Differential Activation of V γ4V δ1 and V γ9V δ2 Cord Blood Derived Gamma Delta T Cells upon Exposure to EBV-Lcl and K562 Cells
Bibliographic record
Abstract
Abstract Gamma-delta (γδ) T cells have emerged as a promising candidate for adoptive cellular immunotherapy. To harness and maximize the anti-leukemia properties of these cells, we sort to comprehensively profile the transcriptomic signatures and immune repertoire of in vitro expanded γδ T cell products. Given the reported diverse TCR γδ repertoire and naïve nature of γδ T cells found in human cord blood (CB γδ), we serially track the molecular and cellular changes in these cells upon activation in expansion cultures. Based on the established viral reactivities of γδ T cell as well as prior studies showing their cross reactivities against leukemia and cancer cells, we had previously shown that stimulating CB γδ with an irradiated EBV-LCL feeder cell-based rapid expansion protocol (REP) is capable of generating cell products with potent and specific cytotoxicity against human AML cells. In the present study, using single cell RNA sequencing (scRNA-seq) coupled with single cell TCR γδ repertoire analysis, we compared the transcription signatures between our REP expanded γδ T cell (REP γδ) and non-manipulated γδ T cells reported in literatures, showing the progressive acquisition of an adult PB derived γδ T cell (PB γδ)-like cell states. Time course analysis demonstrated complex T cell activation and maturation trajectories correlating with variable level of clonal induction throughout the course of in vitro expansion. At the end of expansion, the harvested REP γδ are predominantly of the V γ4V δ1 subtype. Nevertheless, upon exposing REP γδ to target leukemia cell line K562, outgrowth of other non-V γ4V δ1 as well as the semi-invariant V γ9V δ2 cells were observed. Taken together, our data shows that as CB γδ expand and differentiate in culture, they adopt an adult PB γδ-like program. More importantly, our data highlights the rich clonal composition of in vitro expanded CB γδ, with different clonotypes being variably activated upon exposure to different stimuli. Such characteristics can potentially overcome the challenges of cancer heterogeneity and cell persistence, with the potential of improving outcomes in cell immunotherapy. Disclosures No relevant conflicts of interest to declare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".