Allogeneic Double Negative T cell Therapy as a Novel Treatment for AML Patients
Bibliographic record
Abstract
Allogeneic bone marrow transplantation (allo-BMT) is a potentially curative treatment for high-risk leukemia patients. However, a high disease relapse rate caused by residual disease and an associated toxicity such as graft-vs.-host disease (GvHD) remain as major issues that hamper recipients' survival. Many forms of immunosuppressants to control GvHD increase the risk of disease relapse, and therefore, there is an unmet need for a treatment that can target chemotherapy-resistant blasts with low off-tumor toxicity. Approaches to prevent GvHD while maintaining or enhancing graft-versus-leukemia (GvL) are the ‘Holy Grail’ for allo-BMT patients. CD3+ CD4- CD8- double negative T cell (DNT) is an unconventional mature T cell subset found in periphery. In this thesis, I have developed a method to expand therapeutically-relevant numbers of clinical-grade DNTs obtained from healthy donors (HDs) and extensively characterized them. I demonstrated that ex vivo expanded HD-DNTs target an array of leukemic cell lines and primary AML cells including chemotherapy-resistant patient samples in vitro and significantly reduce the leukemia load in patient-derived xenograft (PDX) models. Unlike CD4+ and CD8+ conventional T (Tconv) cells, DNTs do not attack normal allogeneic cells and normal xenogeneic tissues in vitro and in xenograft models. Further, potentials of using allogeneic DNTs as an off-the-shelf adoptive cell therapy have been demonstrated herein, including resistance to host-versus-graft (HvG) rejection and lack of GvHD-inducing activities. Interestingly, allogeneic DNTs effectively suppressed proliferation of Tconv cells and prevented priming of CD8+ T cells against allogeneic antigens, and infusion of DNTs with human peripheral blood mononuclear cells (PBMCs) into mice suppressed xenogeneic GvHD caused by Tconv cells. Notably, co-infusion of DNTs and PBMC into leukemia-bearing recipient eradicated the disease while suppressing tissue damage caused by Tconv cells. Collectively, in this thesis, I have developed a novel form of a cellular therapy for leukemia patients that has potentials to be used as an off-the-shelf treatment as a monotherapy or as a follow-up therapy to allo-BMT.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".