Description
Signalling pathways regulate all major cellular events in health and disease, including asthma development and progression. Complexity of human intracellular signalization can be explored using novel systemic approaches that exploit whole-transcriptome analysis. Cap-analysis-of-gene-expression (CAGE) is a method of choice for generating transcriptome libraries, as it interrogates only terminally capped mRNAs that have the highest probability to be translated into protein. In this study we for the first time systematically profiled differentially activated Intracellular Signalling Pathways (ISPs) in cultured primary human airway smooth muscle (ASM) cells from asthmatic (n=8) and non-asthmatic (n=6) subjects in a high-throughput assay, highlighting asthma-specific co-regulatory patterns. CAGE-libraries from primary human ASM cells were subject to massive parallel next generation sequencing, and a comprehensive analysis of ISP activation was performed using a recently developed technique OncoFinder. Analysis of 270 ISPs led to discovery of multiple pathways clearly distinguishing asthmatic from normal cells. In particular, we found 146 (p<0.05) and 103 (p<0.01) signalling pathways differentially active in asthmatic vs non-asthmatic samples. We identified seven clusters of coherently acting pathways functionally related to the disease. Pathways down-regulated in asthma mostly represented cell death-promoting pathways, whereas the up-regulated ones were mainly involved in cell growth and proliferation, inflammatory response and some specific reactions, including smooth muscle contraction and hypoxia - related signalization. Most of interactions uncovered in this study were not previously associated with asthma, suggesting that these results may be pivotal to development of novel therapeutic strategies that specifically address the ISP signature linked with asthma pathophysiology. Overall design: Capped mRNA profiles of primary bronchial smooth muscle cells from 8 asthmatic and 6 healthy donors were generated by deep sequencing using Illumina HiSeq1500.