The pathophysiology of keloid formation is not yet understood, so the identification of biomarkers for kelod can be one step towards designing new targeting therapies which will improve outcomes for patients with keloids or at risk of developing keloids.
In this study, we performed single-cell RNA sequencing analysis, weighted co-expression network analysis, and differential expression analysis of keloids based on public databases. And 3 RNA sequencing data from keloid patients in our center were used for validation. Besides, we performed QRT-PCR on keloid tissue and adjacent normal tissues from 16 patients for further verification.
We identified the sensitive biomarker of keloid: Tenascin-C (TNC). Then, Pseudotime analysis found that the expression level of TNC decreased first, then stabilized and finally increased with fibroblast differentiation, suggesting that TNC may play an potential role in fibroblast differentiation. In addition, there were differences in the infiltration level of macrophages M0 between the TNC-high group and the TNC-low group. Macrophages M0 had a higher infiltration level in low TNC- group (P<0.05).
Our results can provide a new idea for the diagnosis and treatment of keloid.