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Abstract A047: Tumor specific γδ T cells expand and respond to PD-1 blockade

2023· article· en· W4389227797 on OpenAlexaffabout
Scott Lien, Dalam Ly, S.Y. Cindy Yang, Ben X. Wang, Michael St. Paul, Ramy Gadalla, Babak Noamani, Sarah Boross-Harmer, Trevor J. Pugh, Anna Spreafico, Naoto Hirano, Albiruni R. Abdul Razak, Pamela S. Ohashi

Bibliographic record

VenueCancer Immunology Research · 2023
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsPembrolizumabTIGITT cellT-cell receptorBlockadeImmunologyCancer immunotherapyTumor-infiltrating lymphocytesImmunotherapyBiologyCancer researchMedicineImmune systemReceptorInternal medicine

Abstract

fetched live from OpenAlex

Abstract With the breakthrough of checkpoint blockade, immunotherapies targeting PD-1/PD-L1 have had remarkable success in the clinic and are now widely used to treat a variety of malignancies. While the majority of research on T cell exhaustion and PD-1 blockade has been focused on conventional αβ T cells, the contribution of innate-like T cells such as γδ T cells to PD-1 blockade is not clear. γδ T cells are generally not restricted to conventional MHC-peptide molecules and can recognize a diverse range of ligands including phosphoantigens presented on butyrophilins and MHC class I-like family members MR1, and CD1 isoforms. Using flow cytometry, we evaluated the γδ T cell responses in tumor biopsies and peripheral blood from six MCC patients treated with pembrolizumab. Furthermore, bulk and single cell γδ TCR sequencing was used to measure diversity and clonal expansion in the blood upon PD-1 blockade. TCRs were cloned and expressed in Jurkat cells to screen for reactivity against tumor cells lines. Finally, we used CRISPR-Cas9 to knockout known γδ T cell ligands to identify potential tumor antigen recognized by γδ T cells. We identified a MCC patient who experienced a complete response to pembrolizumab treatment and had a ten-fold expansion of γδ T cells in their tumor biopsies. Tumor-infiltrating γδ T cells expressed high levels of inhibitory receptors PD-1 and TIGIT. Furthermore, γδ T cells characterized in peripheral blood were predominantly Vδ1 cells and had increased Ki-67 expression upon pembrolizumab treatment. From TCR sequencing of peripheral blood, we observed the emergence of a dominant γδ T cell clonotype that was also found in the tumor. Upon TCR gene transfer into Jurkat 76 cells, we identified a γδ TCR that was able to recognize multiple Merkel cancer cell lines. CRISPR knockout of B2M in tumor cells still retained γδ TCR reactivity, suggesting that γδ TCR recognition is independent of B2M expression. Together, these results show innate-like T cells such as γδ T cells also have the capacity to respond to checkpoint blockade. As mutations in antigen presentation can be a resistance mechanism to PD-1 blockade, our study provides the rationale to utilize γδ T cells for treating cancer variants that have escaped the immune system and warrants further investigation of the interplay between γδ T cells and checkpoint blockade. Citation Format: Scott C. Lien, Dalam Ly, S.Y. Cindy Yang, Ben X. Wang, Michael St. Paul, Ramy Gadalla, Babak Noamani, Sarah Boross-Harmer, Trevor J. Pugh, Anna Spreafico, Naoto Hirano, Albiruni R.A. Razak, Pamela S. Ohashi. Tumor specific γδ T cells expand and respond to PD-1 blockade [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr A047.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.124
GPT teacher head0.435
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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