Background: Fibrosis in most organs has proven to be an critical factor related to high risk of morbidity and mortality, but an adequate assessment of fibrosis severity is still challenging. This study tried to evaluate fibrosis severity through a fibrosis transcriptional signature.
Methods: A fibrosis transcriptional signature was developed through an integrated analysis of multiple expression profiling datasets of human organs with fibrosis-related diseases. A fibrosis severity score for each sample was the calculated through gene set variation analysis (GSVA), and its role in evaluating fibrosis severity was then analyzed.
Results: Ten expression profiling datasets of human tissues with organ failure were integrated with robust rank aggregation method, and a fibrosis severity score consisting of 149 genes. Most of those included genes were involved in fibrogenic pathways. GSEA analysis revealed that fibrosis transcriptional signature was significantly enriched in the fibrogenic tissues. Additionally, we found that fibrosis transcriptional signature could effectively differentiate fibrosis tissues and non-fibrosis tissues.
Conclusion: This study developed an useful fibrosis transcriptional signature involved in fibrosis-related diseases. This fibrosis transcriptional signature is helpful in precisely evaluating the fibrosis severity in common organs at the transcriptional level.