The Function of Cortactin in the Clustering of Acetylcholine Receptors at the Vertebrate Neuromuscular Junction

Background: Postsynaptic enrichment of acetylcholine receptors (AChRs) at the vertebrate neuromuscular junction (NMJ) depends on the activation of the muscle receptor tyrosine MuSK by neural agrin. Agrin-stimulation of MuSK is known to initiate an intracellular signaling cascade that leads to the clustering of AChRs in an actin polymerization-dependent manner, but the molecular steps which link MuSK activation to AChR aggregation remain incompletely defined. Methodology/Principal Findings: In this study we used biochemical, cell biological and molecular assays to investigate a possible role in AChR clustering of cortactin, a protein which is a tyrosine kinase substrate and a regulator of F-actin assembly and which has also been previously localized at AChR clustering sites. We report that cortactin was co-enriched at AChR clusters in situ with its target the Arp2/3 complex, which is a key stimulator of actin polymerization in cells. Cortactin was further preferentially tyrosine phosphorylated at AChR clustering sites and treatment of myotubes with agrin significantly enhanced the tyrosine phosphorylation of cortactin. Importantly, forced expression in myotubes of a tyrosine phosphorylation-defective cortactin mutant (but not wild-type cortactin) suppressed agrin-dependent AChR clustering, as did the reduction of endogenous cortactin levels using RNA interference, and introduction of the mutant cortactin into muscle cells potently inhibited synaptic AChR aggregation in response to innervation. Conclusion: Our results suggest a novel function of phosphorylation-dependent cortactin signaling downstream fro

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases