Conclusion
In our study, we demonstrated that Tpt1, Mmp9 and Fth1 have great potential to be biomarker of SIC. These findings will facilitated to understand the occurrence and development mechanism of SIC.
Methods
The transcriptomic dataset, GSE171564, was downloaded from NCBI for further analysis. Gene expression matrices for the sample group were obtained by quartile standardization and log2 logarithm conversion prior to analysis. The time series, protein-protein interaction (PPI) network, and functional enrichment analysis via Gene Ontology and KEGG Pathway Databases were used to identify key gene clusters and their potential interactions. Predicted miRNA-mRNA relationships from multiple databases facilitated the construction of a TF-miRNA-mRNA regulatory network. In vivo experiments, along with qPCR and western blot assays, provided experimental validation.
Results
The transcriptome data analysis between SIC and healthy samples revealed 221 down-regulated, and 342 up-regulated expressed genes across two distinct clusters. Among these, Tpt1, Mmp9 and Fth1 were of particular significance. Functional analysis revealed their role in several biological processes and pathways, subsequently, in vivo experiments confirmed their overexpression in SIC samples. Notably, we found TPT1 play a pivotal role in the progression of SIC, and silencing TPT1 showed a protective effect against LPS-induced SIC.