ReviewFrontiers in systems biology2026
GPCR signaling systems facilitate precision interventions for multi-oncology therapy.
Review in Frontiers in systems biology, 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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7 authors.
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Abstract
Precision oncology has undergone a transformative evolution from static genomic profiling toward dynamic, multi-omics frameworks capable of capturing tumor heterogeneity and adaptive resistance in real time. Central to this paradigm shift is the emerging recognition that G protein-coupled receptors (GPCRs) constitute a vastly underexploited axis of oncogenic signaling, tumor microenvironment (TME) modulation, and non-genetic adaptive resistance. Here we delineate the effective transition to GPCR-focused precision oncology, emphasizing the integrated deployment of next-generation sequencing (NGS), single-cell transcriptomics, expression-based liquid biopsies (ctRNA, exosomal miRNA, circulating tumor cells), and AI-driven quantitative systems network modeling to interrogate GPCR signaling dynamics across solid and hematologic malignancies. GPCRs, comprising approximately 800 human receptors with extensive pharmacological plasticity, encompassing biased agonism, allosteric modulation, receptor heterodimerization, and ligand-independent signaling, serve as critical integrators of extracellular cues and intracellular transcriptional programs. Their overexpression, mutation, and epigenetic dysregulation in multiple cancer types positions them as both prognostic biomarkers and actionable therapeutic targets. We discuss recent advances in integrative genomic platforms, liquid biopsy evolution, case studies of GPCR-driven tumor evolution, and cutting-edge therapeutic modalities, including PROTACs (Proteolysis Targeting Chimeras), biased ligands, RNA therapeutics, and digital twin modeling, to articulate a forward-looking vision for GPCR-centric precision oncology. By harnessing real-time tumor monitoring and AI-optimized adaptive therapies, this framework promises to overcome the limitations of static genomic approaches, enabling mid-treatment recalibration to combat resistance and improve durable survival in heterogeneous solid tumors.
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