LCL161 enhances expansion and survival of engineered anti-tumor T cells but is restricted by death signaling
Bibliographic record
Abstract
Background: The genesis of SMAC mimetic drugs is founded on the observation that many cancers amplify IAP proteins to facilitate their survival, and therefore removal of these pathways would re-sensitize the cells towards apoptosis. It has become increasingly clear that SMAC mimetics also interface with the immune system in a modulatory manner. Suppression of IAP function by SMAC mimetics activates the non-canonical NF-κB pathway which can augment T cell function, opening the possibility of using SMAC mimetics to enhance immunotherapeutics. Methods: We have investigated the SMAC mimetic LCL161, which promotes degradation of cIAP-1 and cIAP-2, as an agent for delivering transient costimulation to engineered BMCA-specific human TAC T cells. In doing so we also sought to understand the cellular and molecular effects of LCL161 on T cell biology. Results: LCL161 activated the non-canonical NF-κB pathway and enhanced antigen-driven TAC T cell proliferation and survival. Transcriptional profiling from TAC T cells treated with LCL161 revealed differential expression of costimulatory and apoptosis-related proteins, namely CD30 and FAIM3. We hypothesized that regulation of these genes by LCL161 may influence the drug's effects on T cells. We reversed the differential expression through genetic engineering and observed impaired costimulation by LCL161, particularly when CD30 was deleted. While LCL161 can provide a costimulatory signal to TAC T cells following exposure to isolated antigen, we did not observe a similar pattern when TAC T cells were stimulated with myeloma cells expressing the target antigen. We questioned whether FasL expression by myeloma cells may antagonize the costimulatory effects of LCL161. Fas-KO TAC T cells displayed superior expansion following antigen stimulation in the presence of LCL161, suggesting a role for Fas-related T cell death in limiting the magnitude of the T cell response to antigen in the presence of LCL161. Conclusions: Our results demonstrate that LCL161 provides costimulation to TAC T cells exposed to antigen alone, however LCL161 did not enhance TAC T cell anti-tumor function when challenged with myeloma cells and may be limited due to sensitization of T cells towards Fas-mediated apoptosis.
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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) | 0.002 | 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".