ReviewCancers2026
Post-Translational Modification Crosstalk in Gastric Cancer: Molecular Switches, Signaling Networks, and Therapeutic Opportunities, with Comparative Insights from Colorectal Cancer.
Review in Cancers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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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.
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Authors and funding
4 authors.
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Abstract
Gastric cancer remains a leading cause of cancer-related death, and its malignant behavior is driven in large part by dysregulated post-translational modifications (PTMs). Yet the prevailing tendency to study individual modifications in isolation has obscured a defining feature of PTM biology: modifications frequently interact, competing for the same residue or cooperating across residues to form regulatory switches that dictate protein fate. This review synthesizes the PTM crosstalk framework in gastric cancer around three principal axes-phosphorylation-ubiquitination relays, SUMOylation-ubiquitination interplay, and metabolic coupling through lactylation-and traces how these axes translate into the hallmarks of proliferation, metastasis, therapeutic resistance, and immune evasion. The framework is further extended to colorectal cancer to separate shared regulatory principles from cancer-specific switches. Central to this account is the proposition that oncogenic output is governed not by any single modification but by the balance among competing and cooperating marks, and that the switch enzymes maintaining this balance constitute the most informative therapeutic targets. Translating this view into therapy will require selective degraders and inhibitors, crosstalk-aware biomarkers, and systematic multi-omics maps of the modification network.
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