Increasing evidence suggests that caveolin-1 and large conductance Ca2+-activated potassium (BKCa) channels are implicated in the carcinogenesis processes, including cell proliferation and invasion. These two proteins have been proven to interact with each other in vascular endothelial and smooth muscle cells and modulate vascular contractility. In this study, we investigated the probable interaction between caveolin-1 and BKCa in MCF-7 breast cancer cells. We identified that caveolin-1 and BKCa were co-localized and could be reciprocally co-immunoprecipitated in human breast cancer MCF-7 cells. siRNA mediated caveolin-1 knockdown resulted in activation and increased surface expression of BKCa channel, and subsequently promoted the proliferation and invasiveness of breast cancer cells. These effects were attenuated in the presence of BKCa-siRNA. Conversely, up-regulated caveolin-1 suppressed function and surface expression of BKCa channel and exerted negative effects on breast cancer cell proliferation and invasion. Similarly, these opposing effects were abrogated by BKCa up-regulation. Collectively, our findings suggest that BKCa is a critical target for suppression by caveolin-1 in suppressing proliferation and invasion of breast cancer cells. The functional complex of caveolin-1 and BKCa in the membrane microdomain may be served as a potential therapeutic target in breast cancer.
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Journal of Visualized Experiments
What is Visualize?
JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.
How does it work?
We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.
Video X seems to be unrelated to Abstract Y...
In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.