ReviewBioscience reports2026
Proteomic investigation of signaling dynamics: from static maps to network rewiring.
Review in Bioscience reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
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0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
4 authors.
Funding
Abstract
Cellular processes are controlled by interconnected networks of protein-protein interactions that can be dynamically regulated by post-translational modifications such as phosphorylation. Dysregulation of signaling pathways can drive cellular transformation and contribute to cancer treatment resistance. Mass spectrometry (MS)-based approaches have emerged as key technologies to study both protein function and their dynamic regulation at a network level. Modern proteomics allows investigators to study how signaling networks are rewired in response to genetic lesions, external cues, and targeted therapies, enabling the comparison of baseline (steady-state) networks to perturbed states. Here, we briefly describe key advancements in proteomics to study signaling dynamics, including affinity-purification combined with MS, proximity proteomics (e.g., BioID, APEX), and phosphoproteomics. We highlight how proteomics has led to the identification of comprehensive protein-protein interaction networks, to the delineation of protein subcellular localization maps and to discoveries regarding their dynamics and rewiring in disease. Finally, we comment on the future directions of proteomics to study signaling dynamics, enabled by next-generation MS instruments and AI-driven data analysis, and discuss how these developments are paving the way for clinical translation by bringing quantitative network biology into patient-relevant contexts.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.