In the context of continuing efforts to support inter-laboratory T cell assay harmonization, the CIMT Immunoguiding Program organized its third proficiency panel dedicated to the detection of antigen-specific CD8+ T cells by HLA-peptide multimer staining. We first assessed the contribution of manual data analysis to the variability of reported T cell frequencies within a group of laboratories staining and analyzing the same cell samples with their own reagents and protocols. The results show that data analysis is a source of variation in the multimer assay outcome. To evaluate whether an automated analysis approach can reduce variability of proficiency panel data, we used a hierarchical statistical mixture model to identify cell clusters. Challenges for automated analysis were the need to process non-standardized data sets from multiple centers, and the fact that the antigen-specific cell frequencies were very low in most samples. We show that this automated method can circumvent difficulties inherent to manual gating strategies and is broadly applicable for experiments performed with heterogeneous protocols and reagents.


HLA-peptide multimer Proficiency panel Data analysis Flow cytometry gating Automated analysis 



Cancer Immunotherapy Consortium


CIMT Immunoguiding Program


Association for Cancer Immunotherapy


Human cytomegalovirus


Coefficient of variation


Flow cytometry

FCS file

Flow Cytometry Standard format for data files


Fluorescence minus one


Human leukocyte antigen


Intracellular cytokine staining


Interferon gamma


Monoclonal antibody


Peripheral blood mononuclear cells


Room temperature


T cell receptor



CIP and C. Chan are supported by a grant of the Wallace Coulter Foundation (Miami, Florida, USA). C. Gouttefangeas receives a grant from the Deutsche Forschungsgemeinschaft SFB 685/Z5. M. J. P. Welters is supported by a grant from the Dutch Cancer Society (UL 2009-4400). C. Chan is supported by grants to the Duke University Center for AIDS Research and EQAPOL program funded by NIH grant 5P30 AI064518 and NIH contract HHSN272201000045C respectively. We thank the Association for Cancer Immunotherapy (CIMT) for its patronage and financial support, all panel participants listed below, and laboratory ID01 for providing FCS files for the FlowRepository database. Panel participants E. Inderberg, K. Lislerud, AM. Rasmussen, G. Gaudernack, Institute of Cancer Research, Radium Hospital, Oslo, Norway; K. Giannopoulos, Clinical Immunology Department, Medical University of Lublin, Lublin, Poland; S. Attig*, C. Gouttefangeas, Department of Immunology, University of Tübingen, Tübingen, Germany. * Now TRON gGmbH, Johannes Gutenberg University, Mainz, Germany; M. Schmitt-Händle, E. Kämpgen, Department of Dermatology, University Hospital Erlangen, Erlangen, Germany; A. Konur, Third Medical Department, Johannes-Gutenberg University, Mainz, Germany; A. Letsch, Department for Haematology and Oncology, Charite Hospital, Berlin, Germany; A. Mackensen, M. Aigner, Department for Haematology and Oncology, Erlangen, Germany; R. Maier, Institute of Immunobiology, Cantonal Hospital St.Gallen, Switzerland; L. Low, C. Ottensmeier, Cancer Science Division, Southampton University Hospitals, Southampton, UK; E. Derhovanessian, G. Pawelec, Center for Medical Research, University of Tübingen, Tübingen, Germany; H. Pohla, Laboratory for Tumor Immunology, Ludwig-Maximilians University, Munich, Germany; D. Riemann, B. Seliger, Institute for Medical Immunology, Martin Luther University, Halle, Germany; T. Køllgaard*, P. thor Straten, Center for Cancer Immune Therapy, Herlev, Denmark. * Now Institute for Inflammation Research (IIR), Copenhagen University Hospital, Denmark; M. Welters, SH. van der Burg, Department of Clinical Oncology, Leiden University Medical Center, Leiden, The Netherlands; CM. Britten*, Department of Immunohematology and Blood Transfusion, Leiden University Medical Center, Leiden, The Netherlands. * Now TRON gGmbH, Johannes-Gutenberg University, Mainz, Germany; S. Koch*, R. van Lier, Department for Experimental Immunology, University of Amsterdam, Amsterdam, The Netherlands. * Now Curevac GmbH, Tübingen, Germany; M. Navarette*, AK. Kaskel, H. Veelken+, Department of Haematology and Oncology, Freiburg University Medical Center, Freiburg, Germany. * Now Magallanes University Medical School, Punta Arenas, Chile. + Now Department of Haematology, Leiden University Medical Center, Leiden, The Netherlands; MN; R. Mendrzyk, S. Walter, Immatics biotechnologies GmbH, Tübingen, Germany.

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

262_2014_1649_MOESM1_ESM.pdf (2.5 mb)
Supplementary material 1 (PDF 2587 kb)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Cécile Gouttefangeas
    • 1
    Email author
  • Cliburn Chan
    • 2
  • Sebastian Attig
    • 1
    • 8
  • Tania T. Køllgaard
    • 3
    • 9
  • Hans-Georg Rammensee
    • 1
  • Stefan Stevanović
    • 1
  • Dorothee Wernet
    • 4
  • Per thor Straten
    • 3
  • Marij J. P. Welters
    • 5
  • Christian Ottensmeier
    • 6
  • Sjoerd H. van der Burg
    • 5
  • Cedrik M. Britten
    • 7
  1. 1.Department of Immunology, Institute for Cell BiologyEberhard Karls UniversityTübingenGermany
  2. 2.Department of Biostatistics and BioinformaticsDuke University Medical CenterDurhamUSA
  3. 3.Center for Cancer Immune TherapyCopenhagen University HospitalHerlevDenmark
  4. 4.Center for Clinical Transfusion MedicineUniversity HospitalTübingenGermany
  5. 5.Department of Clinical OncologyLeiden University Medical CenterLeidenThe Netherlands
  6. 6.Cancer Sciences DivisionSouthampton University HospitalsSouthamptonUK
  7. 7.Translational Oncology, University Medical CenterJohannes Gutenberg University (TRON gGmbH)MainzGermany
  8. 8.TRON gGmbH, University Medical CenterJohannes Gutenberg University MainzMainzGermany
  9. 9.Institute for Inflammation Research (IIR)Copenhagen University HospitalCopenhagenDenmark

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