Endogenous CD28 drives CAR T cell responses in multiple myeloma
Bibliographic record
Abstract
Abstract Recent FDA approvals of chimeric antigen receptor (CAR) T cell therapy for multiple myeloma (MM) have reshaped the therapeutic landscape for this incurable cancer. In pivotal clinical trials B cell maturation antigen (BCMA) targeted, 4-1BB co-stimulated (BBζ) CAR T cells dramatically outperformed standard-of-care chemotherapy, yet most patients experienced MM relapse within two years of therapy, underscoring the need to improve CAR T cell efficacy in MM. We set out to determine if inhibition of MM bone marrow microenvironment (BME) survival signaling could increase sensitivity to CAR T cells. In contrast to expectations, blocking the CD28 MM survival signal with abatacept (CTLA4-Ig) accelerated disease relapse following CAR T therapy in preclinical models, potentially due to blocking CD28 signaling in CAR T cells. Knockout studies confirmed that endogenous CD28 expressed on BBζ CAR T cells drove in vivo anti-MM activity. Mechanistically, CD28 reprogrammed mitochondrial metabolism to maintain redox balance and CAR T cell proliferation in the MM BME. Transient CD28 inhibition with abatacept restrained rapid BBζ CAR T cell expansion and limited inflammatory cytokines in the MM BME without significantly affecting long-term survival of treated mice. Overall, data directly demonstrate a need for CD28 signaling for sustained in vivo function of CAR T cells and indicate that transient CD28 blockade could reduce cytokine release and associated toxicities.
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 | 0.001 |
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".