Rapidly Expanded EBV-Specific T Cells for the Treatment of Refractory EBV Reactivation and EBV-Related Lymphoproliferative Disorders
Bibliographic record
Abstract
Background: Latent Epstein-Barr virus (EBV) infection is asymptomatic in most adults but can be associated with lymphoma, particularly in immunocompromised patients. Options are limited for patients with EBV viremia disease refractory to B-cell depleting antibodies or chemotherapy. Cellular therapies targeting EBV have shown promise in treating EBV-associated malignancies and restoring anti-EBV immunity. Methods: This is a phase I/II clinical trial in 9 patients, along with 3 additional single-patient trial cases, evaluating patient-specific manufacturing and administration of virus-specific T cells (VSTs) from various sources for the treatment or prevention of EBV-related lymphoma. The VSTs were produced from autologous and allogeneic peripheral blood mononuclear cells (PBMCs) using synthetic viral peptides stimulation. Results: Three patients were allogeneic hematopoietic stem cell transplant (HCT) recipients, 4 were solid organ transplant (SOT) recipients, and 2 were nontransplant patients with EBV-associated lymphoma. VSTs were successfully manufactured from healthy donors and demonstrated strong and specific reactivity to EBV. Six patients achieved or maintained complete responses (3 SOT and 3 HCT) while 3 did not respond to therapy (1 SOT recipient and 2 nontransplant patients), resulting in an overall response rate of 67% (86% in transplant patients). One patient died of noninfusion related complications during the study follow-up period. Cell infusions were well tolerated with no treatment-related serious adverse events reported. Conclusions: These results strengthen previously published results using VSTs from healthy donors and further support the development of EBV-specific T cell therapies to treat refractory EBV reactivation and EBV-associated malignancies, particularly in transplant recipients.
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) | 0.002 | 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".