Conclusion
These data provide strong support for the human tissue-based and bioinformatics approaches adopted to identify critical transcriptional nodes associated with the key pathogenic cell responsible for fibrogenesis in situ and further identify the TSC2/RHEB axis as a potential novel target for interfering with excessive matrix deposition in IPF and other fibrotic conditions.
Methods
The challenges associated with deriving gene calls from low amounts of RNA and the absence of a meaningful comparator cell type were overcome by adopting novel data mining strategies and by using weighted gene co-expression network analysis (WGCNA), as well as an eigengene-based approach to identify transcriptional signatures, which correlate with fibrillar collagen gene expression.
Results
WGCNA identified prominent clusters of genes associated with cell cycle, inflammation/differentiation, translation and cytoskeleton/cell adhesion. Collagen eigengene analysis revealed that transforming growth factor β1 (TGF-β1), RhoA kinase and the TSC2/RHEB axis formed major signalling clusters associated with collagen gene expression. Functional studies using CRISPR-Cas9 gene-edited cells demonstrated a key role for the TSC2/RHEB axis in regulating TGF-β1-induced mechanistic target of rapamycin complex 1 activation and collagen I deposition in mesenchymal cells reflecting IPF and other disease settings, including cancer-associated fibroblasts.