As the leading cause of death in cancer, there is an urgent need to develop treatments to target the dissemination of primary tumor cells to secondary organs, known as metastasis. Bioelectric signaling has emerged in the last century as an important controller of cell growth, and with the development of current molecular tools we are now beginning to identify its role in driving cell migration and metastasis in a variety of cancer types. This review summarizes the currently available research for bioelectric signaling in solid tumor metastasis. We review the steps of metastasis and discuss how these can be controlled by bioelectric cues at the level of a cell, a population of cells, and the tissue. The role of ion channel, pump, and exchanger activity and ion flux is discussed, along with the importance of the membrane potential and the relationship between ion flux and membrane potential. We also provide an overview of the evidence for control of metastasis by external electric fields (EFs) and draw from examples in embryogenesis and regeneration to discuss the implications for endogenous EFs. By increasing our understanding of the dynamic properties of bioelectric signaling, we can develop new strategies that target metastasis to be translated into the clinic.
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http://dx.doi.org/10.1089/bioe.2019.0013 | DOI Listing |
Medicine (Baltimore)
November 2024
Graduate School, Heilongjiang University of Chinese Medicine, Haerbin, China.
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January 2025
The Affiliated Stomatological Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, 401147, P. R. China.
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View Article and Find Full Text PDFBiomaterials
January 2025
State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China. Electronic address:
Artif Intell Med
December 2024
Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran. Electronic address:
Modeling Optical Coherence Tomography (OCT) images is crucial for numerous image processing applications and aids ophthalmologists in the early detection of macular abnormalities. Sparse representation-based models, particularly dictionary learning (DL), play a pivotal role in image modeling. Traditional DL methods often transform higher-order tensors into vectors and then aggregate them into a matrix, which overlooks the inherent multi-dimensional structure of the data.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai 519031, China.
Electroencephalogram (EEG) signals are important bioelectrical signals widely used in brain activity studies, cognitive mechanism research, and the diagnosis and treatment of neurological disorders. However, EEG signals are often influenced by various physiological artifacts, which can significantly affect data analysis and diagnosis. Recently, deep learning-based EEG denoising methods have exhibited unique advantages over traditional methods.
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