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Phosphoproteomics guides effective low-dose drug combinations against pancreatic ductal adenocarcinoma
Andrea Vallés-Martí1, Giulia Mantini2, Paul Manoukian3
1Amsterdam University Medical Center, VU University, Department of Medical Oncology, Amsterdam, the Netherlands; Cancer Center Amsterdam, OncoProteomics Laboratory, Amsterdam, the Netherlands; Cancer Center Amsterdam, Cancer Biology, Amsterdam, the Netherlands; Cancer Center Amsterdam, Pharmacology Laboratory, Amsterdam, the Netherlands.
Abstract:
Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a limited set of known driver mutations but considerable cancer cell heterogeneity. Phosphoproteomics provides a readout of aberrant signaling and has the potential to identify new targets and guide treatment decisions. Using two-step sequential phosphopeptide enrichment, we generate a comprehensive phosphoproteome and proteome of nine PDAC cell lines, encompassing more than 20,000 phosphosites on 5,763 phospho-proteins, including 316 protein kinases. By using integrative inferred kinase activity (INKA) scoring, we identify multiple (parallel) activated kinases that are subsequently matched to kinase inhibitors. Compared with high-dose single-drug treatments, INKA-tailored low-dose 3-drug combinations against multiple targets demonstrate superior efficacy against PDAC cell lines, organoid cultures, and patient-derived xenografts. Overall, this approach is particularly more effective against the aggressive mesenchymal PDAC model compared with the epithelial model in both preclinical settings and may contribute to improved treatment outcomes in PDAC patients.
Insights
This study used phosphoproteomics to identify activated kinases in pancreatic cancer. Tailored low-dose drug combinations targeting multiple kinases showed superior efficacy in preclinical models.
Area of Science:
- Biochemistry
- Oncology
- Proteomics
Background:
- Pancreatic ductal adenocarcinoma (PDAC) presents significant challenges due to limited known driver mutations and substantial cancer cell heterogeneity.
- Phosphoproteomics offers a method to analyze aberrant signaling pathways, potentially revealing novel therapeutic targets for PDAC.
- Identifying and targeting activated kinases is crucial for developing effective PDAC treatments.
Purpose of the Study:
- To comprehensively map the phosphoproteome and proteome of PDAC cell lines.
- To identify activated kinases and their potential drug targets using integrative inferred kinase activity (INKA) scoring.
- To evaluate the efficacy of multi-target kinase inhibitor combinations compared to single-drug treatments.
Main Methods:
- Utilized two-step sequential phosphopeptide enrichment to generate comprehensive phosphoproteome and proteome data from nine PDAC cell lines.
- Analyzed over 20,000 phosphosites on 5,763 phospho-proteins, including 316 protein kinases.
- Applied integrative inferred kinase activity (INKA) scoring to identify activated kinases and matched them with kinase inhibitors.
Main Results:
- Identified multiple parallel activated kinases within PDAC cell lines.
- Demonstrated superior efficacy of low-dose, three-drug combinations tailored by INKA scoring compared to high-dose single-drug treatments.
- Observed enhanced effectiveness of the multi-target approach in aggressive mesenchymal PDAC models versus epithelial models in preclinical settings.
Conclusions:
- INKA scoring effectively identifies actionable kinase targets in PDAC.
- Multi-target, low-dose drug combinations show significant promise for improving PDAC treatment outcomes.
- This phosphoproteomics-guided strategy offers a new avenue for precision medicine in pancreatic cancer therapy.
