ReviewFrontiers in immunology2023
The capability of heterogeneous γδ T cells in cancer treatment.
Review in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Regulatory T cells in the breast cancer tumor microenvironment: new mechanisms, potential therapeutic strategies and future perspectives.American journal of cancer research · 2026Review
- Phenoscaping Reveals Multimodal γδ T-cell Cytotoxicity as a Strategy to Overcome Cancer Cell-Mediated Immunomodulation.Cancer research · 2025Article
- Uncovering the mysteries of human gamma delta T cells: from origins to novel therapeutics.Frontiers in immunology · 2025Review
- Integrating of Radiomics and Single-cell Transcriptomics Uncovers the Crucial Role of γδ T Cells in Lung Adenocarcinoma.Journal of Cancer · 2025Article
- CAR-iNKT cells: redefining the frontiers of cellular immunotherapy.Frontiers in immunology · 2025Review
- Single-cell ligand-receptor profiling reveals an immunotherapy-responsive subtype and prognostic signature in triple-negative breast cancer.Frontiers in immunology · 2025Article
- Crotonylation-Related Prognostic Model of Esophageal Squamous Cell Carcinoma Based on Transcriptome Analysis and Single-Cell Sequencing Analysis.International journal of general medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
γδ T cells, a specialized subset of T lymphocytes, have garnered significant attention within the realm of cancer immunotherapy. Operating at the nexus between adaptive and innate immunological paradigms, these cells showcase a profound tumor discernment repertoire, hinting at novel immunotherapeutic strategies. Significantly, these cells possess the capability to directly identify and eliminate tumor cells without reliance on HLA-antigen presentation. Furthermore, γδ T cells have the faculty to present tumor antigens to αβ T cells, amplifying their anti-tumoral efficacy.Within the diverse and heterogeneous subpopulations of γδ T cells, distinct immune functionalities emerge, manifesting either anti-tumor or pro-tumor roles within the tumor microenvironment. Grasping and strategically harnessing these heterogeneous γδ T cell cohorts is pivotal to their integration in tumor-specific immunotherapeutic modalities. The aim of this review is to describe the heterogeneity of the γδ T cell lineage and the functional plasticity it generates in the treatment of malignant tumors. This review endeavors to elucidate the intricate heterogeneity inherent to the γδ T cell lineage, the consequential functional dynamics in combating malignancies, the latest advancements from clinical trials, and the evolving landscape of γδ T cell-based oncological interventions, while addressing the challenges impeding the field.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.