Roles of Voltage-Gated Sodium (NaV) and Calcium (CaV) Channels in the Biology of the Cancer Cell
A special issue of Cells (ISSN 2073-4409). This special issue belongs to the section "Cell Microenvironment".
Deadline for manuscript submissions: closed (1 December 2023) | Viewed by 428
Special Issue Editors
Interests: ion channels; purinoreceptors; Na+/H+ exchangers; ATP; cancer cell invasion; metastases; extracellular matrix degradation; exosomes; pH regulation
Interests: NaV and CaV biophysics; cancer; drug repurposing
Interests: NaV and CaV channels in cancer; 3D invasion models; chemoresistance; ABC transporters; image-based machine-learning methods
Special Issue Information
Dear Colleagues,
Since the late 1980s and 1990s, the presence of macroscopic currents generated by voltage-gated ion channels in human malignant tumor cells has been known. The first evidence revealed both canonical and non-canonical functions of these four-domain plasma membrane proteins and suggested their active role in pro-cancerous cell properties, which led to the rise of a new research field related to ion channels in cancer.
The contribution of voltage-gated sodium channels (NaVs) to the invasive properties of tumor cells has been demonstrated in the last two decades, with NaV1.5, NaV1.7, and NaV1.6 channels being the most frequently overexpressed subunits responsible for ionic currents in cells from human cancers. The functioning of voltage-gated calcium channels (CaVs), including members of the high-voltage activated (HVA) and low-voltage activated (LVA) calcium channel families, on the other hand, is mainly related to cell growth, unlimited replicative potential, and the metastatic properties of tumoral cells.
In this Special Issue, all original research and review articles addressing the dysregulation mechanisms, clinically relevant expression profiles, biophysical characteristics, anti-cancer effect of specific antagonists, etc., of NaV and CaV channels involved in the biology of human cancers are welcome. This Special Issue also encourages the data mining of public gene expression repositories and works on image-based machine-learning methods investigating the predictive value of NaV and CaV proteins expression for therapeutic strategies and patient outcomes.
Prof. Dr. Sébastien Roger
Dr. Juan Carlos Gomora Martinez
Guest Editors
Dr. Osbaldo Lopez-Charcas
Guest Editor Assistant
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Keywords
- cancer
- Nav channels
- Cav channels
- cancer therapy
- biomarkers
- image-based machine learning
