Lenalidomide enhances CD23.CAR T cell therapy in chronic lymphocytic leukemia
Bibliographic record
Abstract
Chimeric antigen receptors (CAR)-modified T cells are an emerging therapeutic tool for chronic lymphocytic leukemia (CLL). However, in patients with CLL, well-known T-cell defects and the inhibitory properties of the tumor microenvironment (TME) hinder the efficacy of CAR T cells. We explored a novel approach combining CARs with lenalidomide, an immunomodulatory drug that tempers the immunosuppressive activity of the CLL TME. T cells from patients with CLL were engineered to express a CAR specific for CD23, a promising target antigen. Lenalidomide maintained the in vitro effector functions of CD23.CAR+ T cells effector functions in terms of antigen-specific cytotoxicity, cytokine release and proliferation. Overall, lenalidomide preserved functional CAR T-CLL cell immune synapses. In a Rag2−/−γc−/−-based xenograft model of CLL, we demonstrated that, when combined with low-dose lenalidomide, CD23.CAR+ T cells efficiently migrated to leukemic sites and delayed disease progression when compared to CD23.CAR+ T cells given with rhIL-2. These observations underline the therapeutic potential of this novel CAR-based combination strategy in CLL.
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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) | 0.001 | 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".