MicroRNA-regulated network promotes pulmonary hypertension

MicroRNA-regulated network promotes pulmonary hypertension


MicroRNA-regulated network promotes pulmonary hypertension

Pulmonary hypertension is a complex disease that affects multiple vascular cell types, and mircoRNAs (miRNAs) have been implicated in the pathogenesis of this condition. In this episode, Stephen Chan discusses how his group used network theory to identify miRNA-130/301 as a regulator of a system of miRNAs that promote the development of pulmonary hypertension. Furthermore, inhibition of miR130/301 prevented the development on pulmonary hypertension in a hypoxic murine model. The results of this study support the use of network analysis for identifying complex miRNA-regulated pathways involved in disease manifestations.


Content

7.436 -> Stephen Chan: Hello, my name is Stephen Chan.  I'm an assistant professor of medicine at Harvard  
12.72 -> Medical School at the Brigham and Women's Hospital  in Boston, Massachusetts. Today, I'm happy to be  
18.48 -> discussing our laboratory's recent findings of  microRNAs that can act as systems-level regulators  
24.88 -> in the pathogenesis of pulmonary hypertension,  or PH. As many of you know, PH refers to a group  
31.76 -> of pulmonary vascular diseases that can cause  increased pulmonary pressure, right heart failure,  
37.52 -> and often death, but the molecular origins of this  disease remain enigmatic. Over the past decade,  
44.48 -> multitudes of newly identified molecules and  pathways have been implicated in PH, but it  
50.88 -> has been challenging to understand the integrated  effects of all of these factors on overall disease  
56.96 -> manifestation. microRNAs have been proposed  as important factors in this pathogenesis.  
64.4 -> These are small, noncoding RNA molecules that  negatively regulate gene expression by binding  
70.48 -> specific sequences in messenger RNA, in order  to cause translational repression and/or mRNA  
76.64 -> degradation. Recently, we proposed that  microRNAs may serve as good candidates  
82.56 -> that exert hierarchical regulation  of these complex molecular networks,  
87.6 -> given their inherent pleiotrophy of repressing  several messenger transcripts simultaneously.  
94.08 -> However, there are challenges of  studying such complex microRNA biology  
98.64 -> using traditional scientific approaches, and  so we have attempted to address these obstacles  
104 -> by the application of computational network theory  to hone our hypotheses. However, to date, relevant  
111.04 -> high-throughput data in PH has been limited, and  analysis of systems-level regulation of microRNA  
117.6 -> networks in general has consisted mostly of  computational theories without experimental data. 
123.52 -> SC: So the central objective of this  study was to design a strategy combining  
129.2 -> computational analysis of PH disease gene network  architecture with experimental validation that  
136.32 -> accurately identifies microRNAs exerting  systems-level control of pulmonary hypertension.  
142.96 -> To do so, we leveraged a simple concept:  that often microRNAs tend to regulate  
148.16 -> multiple targets in the same functional pathway or  network. We first wanted to determine whether such  
154 -> a network relevant to pulmonary hypertension could  be constructed from available molecular maps.  
159.84 -> To do so, we curated 115 seed genes known to be  important in PH from the scientific literature.  
167.2 -> We then mapped the functional interactions among  these genes using a consolidated set of databases  
173.04 -> that represent all functional interactions among  the human transcriptome and proteome. We then  
179.28 -> expanded the network to include genes that were  not mentioned in the PH-relevant literature but  
184.64 -> were known to interact closely with a number of  our curated PH genes by our network analysis.  
191.28 -> The end product was a single encapsulated  largest connected component carrying  
195.92 -> 249 genes and over 2,000 interconnections. SC: We then use this PH network as a platform,  
203.36 -> coupled with a well-validated microRNA target  prediction algorithm, called target scan, in order  
209.44 -> to identify those microRNAs that have the broadest  influence throughout the entire PH network.  
215.84 -> To do so, we ranked microRNAs based not only  on the number of predicted targets they had  
221.04 -> within the network but also how well distributed  those targets were throughout the network itself.  
227.28 -> Based on this metric, we predicted  the microRNA-130 and -301 family  
232.4 -> to be the most influential set of microRNAs in the  context of PH in this regard. This is a family of  
239.84 -> 4 microRNAs that share the same seed sequence and  thus presumably regulate the same broad cohort  
245.92 -> of PH-relevant target genes. We then performed  a similar set of analyses on the targets of the  
252.56 -> miR-130 and -301 family as well as on their  closest interactors within the PH network,  
258.48 -> in order to determine which of the microRNA family  targets and downstream pathways were the most  
264.8 -> influential in disease. In this way, we uncovered  an intricate network of subordinate microRNA  
271.44 -> activity spearheaded by the miR-130 target  PPAR-gamma, which can regulate miR-424 and -503  
279.12 -> in pulmonary arterial endothelial cells as well as  miR-204 in pulmonary arterial smooth muscle cells. 
286.08 -> SC: These findings suggested to us that the  miR-130/301 family serves as a regulator of  
292.88 -> both of these pathways orchestrating a global  proliferative response throughout the vasculature,  
298.48 -> ultimately culminating in pulmonary hypertension.  Importantly, this process of model building was  
304.8 -> implemented entirely in silico, and while some  of these individual regulatory relationships  
310.96 -> had been previously validated, the notion that  they are united by a single global regulatory  
316.96 -> factor is a novel one and would have been  very difficult to uncover without the aid  
321.52 -> of computational analyses such as these. SC: We then wanted to determine and validate  
327.36 -> this model experimentally. First, in cultured  pulmonary endothelial and smooth muscle cells,  
333.68 -> we used a comprehensive set of gain of  function and loss, loss-of-function approaches  
338.32 -> to manipulate miR-130 and -301, as well as  their downstream effectors, in order to prove  
344.08 -> their pro-proliferative actions via regulation of  miR-424, -503, and miR-204. Second, we examined a  
352.24 -> broad spectrum of disease models of PH spanning  seven different models in rodents and sheep, as  
358.48 -> well as three different subtypes of human disease.  In all cases, we found a coordinated upregulation  
364.72 -> of all miR-130/301 family members, particularly in  remodeled pulmonary vessels. Third, we identified  
372.56 -> multiple triggers of PH as key regulators  of this microRNA family including hypoxia  
378.72 -> inflammatory cytokines and a subset of factors  known to be genetically associated with human PH.  
385.28 -> Finally, by pharmacologic manipulation of this  microRNA family in the pulmonary vasculature of  
391.68 -> mice, we found miR-130 and -301 to be both  necessary and sufficient for hemodynamic  
398.48 -> and histologic manifestations of PH in vivo. SC: In conclusion, we believe that this is the  
404.88 -> first description of a single microRNA family  regulating a hierarchy of subordinate microRNAs  
411.44 -> with systems-level yet cell type–specific  effects in PH. We believe that deciphering  
417.2 -> such systems-level relationships should guide  the development of more effective and perhaps  
423.04 -> more potent clinical management strategies in  pulmonary hypertension. Perhaps more importantly,  
428.8 -> our findings provide critical validation for  the evolving application of network theory  
434.24 -> to the discovery of microRNA-based origins of  pulmonary hypertension, and we hope this work can  
440.4 -> serve as a basis for the search in separate human  diseases for other microRNA master regulators  
447.28 -> that are otherwise hidden in the architecture  of existing network databases. Thank you very  
452.96 -> much for your interest, and on behalf of all of  the authors I hope you enjoy reading our work.

Source: https://www.youtube.com/watch?v=EFNIfZtrN-w