Abstract

Abstract Introduction: Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease, commonly characterized by multiple aberrant signaling. Phosphoproteomics provides a direct read-out of these complex signaling networks and the resultant clinically relevant phenotype, as well as a functional scaffold to identify new targets. In the absence of an oncogenic driver, low dose (LD) kinase inhibitor (KI) combinations against multiple (parallel) activated kinases might provide higher efficacy and reduce toxicity as compared to single drug treatment. Aims: 1) To identify targets and test combinations of multiple KIs at LDs for potential synergism in preclinical models. 2) To chart the phosphoproteome of 42 PDAC tumors to reveal signalling pathways that may be involved in PDAC progression. Methods: By using a two step phosphopeptide enrichment with phosphotyrosine immunoprecipitation and immobilized metal affinity chromatography, followed by label free MS analysis, we analyzed phosphoproteome data of 7 immortalized and 2 primary PDAC cell lines, and of 42 PDAC tumors. We used integrative inferred kinase activity (INKA) scoring of the maxquant output to identify hyperactive kinases. For the cell line panel, five KIs were selected based on targeting coverage of the INKA profiles. LD were set as IC20s for 2,3,4 drug combinations. Cell growth inhibition was assessed by SRB assay. Median-effect analysis was used to assess synergy. Functional testing was performed in immortalized 2D, xenoderived 2D and 3D cultures. Effective low dose 3 drug combinations were further validated using patient-derived xenografts. Results: High INKA scoring of multiple activities per cell line without clear outliers of single kinases underscores the need for combination therapies. Multiple LD combinations showed effective growth inhibition (70 to 92%) and synergism, mostly 3 drug combinations, which required targeting of several RTKs and downstream signaling. Different responses were further observed between epithelial and mesenchymal cell lines. These top performing combinations were further validated in PDAC organoids and in vivo. Clinical utility of these kinase targets was then confirmed in 42 tumor phosphoprofiles, which were characterized in different subtypes with distinct therapeutic options. Phosphoproteome signals and kinases activities with potential prognostic value and mutational associations were further described. Conclusion: Our INKA pipeline, which can rank kinase activities in individual tumors, is optimally suited to specifically prioritize actionable kinases with targeting purposes. Tailored LD combination strategies exhibited promising efficacy in preclinical models and may ultimately improve treatment outcomes. Next Steps: Multicellular patient-derived models will be used to further study and target the TME in PDAC tumors. Citation Format: Andrea Vallés Martí, Giulia Mantini, Cynthia Waasdorp, Richard R. de Goeij- de Haas, Alex A. Henneman, Sander R. Piersma, Thang V. Pham, Jaco C. Knol, Joanne Verheij, Frederike Dijk, Hans Halfwerk, Elisa Giovannetti, Connie R. Jiménez, Maarten F. Bijlsma. Profile guided low dose drug combination strategies and kinase activities with prognostic and therapeutic avenues in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6485.

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