Comprehensive bioinformatic analyses identify a PANoptosome-related gene diagnostic signature in keloid fibroblasts.

Abstract

Keloid (KD) is a fibroproliferative disorder, the formation of which is not only related to abnormal cell proliferation, but also to apoptosis. PANoptosis is a process of molecular interaction among pyroptosis, apoptosis and necroptosis. This study was aimed to explore the molecular markers related to PANoptosis in KD fibroblasts. Five KD-related datasets were downloaded from Gene Expression Omnibus. KD-related differentially expressed genes (DEGs) were identified and PANoptosis-related genes (PARGs) were obtained from the literature. The overlapping genes (DE-PARGs) were screened. WGCNA was used to identify modules related to KD, and intersected with DE-PARGs. Then, PARGS-related signature genes were screened by machine learning method, and the diagnosis model was constructed. The potential biological function, immune cell infiltration, and drug action relationship were explored. In total, 39 DE-PARGs were obtained, and then 22 KD-related DE-PARGs were selected following WGCNA. The 22 genes were involved in some apoptotic processes and pathways, as well as several signal pathways, such as NF-kappa B signaling pathway, p53 signaling pathway, and FoxO signaling pathway. Five signature genes (PLK1, PMAIP1, BMF, BCAP31 and GCH1) were selected for diagnostic model construction. Additionally, 7 immune cell types were found to have significant difference distribution between groups, among which activated CD4 T cell was the most positively correlated with PMAIP1, and immature dendritic cell was the most negatively correlated with BCAP31. Two drug molecules (resveratrol and quercetin) were identified to be associated with KD. The established PANoptosis-related diagnostic model may have a good ability for KD diagnosis.