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      Therapeutic potential for phenytoin: targeting Na v1.5 sodium channels to reduce migration and invasion in metastatic breast cancer

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          Abstract

          Voltage-gated Na + channels (VGSCs) are heteromeric membrane protein complexes containing pore-forming α subunits and smaller, non-pore-forming β subunits. VGSCs are classically expressed in excitable cells, including neurons and muscle cells, where they mediate action potential firing, neurite outgrowth, pathfinding, and migration. VGSCs are also expressed in metastatic cells from a number of cancers. The Na v1.5 α subunit (encoded by SCN5A) is expressed in breast cancer (BCa) cell lines, where it enhances migration and invasion. We studied the expression of SCN5A in BCa array data, and tested the effect of the VGSC-blocking anticonvulsant phenytoin (5,5-diphenylhydantoin) on Na + current, migration, and invasion in BCa cells. SCN5A was up-regulated in BCa samples in several datasets, and was more highly expressed in samples from patients who had a recurrence, metastasis, or died within 5 years. SCN5A was also overexpressed as an outlier in a subset of samples, and associated with increased odds of developing metastasis. Phenytoin inhibited transient and persistent Na + current recorded from strongly metastatic MDA-MB-231 cells, and this effect was more potent at depolarized holding voltages. It may thus be an effective VGSC-blocking drug in cancer cells, which typically have depolarized membrane potentials. At a concentration within the therapeutic range used to treat epilepsy, phenytoin significantly inhibited the migration and invasion of MDA-MB-231 cells, but had no effect on weakly metastatic MCF-7 cells, which do not express Na + currents. We conclude that phenytoin suppresses Na + current in VGSC-expressing metastatic BCa cells, thus inhibiting VGSC-dependent migration and invasion. Together, our data support the hypothesis that SCN5A is up-regulated in BCa, favoring an invasive/metastatic phenotype. We therefore propose that repurposing existing VGSC-blocking therapeutic drugs should be further investigated as a potential new strategy to improve patient outcomes in metastatic BCa.

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          Most cited references60

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          Oncogenic pathway signatures in human cancers as a guide to targeted therapies.

          The development of an oncogenic state is a complex process involving the accumulation of multiple independent mutations that lead to deregulation of cell signalling pathways central to the control of cell growth and cell fate. The ability to define cancer subtypes, recurrence of disease and response to specific therapies using DNA microarray-based gene expression signatures has been demonstrated in multiple studies. Various studies have also demonstrated the potential for using gene expression profiles for the analysis of oncogenic pathways. Here we show that gene expression signatures can be identified that reflect the activation status of several oncogenic pathways. When evaluated in several large collections of human cancers, these gene expression signatures identify patterns of pathway deregulation in tumours and clinically relevant associations with disease outcomes. Combining signature-based predictions across several pathways identifies coordinated patterns of pathway deregulation that distinguish between specific cancers and tumour subtypes. Clustering tumours based on pathway signatures further defines prognosis in respective patient subsets, demonstrating that patterns of oncogenic pathway deregulation underlie the development of the oncogenic phenotype and reflect the biology and outcome of specific cancers. Predictions of pathway deregulation in cancer cell lines are also shown to predict the sensitivity to therapeutic agents that target components of the pathway. Linking pathway deregulation with sensitivity to therapeutics that target components of the pathway provides an opportunity to make use of these oncogenic pathway signatures to guide the use of targeted therapeutics.
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            Stromal gene expression predicts clinical outcome in breast cancer.

            Although it is increasingly evident that cancer is influenced by signals emanating from tumor stroma, little is known regarding how changes in stromal gene expression affect epithelial tumor progression. We used laser capture microdissection to compare gene expression profiles of tumor stroma from 53 primary breast tumors and derived signatures strongly associated with clinical outcome. We present a new stroma-derived prognostic predictor (SDPP) that stratifies disease outcome independently of standard clinical prognostic factors and published expression-based predictors. The SDPP predicts outcome in several published whole tumor-derived expression data sets, identifies poor-outcome individuals from multiple clinical subtypes, including lymph node-negative tumors, and shows increased accuracy with respect to previously published predictors, especially for HER2-positive tumors. Prognostic power increases substantially when the predictor is combined with existing outcome predictors. Genes represented in the SDPP reveal the strong prognostic capacity of differential immune responses as well as angiogenic and hypoxic responses, highlighting the importance of stromal biology in tumor progression.
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              Strong Time Dependence of the 76-Gene Prognostic Signature for Node-Negative Breast Cancer Patients in the TRANSBIG Multicenter Independent Validation Series

              Recently, a 76-gene prognostic signature able to predict distant metastases in lymph node-negative (N(-)) breast cancer patients was reported. The aims of this study conducted by TRANSBIG were to independently validate these results and to compare the outcome with clinical risk assessment. Gene expression profiling of frozen samples from 198 N(-) systemically untreated patients was done at the Bordet Institute, blinded to clinical data and independent of Veridex. Genomic risk was defined by Veridex, blinded to clinical data. Survival analyses, done by an independent statistician, were done with the genomic risk and adjusted for the clinical risk, defined by Adjuvant! Online. The actual 5- and 10-year time to distant metastasis were 98% (88-100%) and 94% (83-98%), respectively, for the good profile group and 76% (68-82%) and 73% (65-79%), respectively, for the poor profile group. The actual 5- and 10-year overall survival were 98% (88-100%) and 87% (73-94%), respectively, for the good profile group and 84% (77-89%) and 72% (63-78%), respectively, for the poor profile group. We observed a strong time dependence of this signature, leading to an adjusted hazard ratio of 13.58 (1.85-99.63) and 8.20 (1.10-60.90) at 5 years and 5.11 (1.57-16.67) and 2.55 (1.07-6.10) at 10 years for time to distant metastasis and overall survival, respectively. This independent validation confirmed the performance of the 76-gene signature and adds to the growing evidence that gene expression signatures are of clinical relevance, especially for identifying patients at high risk of early distant metastases.
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                Author and article information

                Contributors
                +44-1904-328284 , +44-1904-328505 , william.brackenbury@york.ac.uk
                Journal
                Breast Cancer Res Treat
                Breast Cancer Res. Treat
                Breast Cancer Research and Treatment
                Springer US (Boston )
                0167-6806
                1573-7217
                8 June 2012
                8 June 2012
                July 2012
                : 134
                : 2
                : 603-615
                Affiliations
                [1 ]Department of Biology, University of York, Heslington, York, YO10 5DD UK
                [2 ]Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI 48109-5632 USA
                Article
                2102
                10.1007/s10549-012-2102-9
                3401508
                22678159
                83785477-182c-4418-b88a-f7f2b291c627
                © The Author(s) 2012
                History
                : 21 October 2011
                : 16 May 2012
                Categories
                Preclinical Study
                Custom metadata
                © Springer Science+Business Media, LLC. 2012

                Oncology & Radiotherapy
                phenytoin,invasion,metastasis,electrophysiology,migration,voltage-gated na+ channel

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