Development of Improved Lentiviral ‘Suicide’ Gene Therapy for the Management of GvHD and GvL/GvT Responses in Allogeneic BMT.
Bibliographic record
Abstract
Abstract Donor Lymphocyte Infusion (DLI) is employed in the treatment of various malignancies, as donor-derived allogeneic T lymphocytes elicit strong anti-tumor immune responses (GvL/GvT). Unfortunately, these are often accompanied by GvHD, mediated by donor T cells that are allo-activated against host tissues. GvHD manifests with immunosupression, multi-organ dysfunction, severe morbidity and high mortality. It is suggested that CD4+Th1 and CD8+Tc1 cell subsets mediate both strong GvL/GvT and strong GvHD, while being cross-regulated by CD4+Th2 and CD8+Tc2 cells that mediate only moderate effects. Patients transplanted with T cell-depleted BM experience little GvHD, but have high rates of cancer relapse. It is possible to maintain beneficial GvL/GvT responses while controlling GvHD by transferring a drug-activating ‘suicide’ gene into donor T cells prior to transplant. Cells expressing the ‘suicide’ gene-product convert a non-toxic prodrug into a cytotoxic antimetabolite, and are eliminated by apoptosis. We have constructed 3rd generation lentiviral vectors (LVs) for the expression of human converting enzymes. We are using novel enzymes, endogenously present in human cells, to avoid unwanted immune responses against vector-transduced cells, recently proven a major drawback in clinical trials. Our approaches are based on the human thymidylate kinase (Tmpk), which acts on Zidovudine (AZT), and the human deoxycytidine kinase (dCK), which potently activates a number of prodrugs, including Cytarabine (AraC), Gemcitabine and Cladribine. We have developed active-site engineered mutants of Tmpk and dCK that are up to two orders of magnitude more catalytically active than wild-type (wt) enzymes. Our LVs efficiently transduce both immortalized and primary cells (up to 99%). The LV expression cassette also encodes a non-signaling form of human CD19 molecule that serves as a marker for ex vivo enrichment and in vivo tracking of transduced cells. We demonstrate efficient, selective and prompt killing of transduced cells in a dose-dependent manner by a number of prodrugs in cell lines in vitro and in a murine solid tumor model in vivo. For example, R16GLL Tmpk mutant-transduced Jurkat cells (human T cell leukemia line) are completely killed by apoptosis within 4 days of culture in media containing 100uM AZT (IC50 of 2μM), while wt cells are unaffected at the same conditions. In a NOD/SCID murine tumor model, K562 erythroid leukemia cells transduced with either empty vector, wt Tmpk, and R16GLL or F105Y Tmpk mutants were implanted subcutaneously. Mice bearing tumor cells expressing either R16GLL or F105Y Tmpk and receiving a low daily dose of 2.5mg/kg of AZT have developed significantly reduced tumors following 2 weeks of treatment (tumor size of 24–200mm2), compared to mice bearing wt Tmpk and empty vector transduced cells, or untreated mice (tumor size of over 1000mm2). We are currently evaluating the efficiency with which transduced cells can be cleared from circulation in a murine leukemia model and are evaluating the complete GvHD-treatment strategy in a murine model of GvHD/GvT based on the CD45 congenic strains. This much improved therapeutic strategy may offer a safe and complete solution for GvHD in patients undergoing BMT.
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 | 0.001 |
| 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".