Evidence map›Paper›PMID 42039205›Full record

ReviewFrontiers in immunology2026

Targeting regulatory T cells in glioblastoma: from mechanistic insights to novel immunotherapeutic strategies.

Jingwen Li, Yang Liu, Peng Peng, Jinyang Hu

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Jingwen LiDepartment of Oncology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China.
Yang LiuDepartment of Neurosurgery, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China.
Peng PengDepartment of Neurosurgery, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China.
Jinyang HuWenzhou Medical University, Wenzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioblastoma (GBM), the most common and aggressive primary brain tumor in adults, remains a formidable therapeutic challenge. Within the immunosuppressive tumor microenvironment, regulatory T cells (Tregs) have attracted increasing attention for their pivotal role in facilitating tumor immune evasion and sustaining immunosuppression. Through diverse mechanisms, Tregs potently inhibit anti-tumor immunity, thereby driving tumor progression and contributing to therapeutic resistance, which collectively correlates with poor clinical outcomes. This review systematically outlines the biological features and regulatory networks of Tregs in GBM, with particular emphasis on emerging strategies designed to target these cells. We discuss approaches such as Treg depletion, interference with their recruitment, functional reprogramming, and combination immunotherapies. Furthermore, we critically assess the translational progress and clinical limitations of these approaches, including challenges related to target specificity, immune adaptation, and treatment-related toxicities. By synthesizing mechanistic insights with therapeutic prospects, this review aims to inform future directions in precision immunotherapy and inspire multidisciplinary efforts toward effective Treg-targeting regimens for GBM.

Indexed as

Brain NeoplasmsGlioblastomaImmunotherapyT-Lymphocytes, RegulatoryAnimalsHumansTumor EscapeTumor Microenvironmentclinical translationglioblastomaimmune evasionimmune microenvironmentimmunotherapyregulatory T cellstargeted therapy

Identifiers

PMID42039205
PMCPMC13106435

What OpenQuestion holds

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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.