ArticleJournal for immunotherapy of cancer2025
Autologous profiling reveals inter-patient heterogeneity in Vδ2
Article in Journal for immunotherapy of cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The trial behind it
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Who cites it
5 citing papers in PubMed.
- γδ T cells and cancer.The Journal of clinical investigation · 2026Review
- γδ T cells at the interface of innate and adaptive immunity in cancer.Journal for immunotherapy of cancer · 2026Review
- Commentary on "Comparative efficacy and safety of PSCA CAR-engineered Vδ1 γδ T cells for immunotherapy of pancreatic cancer".Journal for immunotherapy of cancer · 2026Article
- Unconventional guardians of the brain: MAIT cells as emerging players in glioblastoma immunity.Frontiers in immunology · 2026Review
- Pre-existing activation states shape functional heterogeneity of human Vγ9Vδ2 T cells.Frontiers in immunology · 2026Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe effectiveness of immunotherapies against glioblastoma (GB) remains limited. A major obstacle in advancing new strategies is the reliance on non-autologous systems, which do not accurately mimic the true extent of inter-patient heterogeneity in both immune responses and tumor susceptibility. This often leads to misleading conclusions about therapeutic efficacy and targetability.
methodsIn this study, we addressed this critical gap by employing a fully autologous model. We phenotypically characterized primary αβ and γδT cells from the peripheral blood and tumors of 40 brain tumor patients, including 36 with confirmed GB, and expanded and functionally assessed the autologous anti-GB reactivity in a subset of patients.
resultsNotably, only Vδ2
conclusionsThis study demonstrates that inter-patient heterogeneity in Vδ2
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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.