Single-cell RNA sequencing of human double-negative T cells reveals a favorable cellular signature for cancer therapy
Bibliographic record
Abstract
Background Allogeneic double-negative T-cell (DNT) therapy has emerged as a novel, off-the-shelf cellular treatment with clinical feasibility, safety, and promising efficacy against leukemia. However, the biology of DNTs is less well characterized, and how DNT therapy distinguishes from conventional γδ T-cell therapy remains unclear. Collectively, this hinders our ability to bolster DNT functionalities in cancer therapy. Here, we performed single-cell RNA sequencing with in vitro and in vivo functional analysis on DNTs. As a significant proportion of DNTs express Vγ9Vδ2 (Vδ2) TCR chain, we compared DNTs with donor-matched conventional Vδ2 T cells expanded with zoledronic acid. Methods Healthy donor-derived allogeneic DNTs and Vδ2 T cells were expanded ex vivo. Single-cell RNA sequencing analysis was performed on both cellular products to identify the transcriptional landscape and inferred cellular interactions within DNTs, followed by comparisons with donor-matched Vδ2 T cells. Unique cellular subsets found only in DNTs were depleted to identify their contributions to the overall efficacy of DNTs against acute myeloid leukemia. The anti-leukemic activity and in vivo persistence of DNTs and Vδ2 T-cells were explored using flow cytometry-based cytotoxicity assays, memory phenotyping, and xenograft models. Results Despite a shared Vδ2 expression between cellular products, we identified unique cellular compositions in DNTs that contribute to distinct transcriptional and cellular communication patterns relative to the donor-matched Vδ2 T cells, including higher expression of genes identified in chimeric antigen receptor T cells that persist in patients with durable cancer-remission. Vδ2 – DNTs exhibited strong persistence characteristics, and their presence promoted the cytotoxic capabilities of Vδ2 + DNTs in repeated stimulation assays. This unique genetic signature and diverse cellular composition of DNTs resulted in better overall ex vivo expansion, prolonged persistence, and superior anti-leukemic activity compared with Vδ2 T cells in vitro and in vivo. Conclusions These results highlight the unique transcriptional, cellular, and functional profile of human DNTs and support the continued clinical investigation of allogeneic DNT therapy. The data also provide a reference gene signature that may help improve the efficacy of other types of allogeneic adoptive cellular therapies.
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 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".