Cancer: A bioelectric disease?

Another key challenge is selectivity. As ion channels and transporters are vital for healthy tissues, particularly in the heart and nervous system, V m‐targeted interventions must be tumour‐specific to minimise off‐target effects. Exploiting cancer‐specific ion channel expression patterns or bioelectric vulnerabilities may enable selective targeting.

It is important to note that V m should not be viewed as a standalone target, but as an additional axis within existing precision oncology frameworks. 13 , 50 , 110 , 111 , 112 Combining bioelectric state information with genomic, transcriptomic and metabolic data could allow for more precise patient classification and optimisation of therapy. In this context, V m can serve as a functional layer that captures the integrated output of multiple molecular perturbations.

Additionally, computational modelling approaches and emerging digital twin frameworks offer powerful tools for simulating V m dynamics, predicting responses to bioelectric interventions, and optimising therapy in silico. 48 , 53 , 54 , 56 , 70 , 111 , 112 , 113 , 114 These approaches build on earlier bioelectric simulation platforms that model the emergence of voltage patterns, voltage‐mediated signalling, and their impact on tissue‐level organisation, thereby linking single‐cell electrophysiology to multicellular behaviour across spatial and temporal scales. 31 , 32 These frameworks enable hypothesis testing in silico and represent an important step towards predictive, multiscale modelling of bioelectric regulation in cancer.

These considerations establish membrane potential as a clinically actionable parameter with significant diagnostic and therapeutic potential. By enabling the direct measurement and manipulation of the cellular state, bioelectric approaches offer a complementary strategy to molecular targeting. This has the potential to enhance treatment efficacy, overcome resistance and improve patient outcomes.

Despite strong experimental evidence supporting the role of voltage‐gated ion channels in tumour biology, the translation of bioelectric interventions into clinical practice remains limited. 78 , 109 , 110 With the exception of tumour‐treating fields, most V m‐modulating strategies remain confined to preclinical models, including in vitro systems and non‐mammalian organisms such as Xenopus laevis. 6 , 11 , 12 , 101

Several factors contribute to this translational gap. Firstly, many experimental studies rely on simplified systems that do not fully capture the complexity of the human tumour microenvironment. Secondly, the systemic effects of ion channel modulation raise safety concerns and off‐target toxicity, particularly in excitable tissues such as the heart and nervous system. Thirdly, the lack of standardised protocols for measuring V m in patient samples complicates the integration of bioelectric biomarkers into clinical workflows. 17 , 23 , 50 , 78

Bridging this gap will require coordinated efforts to validate bioelectric targets in clinically relevant models, such as patient‐derived organoids and in vivo systems, as well as establishing robust safety profiles for V m‐modulating interventions. Additionally, early‐phase clinical trials should incorporate V m measurements as pharmacodynamic endpoints to evaluate target engagement and treatment response. Such strategies will be essential for translating promising preclinical findings into clinically actionable therapies (see Figure 3).

The evidence integrated in this review supports the interpretation of membrane potential as an integrative and clinically actionable regulator of cancer biology. However, translating this concept into clinical practice requires a structured framework that connects mechanistic understanding, quantitative measurement and therapeutic application. Here, we present a stepwise translational roadmap that positions the control of the bioelectric state as a complementary axis within precision oncology (Figure 4).

The immediate priority is to establish robust, standardised methods for measuring V m in experimental and clinical settings. 60 , 83 , 98 This includes the harmonisation of voltage‐sensitive dyes, calibration protocols, ionic conditions and temperature control, in order to ensure reproducibility and comparability across laboratories. 83 , 99

In parallel, V m must be validated as a pharmacodynamic (PD) biomarker by systematically linking voltage changes to functional outcomes such as proliferation, apoptosis, and differentiation. Incorporating V m measurements into preclinical studies and early‐phase clinical trials will be critical for establishing its predictive and monitoring value. 6 , 10 , 14 , 50 , 51 , 58 , 110

Near‐term studies should prioritise tumour entities with existing quantitative V m evidence, such as breast cancer, glioblastoma, gastric cancer and myeloma, using paired tumour‐versus‐normal biopsy profiling, standardised optical V m calibration, and prospective pharmacodynamic monitoring in early‐phase intervention studies. 47 , 58 , 59 , 60 , 83

In the medium term, V m measurements should be incorporated into multi‐parameter precision oncology frameworks alongside genomic, transcriptomic and metabolic profiling. This will enable V m to serve as a functional readout capturing the combined effects of multiple molecular alterations. 1 , 4 , 23 , 25 , 50 , 51 , 110

Biomarker‐guided therapeutic strategies can then be developed by aligning V m‐modulating interventions with specific tumour states. For instance, hyperpolarising approaches could be employed to promote differentiation in stem cell‐like tumours, while controlled depolarisation might increase susceptibility to apoptosis‐inducing therapies. 14 , 51 , 67 , 92 , 102

Computational modelling and digital twin approaches will play a central role at this stage. Existing bioelectric models can simulate V m dynamics, ion‐channel perturbations and treatment responses. This supports hypothesis testing and the virtual screening of therapeutic strategies. 48 , 55 , 111 , 112 , 115

However, the creation of fully personalised digital twins is a long‐term goal that requires advances in parameter identifiability, multimodal data integration, and the development of rigorous verification, validation, and uncertainty quantification (VVUQ) frameworks. 31 , 48 , 53 , 54 , 111 , 112 , 113 , 114

In the long term, advances in bioelectric measurement and control could make fully integrated bioelectric precision medicine possible. 115 This includes developing non‐invasive V m imaging technologies, implantable or wearable electroceutical devices and V m‐guided dosing protocols that can adjust therapy dynamically based on real‐time bioelectric feedback. 50 , 51 , 54 , 60 , 78 , 83 , 110

Such approaches could enable clinicians to actively influence tumour states by moving cells away from pathological bioelectric attractors and towards less aggressive or more therapy‐sensitive states. In this context, V m would function not only as a biomarker, but also as a control variable within adaptive treatment strategies. 2 , 100 , 111 , 116

Another key objective is to develop reference atlases mapping V m distributions across tumour types, stages and microenvironmental contexts. These atlases would provide a baseline for identifying tumour‐specific bioelectric signatures and enable comparative analyses across patient cohorts. 3 , 4 , 50 , 60 , 83 , 110

This roadmap supports a conceptual shift in cancer biology. We propose that malignancy can be conceptualised as a disorder of dysregulated bioelectric state control within a broader multi‐layered regulatory framework, consistent with emerging hypotheses in other disease domains where restoration of membrane potential is proposed as a therapeutic strategy. 2 , 12 , 34 , 50 , 55 In this model, membrane potential integrates and constrains multiple layers of cellular regulation. More broadly, this view aligns with the idea that bioelectricity is a universal and multifaceted signalling mechanism operating throughout development, regeneration and disease. 73 , 117

This perspective does not replace existing frameworks, but complements them by introducing a physically grounded, measurable and manipulable variable that links molecular perturbations to functional outcomes and aligns with emerging perspectives advocating the integration of novel regulatory dimensions into next‐generation cancer therapies. 4 , 12 , 13 , 110 , 118 Importantly, bioelectric interventions do not compete with established therapies, but provide an additional axis of control that can enhance the precision, timing and efficacy of these therapies.

By incorporating membrane potential into the conceptual and clinical framework of oncology, this approach aims to extend the scope of precision medicine from static molecular profiles to dynamic, state‐based intervention strategies. 54 , 111

Despite substantial progress, the current body of research on cancer bioelectricity has several important limitations that must be considered when interpreting its potential for translation into clinical practice.

One major limitation is the heavy reliance on in vitro systems and non‐mammalian models, such as Xenopus laevis, that may not accurately reflect the complexity of human tumours and their microenvironment. 11 While these models provide valuable mechanistic insights, their predictive value for clinical outcomes is uncertain.

In addition, methodological variability in V m measurement presents a significant challenge. Differences in electrophysiological techniques, voltage‐sensitive dyes, calibration protocols, and experimental conditions complicate quantitative comparisons across studies and limit reproducibility. 60 , 83 , 98

Another limitation is the incomplete integration of bioelectric signalling with other regulatory layers, including genetics, epigenetics, metabolism, and immunity. Although there is increasing evidence to support interactions between these domains, a unified systems‐level framework has yet to be established. 23 , 29 , 31 , 69 , 81

Finally, clinical validation of V m as a biomarker or therapeutic target is still in its infancy. Large‐scale studies demonstrating its predictive value, specificity and safety in patients are lacking. This raises the possibility that current findings may overestimate the applicability of bioelectric interventions in clinical practice. 51 , 78 , 110 Addressing these limitations is essential for advancing the field from experimental observations to clinically relevant applications.

This review summarises the growing body of evidence suggesting that the membrane potential is a key regulator of cancer cell behaviour. By integrating findings from ion channel biology, bioelectricity and oncology, we demonstrate that V m is an active determinant of proliferation, differentiation, migration and therapy response, not merely a downstream consequence of molecular alterations. 3 , 13 , 15 , 23 , 34

A key contribution of this work is shifting the focus from a reductionist, channel‐centric perspective to a systems‐level understanding of bioelectric regulation. By framing V m as an integrative state variable, we offer a unifying concept that links ion‐channel activity to signalling pathways, metabolic states and phenotypic plasticity. Quantitative synthesis of V m across tumour types further highlights that bioelectric states are measurable, comparable and potentially exploitable for clinical purposes. 59 , 60 , 83

Despite significant advances, major gaps remain. Current studies are limited by methodological variability, a lack of standardised measurement protocols, and insufficient integration into clinical research pipelines. Overcoming these challenges is essential to establishing V m as a reliable biomarker and therapeutic target. 51 , 110

Looking to the future, integrating bioelectric parameters into precision oncology frameworks promises to offer a new dimension to cancer diagnosis and treatment. Future strategies may seek to modulate global bioelectric states, thereby influencing entire regulatory networks simultaneously, without focusing exclusively on individual molecular targets. In this context, V m could function as both a diagnostic indicator and a controllable variable for therapeutic intervention. This transition may be further accelerated by computational modelling and digital twin approaches, which enable the in silico predictive, state‐based optimisation of bioelectric therapies. 53 , 54 , 111 , 112 , 113 , 114