CAR T cells and T cells phenotype and function are impacted by glucocorticoid exposure with different magnitude
Bibliographic record
Abstract
BACKGROUND: Chimeric antigen receptor (CAR) T cell therapy is associated with high risk of adverse events. Glucocorticoids (GCs) are cornerstone in the management of high-grade cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). Given the potentially deleterious effects of GCs on CAR T cells anti-tumor activity, increasing our understanding of GCs impact on CAR T cells is crucial. METHODS: Using several CAR T cells i.e., CD19, mesothelin (MSLN)-CD28 and MSLN-41BB CAR T cells (M28z and MBBz), we compared phenotypical, functional, changes and anti-tumor activity between i) transduced CD19 CAR T cells with untransduced T cells, ii) M28z with MBBz CAR T cells induced by Dexamethasone (Dx) or Methylprednisolone (MP) exposures. RESULTS: Higher levels of GC receptor were found in less differentiated CAR T cells. Overall, Dx and MP showed a similar impact on CAR T cells. Compared to untreated condition, GCs exposure increased the expression of PD-1 and TIM-3 and reduced the expression of LAG3 and function of T cells and CAR T cells. GC exposures induced more exhausted (LAG3 + PD1 + TIM3 +) and dysfunctional (CD107a-INFγ-TNF-IL2-) untransduced T cells in comparison to CD19 CAR T cells. GC exposure impaired more CD4 + than CD8 + CD19 CAR T cells. GC exposures increased more PD-1 expression associated with reduced proliferative capacity and function of M28z as compared to MBBz CAR T cells. CAR T cells anti-tumor activity was greatly affected by repeated GC exposure but partly recovered within 48h after GCs withdrawal. CONCLUSIONS: In summary, GCs impacted phenotype and function of untransduced and CAR T cell with different magnitude. The nature of the CAR costimulatory domain influenced the magnitude of CAR T cell response to GCs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 teacher head, 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".