Cancer stem cells (CSCs) are a promising target for cancer therapy, particularly for metastatic lung cancers, but how CSCs are regulated is largely unknown. We identify two proteins, SLUG (encoded by ...SNAI2 gene) and SOX9, which are associated with advanced stage lung cancers and are implicated in the regulation of CSCs. Inhibition of either SLUG or SOX9 sufficiently inhibits CSCs in human lung cancer cells and attenuates experimental lung metastasis in a xenograft mouse model. Correlation between SLUG and SOX9 levels was observed remarkably, we therefore sought to explore their mechanistic relationship and regulation. SLUG, beyond its known function as an epithelial-mesenchymal transition transcription factor, was found to regulate SOX9 by controlling its stability via a post-translational modification process. SLUG interacts directly with SOX9 and prevents it from ubiquitin-mediated proteasomal degradation. SLUG expression and binding are necessary for SOX9 promotion of lung CSCs and metastasis in a mouse model. Together, our findings provide a novel mechanistic insight into the regulation of CSCs via SLUG-SOX9 regulatory axis, which represents a potential novel target for CSC therapy that may overcome cancer chemoresistance and relapse.
Mutations in the SCN5A gene, encoding the α subunit of the Nav1.5 channel, cause a life-threatening form of cardiac arrhythmia, long QT syndrome type 3 (LQT3). Mexiletine, which is structurally ...related to the Na
channel-blocking anesthetic lidocaine, is used to treat LQT3 patients. However, the patient response is variable, depending on the genetic mutation in SCN5A.
The goal of this study is to understand the molecular basis of patients' variable responses and build a predictive statistical model that can be used to personalize mexiletine treatment based on patient's genetic variant.
We monitored the cardiac Na
channel voltage-sensing domain (VSD) conformational dynamics simultaneously with other gating properties for the LQT3 variants. To systematically identify the relationship between mexiletine block and channel biophysical properties, we used a system-based statistical modeling approach to connect the multivariate properties to patient phenotype. We found that mexiletine altered the conformation of the Domain III VSD, which is the same VSD that many tested LQT3 mutations affect. Analysis of 15 LQT3 variants showed a strong correlation between the activation of the Domain III-VSD and the strength of the inhibition of the channel by mexiletine. Based on this improved molecular-level understanding, we generated a systems-based model based on a dataset of 32 LQT3 patients, which then successfully predicted the response of 7 out of 8 patients to mexiletine in a blinded, retrospective trial.
Our results imply that the modulated receptor theory of local anesthetic action, which confines local anesthetic binding effects to the channel pore, should be revised to include drug interaction with the Domain III-VSD. Using an algorithm that incorporates this mode of action, we can predict patient-specific responses to mexiletine, improving therapeutic decision making.
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