Evidence map›Paper›PMID 17721783›Full record

ArticleCancer immunology, immunotherapy : CII2008

The CIMT-monitoring panel: a two-step approach to harmonize the enumeration of antigen-specific CD8+ T lymphocytes by structural and functional assays.

C M Britten, C Gouttefangeas, M J P Welters, G Pawelec, S Koch, C Ottensmeier, A Mander, S Walter, A Paschen, J Müller-Berghaus and 14 more

Abstract readCommentComparative StudyMulticenter Study
In one paragraph

Article in Cancer immunology, immunotherapy : CII, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

72 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Antigen-specific active immunotherapy for ovarian cancer.The Cochrane database of systematic reviews · 2018
    Pooled it
  2. Guideline
  3. Targeting Carcinoembryonic Antigen with DNA Vaccination: On-Target Adverse Events Link with Immunologic and Clinical Outcomes.Clinical cancer research : an official journal of the American Association for Cancer Research · 2016
    Trial
  4. Trial
  5. Trial
  6. Trial
  7. Review
  8. Review
  9. Article
  10. Article
  11. Optimization in Detection of Antigen-Specific T Cells Through Differentially Labeled MHC Multimers.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2020
    Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

12 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

24 authors.

C M BrittenDepartment of Immunohaematology and Blood Transfusion, Leiden University Medical Center, Leiden, The Netherlands. cebritten@web.de
C Gouttefangeas
M J P Welters
G Pawelec
S Koch
C Ottensmeier
A Mander
S Walter
A Paschen
J Müller-Berghaus
I Haas
A Mackensen
T Køllgaard
P thor Straten
M Schmitt
K Giannopoulos
R Maier
H Veelken
C Bertinetti
A Konur
C Huber
S Stevanović
T Wölfel
S H van der Burg

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The interpretation of the results obtained from immunomonitoring of clinical trials is a difficult task due to the variety of methods and protocols available to detect vaccine-specific T-cell responses. This heterogeneity as well as the lack of standards has led to significant scepticism towards published results. In February 2005, a working group was therefore founded under the aegis of the Association for Immunotherapy of Cancer ("CIMT") in order to compare techniques and protocols applied for the enumeration of antigen-specific T-cell responses. Here we present the results from two consecutive phases of an international inter-laboratory testing project referred to as the "CIMT monitoring panel". A total of 13 centers from six European countries participated in the study in which pre-tested PBMC samples, synthetic peptides and PE-conjugated HLA-tetramers were prepared centrally and distributed to participants. All were asked to determine the number of antigen-specific T-cells in each sample using tetramer staining and one functional assay. The results of the first testing round revealed that the total number of cells analyzed was the most important determinant for the sensitive detection of antigen-specific CD8(+) T-cells by tetramer staining. Analysis by ELISPOT was influenced by a combination of cell number and a resting phase after thawing of peripheral blood mononuclear cells. Therefore, the experiments were repeated in a second phase but now the participants were asked to change their protocols according to the new guidelines distilled from the results of the first phase. The recommendations improved the number of antigen-specific T-cell responses that were detected and decreased the variability between the laboratories. We conclude that a two-step approach in inter-laboratory testing allows the identification of distinct variables that influence the sensitivity of different T-cell assays and to formally show that a defined correction to the protocols successfully increases the sensitivity and reduces the inter-center variability. Such "two-step" inter-laboratory projects could define rational bases for accepted international guidelines and thereby lead to the harmonization of the techniques used for immune monitoring.

Indexed as

CD8-Positive T-LymphocytesEnzyme-Linked Immunosorbent AssayEpitopesEuropeFlow CytometryHLA-A AntigensHumansImmunotherapyLeukocytes, MononuclearMonitoring, ImmunologicPeptidesProfessional Staff CommitteesReference ValuesReproducibility of ResultsSensitivity and SpecificityStaining and LabelingEpitopesHLA-A AntigensPeptides

Identifiers

PMID17721783
PMCPMC2150627

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.