Infantile hemangioma (IH) is the most common vascular tumor among infants and children. However, the understanding of pathogenesis about IH has not been fully elucidated, and the potential diagnostic maker remains further explored. In this study, we aimed to find miRNAs as potential biomarkers of IH through bioinformatic analysis. The microarray datasets GSE69136, GSE100682 were downloaded from the GEO database. The co-expressed differential miRNAs were identified by analyzing these two datasets. The downstream common target genes were predicted by the ENCORI, Mirgene, miRWalk, and Targetscan databases. GO annotation and KEGG pathway enrichment analysis for target genes were performed. The STRING database and Cytoscape software were used to construct the protein-protein interaction network and screen hub genes. Then potential diagnostic markers for IH were further screened and identified by using Receiver operating characteristic curve analysis. A total of thirteen co-expressed up-regulated miRNAs were screened out in the above two datasets, and 778 down-regulated target genes were then predicted. GO annotation and KEGG pathway enrichment analysis indicated that the common target genes strongly correlated with IH. Through the DEM-hub gene network construction, six miRNAs associated with the hub genes were identified. Finally, has-miR-522-3p, has-miR-512-3p, has-miR-520a-5p with high diagnostic values were screened out by receiver operating characteristic analysis. In the study, the potential miRNA-mRNA regulatory network was firstly constructed in IH. And, the three miRNAs might be used as potential biomarkers for IH, which also provided novel strategies for the therapeutic intervention of IH.

Background. Pigmented villous nodular synovitis (PVNS) is a tumor-like proliferative disease characterized by impairment of daily activities, decreased quality of life, and a high recurrence rate. However, the specific pathological mechanisms are still ill-defined and controversial. The purpose of this study was to define potential diagnostic markers and evaluate immune cell infiltration in the pathogenesis of PVNS. Method. The expression profile of GSE3698 was reanalyzed in the Gene Expression Omnibus (GEO) database. First, differentially expressed genes (DEGs) were identified using the R package “limma” and analyzed by Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Next, the DEGs were imported into the STRING database and Cytoscape to construct a protein–protein interaction (PPI) network. Then, cytoHubba and ROC curve analyses were used to determine potential diagnostic biomarkers of PVNS. Finally, we used CIBERSORT to estimate the proportions of 22 immune cell subtypes in PVNS and analyzed the correlation between diagnostic markers and infiltrating immune cells. Result. We found 139 DEGs (including 93 upregulated genes and 46 downregulated genes). TYROBP, FCER1G, LAPTM5, and HLA-DPB1 were identified as potential diagnostic biomarkers of PVNS. Immune cell infiltration analysis indicated that neutrophils and M2 macrophages might be associated with the genesis and progression of PVNS. Furthermore, our correlation analysis of diagnostic markers and infiltrating immune cells found that TYROBP, FCER1G, LAPTM5, and HLA-DPB1 were positively correlated with M2 macrophage infiltration and that neutrophils, TYROBP, FCER1G, and LAPTM5 were negatively correlated with plasma cell infiltration. Conclusions. We identified TYROBP, FCER1G, LAPTM5, and HLA-DPB1 as potential diagnostic markers for PVNS and concluded that immune cell infiltration plays an important role in the genesis and progression of PVNS.

Osteonecrosis of the femoral head (ONFH) is a multifactorial disease leading to severely limited function. By far, the etiology and pathogenesis of ONFH are not fully understood, and surgery is the only effective way to treat ONFH. This study aims to identify hub genes and therapeutic drugs in ONFH. Two gene expression profiles were downloaded from the gene expression omnibus database, and the hub genes and candidate drugs for ONFH were identified through integrated bioinformatics analysis and cross-validated by literature mining. A total of 159 DEGs were identified. PTGS2, LRRK2, ANXA5, IGF1R, MCL1, TIMP2, LYN, CD68, CBL, and RUNX2 were validated as 10 hub genes, which has considerable implications for future genetic research and related research fields of ONFH. Our findings indicate that 85 drugs interact with ONFH, with most drugs exhibiting a positive impact on ONFH by promoting osteogenesis and angiogenesis or inhibiting microcirculation embolism, rather than being anti-inflammatory. Our study provides novel insights into the pathogenesis, prevention, and treatment of ONFH.