Background: Gene expression signatures for the prediction of differential survival of patients undergoing anti-cancer therapies are of great interest because they can be used to prospectively stratify patients entering new clinical trials, or to determine optimal treatment for patients in more routine clinical settings. Unlike prognostic signatures however, predictive signatures require training set data from clinical studies with at least two treatment arms. As two-arm studies with gene expression profiling have been rarer than similar one-arm studies, the methodology for constructing and optimizing predictive signatures has been less prominently explored than for prognostic signatures.
View Article and Find Full Text PDFBackground: Huntington Disease (HD) is an incurable autosomal dominant neurodegenerative disorder driven by an expansion repeat giving rise to the mutant huntingtin protein (mHtt), which is known to disrupt a multitude of transcriptional pathways. Pridopidine, a small molecule in development for treatment of HD, has been shown to improve motor symptoms in HD patients. In HD animal models, pridopidine exerts neuroprotective effects and improves behavioral and motor functions.
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