ReviewCancers2022
Potassium Ion Channels in Malignant Central Nervous System Cancers.
Review in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 15 citations in OpenAlex.
- The Kv10.1 potassium channel, driver of hypoxia-induced EMT and breast cancer cell aggressiveness.Cancer cell international · 2025Article
- Sensitive red fluorescent indicators for real-time visualization of potassium ion dynamics in vivo.PLoS biology · 2025Article
- Cell Settling, Migration, and Stochastic Cancer Gene Expression Suggest Potassium Membrane Flux May Initiate pH Reversal.Biomolecules · 2025Article
- Evolution of Bioelectric Membrane Potentials: Implications in Cancer Pathogenesis and Therapeutic Strategies.The Journal of membrane biology · 2024Review
- Advancements in Targeting Ion Channels for the Treatment of Neurodegenerative Diseases.Pharmaceuticals (Basel, Switzerland) · 2024Review
- Loss of the large conductance calcium-activated potassium channel causes an increase in mitochondrial reactive oxygen species in glioblastoma cells.Pflugers Archiv : European journal of physiology · 2023Article
- Recent Advances in Computer-Aided Structure-Based Drug Design on Ion Channels.International journal of molecular sciences · 2023Review
- Potassium Ion Channels in Glioma: From Basic Knowledge into Therapeutic Applications.Membranes · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Malignant central nervous system (CNS) cancers are among the most difficult to treat, with low rates of survival and a high likelihood of recurrence. This is primarily due to their location within the CNS, hindering adequate drug delivery and tumour access via surgery. Furthermore, CNS cancer cells are highly plastic, an adaptive property that enables them to bypass targeted treatment strategies and develop drug resistance. Potassium ion channels have long been implicated in the progression of many cancers due to their integral role in several hallmarks of the disease. Here, we will explore this relationship further, with a focus on malignant CNS cancers, including high-grade glioma (HGG). HGG is the most lethal form of primary brain tumour in adults, with the majority of patient mortality attributed to drug-resistant secondary tumours. Hence, targeting proteins that are integral to cellular plasticity could reduce tumour recurrence, improving survival. This review summarises the role of potassium ion channels in malignant CNS cancers, specifically how they contribute to proliferation, invasion, metastasis, angiogenesis, and plasticity. We will also explore how specific modulation of these proteins may provide a novel way to overcome drug resistance and improve patient outcomes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.