ReviewFrontiers in oncology2026
Translating physical stress into biological signals: precision electro-oncology based on conformational changes of electro-sensitive receptors and parameterized immune remodeling.
Review in Frontiers in oncology, 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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5 authors.
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Abstract
Tumor Treating Fields (TTFields) and pulsed electric fields (PEF) have emerged as a fourth modality in oncological treatment, succeeding surgery, radiotherapy, and pharmacotherapy. However, the fundamental mechanisms through which physical electrical stress is precisely transduced into biochemical signals remain to be fully elucidated. By integrating molecular dynamics simulations, multi-omics profiling, and the latest clinical trial data, this review systematically explores how electric fields, functioning as physical signals, initiate intracellular transduction by inducing conformational kinetic changes in G protein-coupled receptors (GPCRs), such as NPFFR2. Furthermore, we discuss how the modulation of waveform parameters enables the precise programming of apoptosis and pyroptosis patterns, thereby inducing immunogenic cell death (ICD) and activating the cGAS-STING pathway. Additionally, proteomics-based insights are employed to reveal the mechanisms of electric-field-induced compensatory resistance, and the pivotal role of electric fields in remodeling the tumor immune microenvironment and reversing resistance to immune checkpoint inhibitors is discussed. This review aims to provide refined theoretical guidance for the clinical translation of the emerging field of the "electro-immunome".
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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 Socratic graph.