Background: Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer mortality in the United States (US) with a 10% 5-year survival. Acquired resistance plays a critical role in progression, however targeted therapeutics have shown minimal clinical activity. There remains an unmet need to provide combination targeted therapies across the breadth of clinical development. KinderMiner is a highly efficient text mining algorithm developed to predict association with search terms across publicly available research. BMS986158 is a novel bromodomain and extraterminal (BET) inhibitor in early phase clinical trials, recently reported to have preclinical activity in combination with chemotherapy.

Methods: Potential genes for targeting in combination with BMS986158 were queried using KinderMiner (KM) and Serial KinderMiner (SKiM). Search terms included synonymous terms of “drug resistance” and “BET”. BMS986158 was assayed for single agent activity at 72h and 144h.  Lead agents in active clinical trials were screened for synergistic activity. All assays were performed with patient derived organoids (PCOs) in a low volume format with high content imaging, using dose titration in combination grid to assay synergy.  Viability was assessed using 3D CellTiterGlo (CTG, Promega Inc) (50% v/v) with synergy scores determined by SynergyFinder 3.0 for Bliss Independence (Bliss), Highest Single Agent (HSA), and Loewe Additivity (Loewe).

Results: A KM/SKiM query was performed against >30M primary literature reports resulting in 39 unique genes with significant relationship with BET. CDK9 was selected as a lead gene target based on CDK9 inhibitor, AZD4573, in active clinical trials with highly significant prediction from text mining screen (p<0.001). BMS986158 was found to have nanomolar single agent IC50 activity across multiple primary PDAC PCOs (n=5) that improved from 72h [43-411nM] in comparison to 144h [12-54nM].  AZD4573 was found to have single agent IC50 ranging from 18-246nM across 3 primary cultures. Therapeutically relevant dosing of 6.25nM BMS986158 and 12.5nM AZD4573 in combination was found to induce significant response including normalized change in diameter relative to control, single agent BMS986158, and AZD4573 (effect sizes=1.7, 1.4, 0.7) The combination of BMS986158 and AZD4573 was also found to have augmented activity with positive synergy scores across all reference models: Bliss=3.47, HSA=8.81, and Loewe=15.92.

Conclusion: Here, we adapt a novel text-mining algorithm, KinderMiner, to screen agents for combination with BMS986158 to inform combination therapeutics.  The combination of BMS986158 and AZD4573 was shown to have improved activity in a model of PDAC PCOs. Validation of the combination efficacy across different PDAC PCOs is ongoing to compare this activity across a diversity of mutational profiles. Future directions will assay the mechanistic modeling to characterize the interaction between transcriptional regulation and the induction of apoptosis.

Citation Format: Austin Stram, Luke Koeppel, Rob Millikin, Eleanor Riedl, Md Shahadat Hossan, Ethan S Lin, Ron Stewart, Jeremy D Kratz. Activity of dual BET and CDK9 inhibition in Pancreatic Ductal Adenocarcinoma informed from KinderMiner Prediction [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A164.