Abstract A164: Activity of dual BET and CDK9 inhibition in Pancreatic Ductal Adenocarcinoma informed from KinderMiner Prediction

• Published in: Molecular cancer therapeutics 2023-12, Vol.22 (12_Supplement), p.A164-A164
• Main Authors: Stram, Austin, Koeppel, Luke, Millikin, Rob, Riedl, Eleanor, Hossan, Md Shahadat, Lin, Ethan S, Stewart, Ron, Kratz, Jeremy D
• Format: Article
• Language: English
• ISSN: 1538-8514; 1538-8514
• DOI: 10.1158/1535-7163.TARG-23-A164

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