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Photoelectrical control of apoptosis and autophagy
1Independent Researcher, Pavia, Italy.
Biophysical Reports
|November 30, 2025
Summary
This study introduces a bioelectronic oncology framework to control cancer cell fate using electrical stimulation. Photovoltaic stimulation modulates reactive oxygen species (ROS) and ion channels, offering a new approach for cancer therapy.
Area of Science:
- Bioelectronic oncology
- Cancer cell fate regulation
- Electrophysiology and redox signaling
Background:
- Electrically excitable cancer cells exhibit unique sensitivities to electrical and redox stimuli.
- Controlling cancer cell fate involves membrane depolarization, reactive oxygen species (ROS) dynamics, and voltage-gated ion channel (VGIC) activation.
- Photoelectrical stimulation offers a novel approach to modulate these cellular processes.
Purpose of the Study:
- To develop an integrated theoretical and transcriptomic framework for photoelectrical stimulation in cancer therapy.
- To investigate how photocapacitive and photofaradaic stimulation influences intracellular signaling pathways and cell fate outcomes.
- To establish a predictive foundation for designing cell-type-specific photovoltaic cancer therapies.
Main Methods:
- Development of an integrated theoretical and transcriptomic framework.
- Utilizing experimental data sets (GSE59612, GSE103224, GSE97508, GSE45827) for parameterization.
- Simulations of photovoltaic stimulation (20-Hz waveform) and cell fate modeling.
Main Results:
- Photocapacitive depolarization elevates glioblastoma ROS levels, inducing a proliferative-to-autophagic transition.
- Glioblastoma-specific redox thresholds align with transcriptomic VGIC and antioxidant signatures.
- Photovoltaic stimulation in MDA-MB-231 cells induces controlled autophagy, offering anti-inflammatory benefits.
Conclusions:
- The integrated framework provides a predictive foundation for photovoltaic cancer therapies.
- Therapies can be tuned to cell-type-specific electrophysiological and redox landscapes.
- This approach unifies stimulation physics, bioelectrical modeling, and omics data for targeted cancer treatment.
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