Befriending the Hostile Tumor Microenvironment in CAR T-Cell Therapy
Bibliographic record
Abstract
T-cells genetically engineered to express a chimeric antigen receptor (CAR) have shown remarkable results in patients with B-cell malignancies, including B-cell acute lymphoblastic leukemia, diffuse large B-cell lymphoma, and mantle cell lymphoma, with some promising efficacy in patients with multiple myeloma. However, the efficacy of CAR T-cell therapy is still hampered by local immunosuppression and significant toxicities, notably cytokine release syndrome (CRS) and neurotoxicity. The tumor microenvironment (TME) has been identified to play a major role in preventing durable responses to immunotherapy in both solid and hematologic malignancies, with this role exaggerated in solid tumors. The TME comprises a diverse set of components, including a heterogeneous population of various cells and acellular elements that collectively contribute towards the interplay of pro-immune and immunosuppressive signaling. In particular, macrophages, myeloid-derived suppressor cells, regulatory T-cells, and cell-free factors such as cytokines are major contributors to local immunosuppression in the TME of patients treated with CAR T-cells. In order to create a more favorable niche for CAR T-cell function, armored CAR T-cells and other combinatorial approaches are being explored for potential improved outcomes compared to conventional CAR T-cell products. While these strategies may potentiate CAR T-cell function and efficacy, they may paradoxically increase the risk of adverse events due to increased pro-inflammatory signaling. Herein, we discuss the mechanisms by which the TME antagonizes CAR T-cells and how innovative immunotherapy strategies are being developed to address this roadblock. Furthermore, we offer perspective on how these novel approaches may affect the risk of adverse events, in order to identify ways to overcome these barriers and expand the clinical benefits of this treatment modality in patients with diverse cancers. Precise immunomodulation to allow for improved tumor control while simultaneously mitigating the toxicities seen with current generation CAR T-cells is integral for the future application of more effective CAR T-cells against other malignancies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".