Highly Reproducible Quantitative Proteomics Analysis of Pancreatic Cancer Cells Reveals Proteome-Level Effects of a Novel Combination Drug Therapy That Induces Cancer Cell Death via Metabolic Remodeling and Activation of the Extrinsic Apoptosis Pathway.

Abstract

Pancreatic cancer patients have poor survival rates and are frequently treated using gemcitabine (Gem). However, initial tumor sensitivity often gives way to rapid development of resistance. Gem-based drug combinations are employed to increase efficacy and mitigate resistance, but our understanding of molecular-level drug interactions, which could assist in the development of more effective therapeutic regimens, is limited. Global quantitative proteomic analysis could provide novel mechanistic insights into drug combination interactions, but it is challenging to achieve high-quality quantitative proteomics analysis of the large sample sets that are typically required for drug combination studies. Here, we investigated molecular-level temporal interactions of Gem with BGJ398 (infigratinib), a recently approved pan-FGFR inhibitor, in multiple treatment groups (N = 42 samples) using IonStar, a robust large-scale proteomics method that employs well-controlled, ultrahigh-resolution MS1 quantification. A total of 5514 proteins in the sample set were quantified without missing data, requiring >2 unique peptides/protein, <1% protein false discovery rate (FDR), <0.1% peptide FDR, and CV < 10%. Functional analysis of the differentially altered proteins revealed drug-dysregulated processes such as metabolism, apoptosis, and antigen presentation pathways. These changes were validated experimentally using Seahorse metabolic assays and immunoassays. Overall, in-depth analysis of large-scale proteomics data provided novel insights into possible mechanisms by which FGFR inhibitors complement and enhance Gem activity in pancreatic cancers.