No abstract

Metastatic progression is mediated by complex interactions between deregulated extracellular matrix (ECM) and cancer cells and remains a major challenge in cancer management. To investigate the role of ECM dynamics in promoting metastasis development, we developed an artificial microenvironment (AME) platform comprised of nanodot arrays of increasing diameter. Cells cultured on the platform showed increasing signs of mesenchymallike cell transition as AME diameter increased, suggesting accurate simulation of ECM-mediated gene regulation. Gene expression was analyzed to determine genes significant to transition, which were then used to select appropriate small molecule drugs for time course treatments. Our results suggest that the platform can identify critical target genes as well as possible drug candidates. Overall, the AME platform allows for the study of intricate ECM-induced gene expression trends across metastasis development that would otherwise be difficult to visualize in vivo and may open new avenues toward successful personalized cancer management.

Sudden cardiac death (SCD) is an important cause of mortality worldwide. It accounts for approximately half of all deaths from cardiovascular disease. While coronary artery disease and acute myocardial infarction account for the majority of SCD in the elderly population, inherited cardiac diseases (inherited CDs) comprise a substantial proportion of younger SCD victims with a significant genetic component. Currently, the use of next-generation sequencing enables the rapid analysis to investigate relationships between genetic variants and inherited CDs causing SCD. Genetic contribution to risk has been considered an alternate predictor of SCD. In the past years, large numbers of SCD susceptibility variants were reported, but these results are scattered in numerous publications. Here, we present the SCD-associated Variants Annotation Database (SVAD) to facilitate the interpretation of variants and to meet the needs of data integration. SVAD contains data from a broad screening of scientific literature. It was constructed to provide a comprehensive collection of genetic variants along with integrated information regarding their effects. At present, SVAD has accumulated 2,292 entries within 1,239 variants by manually surveying pertinent literature, and approximately one-third of the collected variants are pathogenic/likely-pathogenic following the ACMG guidelines. To the best of our knowledge, SVAD is the most comprehensive database that can provide integrated information on the associated variants in various types of inherited CDs. SVAD represents a valuable source of variant information based on scientific literature and benefits clinicians and researchers, and it is now available on http:// svad.mbc.nctu.edu.tw/.