Evidence map›Paper›PMID 42823731›Full record

ArticleJournal of translational medicine2026

Lineage-specific immune checkpoint dynamics define a context-dependent regulatory framework with translational relevance in human γδ T cells.

Anna Maria Corsale, Marta Di Simone, Juan Pablo Cerapio, Elena Lo Presti, Gabriele Pizzolato, Claudia Avellone, Costanza Dieli, Salvatore Marchiafava, Laura Di Paola, Francesco Dieli and 1 more

Abstract read
In one paragraph

Article in Journal of translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Anna Maria Corsale *Central Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), University of Palermo, Palermo, Italy. annamaria.corsale@unipa.it.ORCID http://orcid.org/0000-0002-2541-4619
Marta Di Simone *Central Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), University of Palermo, Palermo, Italy.ORCID http://orcid.org/0000-0003-1973-0540
Juan Pablo Cerapio *Centre de Recherches en Cancérologie de Toulouse, Toulouse, France.ORCID http://orcid.org/0000-0002-3032-3180
Elena Lo PrestiNational Research Council of Italy (CNR), Institute for Biomedical Research and Innovation (IRIB), Palermo, Italy.ORCID http://orcid.org/0000-0001-5401-4545
Gabriele PizzolatoCycuria Therapeutics GmbH, Graz, Austria.
Claudia AvelloneCentral Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), University of Palermo, Palermo, Italy.ORCID http://orcid.org/0009-0003-0099-2011
Costanza DieliCentral Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), University of Palermo, Palermo, Italy.ORCID http://orcid.org/0009-0003-1902-7510
Salvatore MarchiafavaCentral Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), University of Palermo, Palermo, Italy.
Laura Di PaolaCentral Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), University of Palermo, Palermo, Italy.ORCID http://orcid.org/0009-0003-6779-225X
Francesco DieliCentral Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), University of Palermo, Palermo, Italy.ORCID http://orcid.org/0000-0002-6685-352X
Serena MeravigliaCentral Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), University of Palermo, Palermo, Italy.ORCID http://orcid.org/0000-0002-0383-5818

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImmune checkpoint receptors (ICRs) are widely used as markers of T-cell exhaustion, yet their interpretation remains context-dependent and is poorly described in γδ T cells. Here, we investigated the dynamics, functional impact, and differentiation-associated distribution of ICRs across human γδ and αβ T-cell subsets.

methodsPeripheral blood mononuclear cells from healthy donors were stimulated in vitro to assess ICR dynamics in γδ and αβ T-cell subsets by flow cytometry. Functional effects of PD-1 and TIM-3 blockade were evaluated through proliferation, cytokine production, and degranulation assays. In parallel, previously published single-cell RNA-sequencing datasets of tumor-infiltrating γδ and CD8 T cells were subjected to secondary bioinformatic analysis to characterize differentiation-associated ICR expression patterns and their modulation following immune checkpoint blockade (ICB) therapy.

resultsICR expression was regulated in a receptor-, lineage- and context-dependent manner. Polyclonal stimulation induced broad ICR upregulation, whereas phosphoantigen-driven Vδ2 T cell expansion resulted in a selective profile with sustained TIM-3 expression and transient modulation of PD-1 and TIGIT. Checkpoint distribution was structured across differentiation states, with TIGIT enriched in antigen-experienced subsets, LAG-3 and TIM-3 in naive compartments, and PD-1 broadly expressed. PD-1 blockade was associated with donor-dependent trends toward increased proliferation and cytokine production, particularly under IL-15 stimulation, whereas TIM-3 inhibition showed variable effects and combined blockade did not produce a consistent additive response. Single-cell transcriptomic analyses revealed that tumor-infiltrating γδ T cells displayed heterogeneous ICR expression across differentiation states, whereas CD8 T cells showed a more progressive pattern of checkpoint expression. Because classical exhaustion-associated transcriptional and epigenetic programs were not evaluated, these patterns neither establish nor exclude the presence of exhausted γδ T-cell subsets. ICB therapy was associated with persistence or upregulation of alternative checkpoints.

conclusionsThese findings indicate that ICR expression in γδ T cells is dynamically shaped by activation, differentiation, and environmental context. However, ICR expression alone is insufficient to define or exclude a state of T-cell exhaustion.

Indexed as

Cell LineageImmune Checkpoint ProteinsReceptors, Antigen, T-Cell, gamma-deltaCell DifferentiationCell ProliferationHepatitis A Virus Cellular Receptor 2HumansImmune Checkpoint InhibitorsProgrammed Cell Death 1 ReceptorT-Cell ExhaustionT-Lymphocyte SubsetsHAVCR2 protein, humanHepatitis A Virus Cellular Receptor 2Immune Checkpoint InhibitorsImmune Checkpoint ProteinsProgrammed Cell Death 1 ReceptorReceptors, Antigen, T-Cell, gamma-deltaGamma delta T cellsImmune checkpoint blockadeImmune checkpoint receptors

Identifiers

PMID42823731
PMCPMC13629053

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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.