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Ion Channels in Cancer: Are Cancer Hallmarks Oncochannelopathies?
Abstract
Genomic instability is a primary cause and fundamental feature of human cancer. However, all cancer cell genotypes generally translate into several common pathophysiological features, often referred to as cancer hallmarks. Although nowadays the catalog of cancer hallmarks is quite broad, the most common and obvious of them are 1) uncontrolled proliferation, 2) resistance to programmed cell death (apoptosis), 3) tissue invasion and metastasis, and 4) sustained angiogenesis. Among the genes affected by cancer, those encoding ion channels are present. Membrane proteins responsible for signaling within cell and among cells, for coupling of extracellular events with intracellular responses, and for maintaining intracellular ionic homeostasis ion channels contribute to various extents to pathophysiological features of each cancer hallmark. Moreover, tight association of these hallmarks with ion channel dysfunction gives a good reason to classify them as special type of channelopathies, namely oncochannelopathies. Although the relation of cancer hallmarks to ion channel dysfunction differs from classical definition of channelopathies, as disease states causally linked with inherited mutations of ion channel genes that alter channel's biophysical properties, in a broader context of the disease state, to which pathogenesis ion channels essentially contribute, such classification seems absolutely appropriate. In this review the authors provide arguments to substantiate such point of view.
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Duranti, C., Iorio, J., Manganelli, V., Bagni, G., Colasurdo, R., Lottini, T., Martinelli, M., Capitani, C., Boso, G., D’Alessandro, F. N., et al. (2025) · Cell Death Discovery · doi:10.1038/s41420-025-02321-2 · Cited by 8
“The functional interaction between ion channels and the lipid component of the plasma membrane may offer a novel perspective in the comprehension of the pathophysiology of cancer [32, 33], where ion channel de-regulation represents one of the hallmarks [34].”
Targeting Dysregulated Ion Channels in Liver Tumors with Venom Peptides
Achimba, F., Faezov, B., Cohen, B., Dunbrack, R., & Holford, M. (2024) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-23-0256 · Cited by 6
Metadata
- Authors
- Prevarskaya, N., Skryma, R., & Shuba, Y.
- Venue
- Physiological Reviews
- Publisher
- American Physiological Society
- Published
- 2018-04-01
- Volume
- 98
- Issue
- 2
- Pages
- 559-621
- ISSN
- 0031-9333 (ISSN-L)
- 1522-1210
- OpenAlex
- W2785885120
- Cited by
- 484
- References
- 531
- FWCI
- 3.62
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
