Abstract
Signaling pathways are useful models for interpreting molecular data, but their coverage has long been constrained by classic biochemistry methods. The growing corpus of kinase-substrate interactions, coupled to phosphoproteomics improvements, pave the way to revisit classic signaling pathways. In this study, we explore context-specific signaling pathway inference from phosphoproteomics and kinase-substrate networks. Focusing on epidermal growth factor (EGF), we conduct a meta-analysis and generate three datasets representing the most comprehensive characterization of the EGF response to date. We infer kinase-kinase pathways and compare them to different ground truth sets. Literature-curated networks consistently yield the highest recovery of ground-truth interactions, with modest gains from network propagation methods. Up to 90% of interactions are absent from current ground truth sets, indicating many unexplored interactions supported by data and knowledge. Our results demonstrate the limitations of traditional views on signaling pathways and point to opportunities for generating better mechanistic hypotheses.
Data availability
All the data to reproduce the results presented in this study can be retrieved from Zenodo: [https://zenodo.org/records/18390833]. The mass spectrometry proteomics raw data generated in this study have been deposited to the ProteomeXchange Consortium via the PRIDE56 partner repository with the dataset identifier PXD056666.
Code availability
All the code to reproduce the results of this manuscript can be accessed at: [https://zenodo.org/records/18390833].
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Acknowledgements
MGR was supported through state funds approved by the State Parliament of Baden-Württemberg for the Innovation Campus Health + Life Science Alliance Heidelberg Mannheim. We thank Ana Mellado-Fuentes for her assistance with the HEK293T experiment and Attila Gabor for fruitful discussions. We thank the authors of studies re-analyzed in this manuscript for providing transparent access to their data. We acknowledge EMBL IT Services for support with high-performance computing.
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M.G.R.: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Software, Writing - Original Draft Preparation. C.P.: Conceptualization, Investigation, Methodology, Validation, Writing - Original Draft Preparation. M.L.B.: Investigation, Visualization. I.B.: Investigation, Visualization. P.R.M.: Methodology, Software, Formal analysis. S.M.D.: Software, Formal analysis. M.S.: Resources, Project administration, Writing - Original Draft Preparation, Supervision, Funding acquisition. J.S.R.: Resources, Project administration, Writing - Original Draft Preparation, Supervision, Funding acquisition.
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J.S.R. reports funding from GSK, Pfizer, and Sanofi and fees/honoraria from Travere Therapeutics, Stadapharm, Astex, Pfizer, Grunenthal, Moderna, and Owkin. The remaining authors declare no competing interests.
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Garrido-Rodriguez, M., Potel, C., Burtscher, M.L. et al. Benchmarking EGF signaling pathway inference using phosphoproteomics and kinase-substrate interactions. Nat Commun (2026). https://doi.org/10.1038/s41467-026-69332-0
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DOI: https://doi.org/10.1038/s41467-026-69332-0
