588 Selective inhibition of Diacylglycerol kinase zeta exhibits increased T cell activation and anti-tumor immunity, demonstrating pharmacodynamic proof of mechanism in the FIH trial of BAY2965501
Bibliographic record
Abstract
Background T cell checkpoint blockade has revolutionized cancer treatment, however, transformative clinical responses continue to be observed in only a subset of patients and tumor indications. Inherently, the finite capacity of a patient’s immune system to recognize tumor mutations as foreign antigens is a well-established factor limiting the benefit of immunotherapy. Diacylglycerol kinases zeta (DGKζ) and alpha, are expressed in T cells and play a key role modulating the intensity of T cell receptor (TCR) signaling. Through phosphorylation of the critical secondary messenger diacylglycerol (DAG) to form phosphatidic acid, DGKs act as intracellular checkpoints attenuating T cell activation and limiting recognition of tumor antigens. Preclinically, BAY2965501 has been shown to inhibit DGKζ enhancing T cell activation and resistance to immune suppression. These effects lead to improved anti-tumor activity in vitro and in vivo syngeneic mouse tumor models as a monotherapy and in combination with anti-PD-1. Thus, selective blocking of DGKζ could represent an attractive strategy to overcome the limitations of first generation immunotherapies.Methods BAY2965501 is being investigated in a FIH dose-escalation and expansion study ( NCT05614102) to evaluate safety, pharmacokinetics and pharmacodynamics, in patients with solid tumors as a monotherapy and in combination with anti-PD-1 antibody pembrolizumab. In addition, a major objective of the study is to establish proof of mechanism (PoM) and determine if DGKζ inhibition has the potential to expand anti-tumor immune responses in patients. To achieve this, the ability of BAY2965501 to enhance TCR signaling, increase T cell function and activation along with modulating the TCR repertoire was evaluated in peripheral blood (n=>100) and tumors (n=>25) across >100 patients in monotherapy and PD-1 combination cohorts.Results Treatment with BAY2965501 achieved exposures above the preclinically defined EC50 necessary for immunologically relevant enhancement of T cell function. This resulted in a dose dependent modulation of TCR signaling as measured by increased ERK phosphorylation and cytokine production in ex vivo assays. Peripherally, patients also showed >2-fold increase in in-situ T cell activation (Ki67+) compared to baseline levels. BAY2965501-induced T cell activation coincided with expansion of newly detected T cell clones both in monotherapy and anti-PD-1 combination as measured by TCRseq. In evaluable paired biopsies, >50% of patients demonstrated >2-fold increase of T cell infiltration/activation confirming DGK inhibition dependent changes in anti-tumor immunity.Conclusions BAY2965501 demonstrates pharmacodynamic PoM in monotherapy and combination, providing evidence that specific inhibition of DGKζ in patients is sufficient to modulate anti-tumor immunity.Acknowledgements Acknowledgments: BAY2965501 DGKz trial 21948 investigators and their patients that participated in the trial and provided samples for this analysisEthics Approval Data from This abstract was collected as part of clinical study NCT05614102 and has received regulatory approval from respective countries and IRBs of respective institutions participating in the trial
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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) | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".