ReviewClinical cancer research : an official journal of the American Association for Cancer Research2024
Arming Vδ2 T Cells with Chimeric Antigen Receptors to Combat Cancer.
Review in Clinical cancer research : an official journal of the American Association for Cancer Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled 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.
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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prostate cancer and CAR-T therapy: a systematic review.BMC cancer · 2026Pooled it
- Harnessing Self-Assembling Peptides on γδ T Cells to Enhance Anti-Tumor Immunity.Polymer science & technology (Washington, D.C.) · 2026Article
- Harnessing the potential of γδ T cells through engineering and combination treatment for cancer therapies.Nature communications · 2026Review
- Engineering CAR-Vδ2 T cells to boost persistence and anti-tumor function.bioRxiv : the preprint server for biology · 2026Article
- Beyond CAR-T and oncology: broadening chimeric antigen receptor technologies across cell types and diseases.Precision clinical medicine · 2026Review
- Generation and preclinical characterization of a novel bispecific CD19-TCRgammadelta antibody for the treatment of B cell acute lymphoblastic leukemia.Frontiers in immunology · 2026Article
- CAR-γδ T cells: a new paradigm of programmable innate immune sentinels and their systemic applications in cancer and beyond.Frontiers in immunology · 2025Review
- From innate-like to innate: the next wave of off-the-shelf CAR immunotherapies.Frontiers in immunology · 2025Review
- Amplifying cancer immunity: AMPK activators and gammadelta T cells unveiled.EXCLI journal · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Immunotherapy has emerged as a promising approach in the field of cancer treatment, with chimeric antigen receptor (CAR) T-cell therapy demonstrating remarkable success. However, challenges such as tumor antigen heterogeneity, immune evasion, and the limited persistence of CAR-T cells have prompted the exploration of alternative cell types for CAR-based strategies. Gamma delta T cells, a unique subset of lymphocytes with inherent tumor recognition capabilities and versatile immune functions, have garnered increasing attention in recent years. In this review, we present how arming Vδ2-T cells might be the basis for next-generation immunotherapies against solid tumors. Following a comprehensive overview of γδ T-cell biology and innovative CAR engineering strategies, we discuss the clinical potential of Vδ2 CAR-T cells in overcoming the current limitations of immunotherapy in solid tumors. Although the applications of Vδ2 CAR-T cells in cancer research are relatively in their infancy and many challenges are yet to be identified, Vδ2 CAR-T cells represent a promising breakthrough in cancer immunotherapy.
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.