miRNA/mRNA co-profiling identifies the miR-200 family as a central regulator of SMC quiescence.

miRNAs are versatile regulators of smooth muscle cell (SMC) fate and behavior in vascular development and disease. Targeted loss-of-function studies have established the relevance of specific miRNAs in controlling SMC differentiation or mediating phenotypic modulation. Our goal was to characterize SMC miRNAome and its contribution to transcriptome changes during phenotypic modulation. Small RNA sequencing revealed that dedifferentiation led to the differential expression of over 50 miRNAs in cultured SMC. miRNA/mRNA comparison predicted that over a third of SMC transcript expression was regulated by differentially expressed miRNAs. Our screen identified the miR-200 cluster as highly downregulated during dedifferentiation. miR-200 maintains SMC quiescence and represses proliferation, migration, and neointima formation, in part by targeting Quaking, a central SMC phenotypic switching mediator. Our study unraveled the substantial contribution of miRNAs in regulating the SMC transcriptome and identified the miR-200 cluster as a pro-quiescence mechanism and a potential inhibitor of vascular restenosis.

Factors Associated with Heritable Pulmonary Arterial Hypertension Exert Convergent Actions on the miR-130/301-Vascular Matrix Feedback Loop.

Pulmonary arterial hypertension (PAH) is characterized by occlusion of lung arterioles, leading to marked increases in pulmonary vascular resistance. Although heritable forms of PAH are known to be driven by genetic mutations that share some commonality of function, the extent to which these effectors converge to regulate shared processes in this disease is unknown. We have causally connected extracellular matrix (ECM) remodeling and mechanotransduction to the miR-130/301 family in a feedback loop that drives vascular activation and downstream PAH. However, the molecular interconnections between factors genetically associated with PAH and this mechano-driven feedback loop remain undefined. We performed systematic manipulation of matrix stiffness, the miR-130/301 family, and factors genetically associated with PAH in primary human pulmonary arterial cells and assessed downstream and reciprocal consequences on their expression. We found that a network of factors linked to heritable PAH converges upon the matrix stiffening-miR-130/301-PPARγ-LRP8 axis in order to remodel the ECM. Furthermore, we leveraged a computational network biology approach to predict a number of additional molecular circuits functionally linking this axis to the ECM. These results demonstrate that multiple genes associated with heritable PAH converge to control the miR-130/301 circuit, triggering a self-amplifying feedback process central to pulmonary vascular stiffening and disease.

How can we improve Science, Technology, Engineering, and Math education to encourage careers in Biomedical and Pathology Informatics?

The Computer Science, Biology, and Biomedical Informatics (CoSBBI) program was initiated in 2011 to expose the critical role of informatics in biomedicine to talented high school students.[1] By involving them in Science, Technology, Engineering, and Math (STEM) training at the high school level and providing mentorship and research opportunities throughout the formative years of their education, CoSBBI creates a research infrastructure designed to develop young informaticians. Our central premise is that the trajectory necessary to be an expert in the emerging fields of biomedical informatics and pathology informatics requires accelerated learning at an early age.In our 4(th) year of CoSBBI as a part of the University of Pittsburgh Cancer Institute (UPCI) Academy (http://www.upci.upmc.edu/summeracademy/), and our 2nd year of CoSBBI as an independent informatics-based academy, we enhanced our classroom curriculum, added hands-on computer science instruction, and expanded research projects to include clinical informatics. We also conducted a qualitative evaluation of the program to identify areas that need improvement in order to achieve our goal of creating a pipeline of exceptionally well-trained applicants for both the disciplines of pathology informatics and biomedical informatics in the era of big data and personalized medicine.