Evidence map›Paper›PMID 22359647›Full record

ArticlePloS one2012

Trafficking of high avidity HER-2/neu-specific T cells into HER-2/neu-expressing tumors after depletion of effector/memory-like regulatory T cells.

Vivian L Weiss, Timothy H Lee, Hong Song, Theodore S Kouo, Chelsea M Black, George Sgouros, Elizabeth M Jaffee, Todd D Armstrong

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
3.4field-weighted citation impact, top 7% of its field
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

28 citing papers in PubMed, 44 citations in OpenAlex.

  1. Trial
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  5. Review
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  7. Review
  8. Immune-Checkpoint Blockade Opposes CD8Cancer immunology research · 2019
    Article
  9. Article
  10. Article
  11. Article
  12. Article
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  15. Article
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  17. Review
  18. Review
  19. Enhancement of T cell recruitment and infiltration into tumours.Clinical and experimental immunology · 2014
    Review
  20. T cell avidity and tumor immunity: problems and solutions.Cancer microenvironment : official journal of the International Cancer Microenvironment Society · 2014
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Vivian L WeissThe Sidney Kimmel Cancer Center at Johns Hopkins, John Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
Timothy H Lee
Hong Song
Theodore S Kouo
Chelsea M Black
George Sgouros
Elizabeth M Jaffee
Todd D Armstrong
Johns Hopkins University · US

Funding

VACCINES--A NEW PARADIGM FOR BREAST CANCERP50CA088843 · NCI · JOHNS HOPKINS UNIVERSITY · PI DAVIDSON, NANCY ELLEN · 2000 to 2010
$27.8M
CELLULAR &MOLECULAR MECH OF INFLAMMATORY REACTIONST32AI007247 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Joel L Pomerantz · 1985 to 2026
$10.2M
Tolerance mechanisms regulating the complete HER-2/neu CD+8 T cell repertoireR01CA122081 · NCI · JOHNS HOPKINS UNIVERSITY · PI JAFFEE, ELIZABETH M. · 2008 to 2012
$1.7M
NCI NIH HHS P50 CA088843NCI NIH HHS P50CA088843NCI NIH HHS R01 CA122081NCI NIH HHS R01CA122081NIAID NIH HHS T32 AI007247
6 · The paper itself

Abstract

backgroundCancer vaccines are designed to activate and enhance cancer-antigen-targeted T cells that are suppressed through multiple mechanisms of immune tolerance in cancer-bearing hosts. T regulatory cell (Treg) suppression of tumor-specific T cells is one barrier to effective immunization. A second mechanism is the deletion of high avidity tumor-specific T cells, which leaves a less effective low avidity tumor specific T cell repertoire available for activation by vaccines. Treg depleting agents including low dose cyclophosphamide (Cy) and antibodies that deplete CD25-expressing Tregs have been used with limited success to enhance the potency of tumor-specific vaccines. In addition, few studies have evaluated mechanisms that activate low avidity cancer antigen-specific T cells. Therefore, we developed high and low avidity HER-2/neu-specific TCR transgenic mouse colonies specific for the same HER-2/neu epitope to define the tolerance mechanisms that specifically affect high versus low avidity tumor-specific T cells. METHODOLOGY/PRINCIPAL

findingsHigh and low avidity CD8(+) T cell receptor (TCR) transgenic mice specific for the breast cancer antigen HER-2/neu (neu) were developed to provide a purified source of naïve, tumor-specific T cells that can be used to study tolerance mechanisms. Adoptive transfer studies into tolerant FVB/N-derived HER-2/neu transgenic (neu-N) mice demonstrated that high avidity, but not low avidity, neu-specific T cells are inhibited by Tregs as the dominant tolerizing mechanism. High avidity T cells persisted, produced IFNγ, trafficked into tumors, and lysed tumors after adoptive transfer into mice treated with a neu-specific vaccine and low dose Cy to deplete Tregs. Analysis of Treg subsets revealed a Cy-sensitive CD4(+)Foxp3(+)CD25(low) tumor-seeking migratory phenotype, characteristic of effector/memory Tregs, and capable of high avidity T cell suppression. CONCLUSION/SIGNIFICANCE: Depletion of CD25(low) Tregs allows activation of tumor-clearing high avidity T cells. Thus, the development of agents that specifically deplete Treg subsets should translate into more effective immunotherapies while avoiding autoimmunity.

Indexed as

T-Lymphocytes, RegulatoryAnimalsAntigens, NeoplasmCancer VaccinesCell MovementErb-b2 Receptor Tyrosine KinasesImmunologic MemoryMammary Neoplasms, ExperimentalMiceMice, TransgenicT-Cell Antigen Receptor SpecificityT-LymphocytesAntigens, NeoplasmCancer VaccinesErbb2 protein, mouseErb-b2 Receptor Tyrosine Kinases

Identifiers

PMID22359647
PMCPMC3281086
OpenAlexW1993659680

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.