Abstract LB037: CD28 drives CAR T cell responses in multiple myeloma
Bibliographic record
Abstract
Abstract FDA approval of chimeric antigen receptor (CAR) T cell therapy for multiple myeloma (MM) has reshaped the therapeutic landscape for this incurable disease. In pivotal clinical trials CAR T cells outperformed standard-of-care chemotherapy, yet most patients experienced MM relapse within two years, underscoring the need to improve CAR T cell therapy for MM. In the current study, we set out to determine if inhibition of MM survival signaling through CD28 could increase sensitivity to CAR T cell therapy. Contrary to expectations, we found that blocking CD28 interaction with its ligands CD86/CD80 using abatacept (CTLA4-Ig) accelerated MM relapse following CAR T therapy in preclinical models. Knockout studies determined that endogenous CD28 expressed on 4-1BB co-stimulated (BBζ) CAR T cells sustained in vivo anti-MM activity. Mechanistically, endogenous CD28 reprogrammed BBζ CAR T cell mitochondrial metabolism to maintain redox balance, stimulated proliferation, and increased inflammatory cytokine production in the MM bone marrow microenvironment (BME). In agreement, higher grade cytokine-mediated toxicities were associated with CD86 expression on CD138+ cells from CAR T cell treated MM patients and short-term abatacept exposure decreased inflammatory cytokine levels in the MM BME of CAR T cell treated mice without affecting their long-term survival. Overall, data directly demonstrate that CD28 signaling sustains in vivo function of BBζ CAR T cells and indicate that transient CD28 inhibition could reduce cytokine release and associated toxicities in MM patients. Citation Format: Mackenzie M. Lieberman, Jason H. Tong, Nkechi U. Odukwe, Colin A. Chavel, Kimberly M. Crasti, Terrence J. Purdon, Craig M. Brackett, Spencer R. Rosario, A.J. Robert McGray, Jonathan L. Bramson, Renier J. Brentjens, Ehsan Malek, Kelvin P. Lee, Scott H. Olejniczak. CD28 drives CAR T cell responses in multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB037.
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".