Background: Oral cancer (OC) is a common and dangerous malignant tumor with a low survival rate. However, the micro level mechanism has not been explained in detail. Methods: Gene and miRNA expression micro array data were extracted from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) and miRNAs (DE miRNAs) were identified by R software. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of genes and genomes (KEGG) pathway analysis were used to assess the potential molecular mechanisms of DEGs. Cytoscape software was utilized to construct protein–protein interaction (PPI) network and miRNA-gene network. Central genes were screened out with the participation of gene degree, molecular complex detection (MCODE) plugin, and miRNA-gene network. Then, the identified genes were checked by The Cancer Genome Atlas (TCGA) gene expression profile, Kaplan-Meier data, Oncomine, and the Human Protein Atlas database. Receiver operating characteristic (ROC) curve was drawn to predict the diagnostic efficiency of crucial gene level in normal and tumor tissues. Univariate and multivariate Cox regression were used to analyze the effect of dominant genes and clinical characteristics on the overall survival rate of OC patients. Results: Gene expression data of gene expression profiling chip(GSE9844, GSE30784, and GSE74530) were obtained from GEO database, including 199 tumor and 63 non-tumor samples. We identified 298 gene mutations, including 200 upregulated and 98 downregulated genes. GO functional annotation analysis showed that DEGs were enriched in extracellular structure and extracellular matrix containing collagen. In addition, KEGG pathway enrichment analysis demonstrated that the DEGs were significantly enriched in IL-17 signaling pathway and PI3K-Akt signaling pathway. Then, we detected three most relevant modules in PPI network. Central genes (CXCL8, DDX60, EIF2AK2, GBP1, IFI44, IFI44L, IFIT1, IL6, MMP9,CXCL1, CCL20, RSAD2, and RTP4) were screened out with the participation of MCODE plugin, gene degree, and miRNA-gene network. TCGA gene expression profile and Kaplan-Meier analysis showed that high expression of CXCL8, DDX60, IL6, and RTP4 was associated with poor prognosis in OC patients, while patients with high expression of IFI44L and RSAD2 had a better prognosis. The elevated expression of CXCL8, DDX60, IFI44L, RSAD2, and RTP44 in OC was verified by using Oncomine database. ROC curve showed that the mRNA levels of these five genes had a helpful diagnostic effect on tumor tissue. The Human Protein Atlas database showed that the protein expressions of DDX60, IFI44L, RSAD2, and RTP44 in tumor tissues were higher than those in normal tissues. Finally, univariate and multivariate Cox regression showed that DDX60, IFI44L, RSAD2, and RTP44 were independent prognostic indicators of OC. Conclusion: This study revealed the potential biomarkers and relevant pathways of OC from publicly available GEO database, and provided a theoretical basis for elucidating the diagnosis, treatment, and prognosis of OC.

At present, the treatment of esophageal cancer (EC) is mainly surgical and drug treatment. However, due to drug resistance, these therapies can not effectively improve the prognosis of patients with the EC. Therefore, a multigene prognostic risk scoring system was constructed by bioinformatics analysis method to provide a theoretical basis for the prognosis and treatment decision of EC. The gene expression profiles and clinical data of esophageal cancer patients were gathered from the Cancer Genome Atlas TCGA database, and the differentially expressed genes (DEGs) were screened by R software. Genes with prognostic value were screened by Kaplan Meier analysis, followed by functional enrichment analysis. A cox regression model was used to construct the prognostic risk score model of DEGs. ROC curve and survival curve were utilized to evaluate the performance of the model. Univariate and multivariate Cox regression analysis was used to evaluate whether the model has an independent prognostic value. Network tool mirdip was used to find miRNAs that may regulate risk genes, and Cytoscape software was used to construct gene miRNA regulatory network. GSCA platform is used to analyze the relationship between gene expression and drug sensitivity. 41 DEGs related to prognosis were pre-liminarily screened by survival analysis. A prognostic risk scoring model composed of 8 DEGs (APOA2, COX6A2, CLCNKB, BHLHA15, HIST1H1E, FABP3, UBE2C and ERO1B) was built by Cox regression analysis. In this model, the prognosis of the high-risk score group was poor (P < 0.001). The ROC curve showed that (AUC = 0.862) the model had a good performance in predicting prognosis. In Cox regression analysis, the comprehensive risk score can be employed as an independent prognostic factor of the EC. HIST1H1E, UBE2C and ERO1B interacted with differentially expressed miRNAs. High expression of HIST1H1E was resistant to trametinib, selumetinib, RDEA119, docetaxel and 17-AAG, High expression of UBE2C was resistant to masitinib, and Low expression of ERO1B made the EC more sensitive to FK866. We constructed an EC risk score model composed of 8 DEGs and gene resistance analysis, which can provide reference for prognosis prediction, diagnosis and treatment of the EC patients.

To screen key biomarkers of esophageal cancer (ESCA) by bioinformatics and analyze the correlation between key genes and immune infiltration. Expression profile data of ESCA was downloaded from TCGA database, and DEGs in ESCA were screened with R software. After the RNA binding proteins (RBPs) in DEGs were screened, the protein interaction network was constructed using tools such as STRING and Cytoscape and the key genes (HENMT1) were screened. Survival analysis of HENMT1 was performed by Kaplan–Meier method. Functional enrichment analysis of HENMT1 interacting proteins was performed using the DAVID website, and GSEA predicted the signal pathways involved by HENMT1. CIBERSORT algorithm was used to analyze the infiltration of immune cells in ESCA. The expression of HENMT1 in ESCA was detected by immunohistochemistry. A total of 105 RNA binding proteins (RBPs) were differentially expressed in ESCA, and a PPI network was constructed to screen the key gene HENMT1. The expression level of hemmt1 gene was closely related to the infiltration of B cells naive, T cells regulatory (Tregs), neutrophils, T cells CD4 memory activated, master cells resting and dendritic cells resting in ESCA tissues (P < .05). Immunohistochemical results showed that HENMT1 was highly expressed in ESCA tissues and was positively correlated with the expression of MKI67. HENMT1 is related to the occurrence and prognosis of ESCA, and is also related to the infiltration of immune cells in ESCA tissue, which may provide a new idea for the targeted treatment of ESCA.

Kawasaki disease (KD) is a systemic vasculitis primarily affecting children, with coronary artery lesions being its most severe complication. In this study, an optimized mouse KD model was established using the water-soluble extract of Candida albicans (CAWS). Myocardial inflammation and related pathological changes were evaluated using HE staining and Masson trichrome staining. The immunofluorescence technique detected the infiltration of immune cells in cardiac tissue. The expression and localization of VDAC1 protein in myocardial tissue were detected by immunohistochemistry. In vitro, a phagocytic model was established by co-culturing RAW264.7 macrophages with Candida albicans spores, and the formation and function of autophagolysosomes were assessed using LC3 immunofluorescence staining and a Lyso-Tracker Red probe. Through dose screening, it was determined that 8 mg was the optimal modeling dose for inducing coronary artery inflammation, with a moderate mortality rate at this dose. HE staining showed that CAWS injection stably induced coronary artery lesions consistent with the characteristics of human Kawasaki disease in mice. Masson staining confirmed that there was significant collagen fiber deposition around the coronary arteries and aorta in the CAWS group of mice, which closely coincided with the inflammatory area, and a statistically significant difference was observed from the control group at 14 days (p < 0.001). Immunofluorescence revealed that, on the 14th day of modeling, the infiltration of multiple immune cells in the cardiac tissue of the CAWS group had significantly increased (p < 0.001). The immunohistochemical results showed that, on the 28th day of modeling, the expression of VDAC1 protein in the myocardial tissue of the CAWS group was significantly upregulated (p < 0.001). In vitro experiments have shown that in macrophages infected with Candida albicans spores, the formation of autophagolysosomes increases in the early stage, while autophagic flow is blocked in the later stage, suggesting a functional disorder.

Kawasaki disease (KD) is a systemic vasculitis primarily affecting children, with coronary artery lesions being its most severe complication. In this study, an optimized mouse KD model was established using the water-soluble extract of Candida albicans (CAWS). Myocardial inflammation and related pathological changes were evaluated using HE staining and Masson trichrome staining. The immunofluorescence technique detected the infiltration of immune cells in cardiac tissue. The expression and localization of VDAC1 protein in myocardial tissue were detected by immunohistochemistry. In vitro, a phagocytic model was established by co-culturing RAW264.7 macrophages with Candida albicans spores, and the formation and function of autophagolysosomes were assessed using LC3 immunofluorescence staining and a Lyso-Tracker Red probe. Through dose screening, it was determined that 8 mg was the optimal modeling dose for inducing coronary artery inflammation, with a moderate mortality rate at this dose. HE staining showed that CAWS injection stably induced coronary artery lesions consistent with the characteristics of human Kawasaki disease in mice. Masson staining confirmed that there was significant collagen fiber deposition around the coronary arteries and aorta in the CAWS group of mice, which closely coincided with the inflammatory area, and a statistically significant difference was observed from the control group at 14 days (p < 0.001). Immunofluorescence revealed that, on the 14th day of modeling, the infiltration of multiple immune cells in the cardiac tissue of the CAWS group had significantly increased (p < 0.001). The immunohistochemical results showed that, on the 28th day of modeling, the expression of VDAC1 protein in the myocardial tissue of the CAWS group was significantly upregulated (p < 0.001). In vitro experiments have shown that in macrophages infected with Candida albicans spores, the formation of autophagolysosomes increases in the early stage, while autophagic flow is blocked in the later stage, suggesting a functional disorder.

Silica exposure is associated with an increased risk of lung adenocarcinoma, but its molecular mechanism remains unclear. This study aims to establish a repeatable experimental protocol to explore how the nuclear factor erythroid 2-related factor 2 (NRF2) inhibitor ML385 inhibits silica-induced malignant progression of lung adenocarcinoma by regulating the ROS/NRF2-autophagy axis pathway. Firstly, a silicosis model was established by intranasal perfusion of silica suspension in C57BL/6 mice. The degree of pulmonary fibrosis was evaluated by Masson staining, the infiltration of immune cells was analyzed by immunofluorescence, and the expressions of NRF2, cyclin-dependent kinase 1 (CDK1), and voltage-dependent anion channel 1 (VDAC1) in lung tissue were detected by immunohistochemistry. Subsequently, in in vitro experiments, the RAW264.7 macrophage cell line was treated with silica. Autophagic flux and oxidative stress levels were evaluated by LC3-lysosome co-localization and ROS probes, and intervention was carried out with the NRF2 inhibitor ML385. Finally, the effects of ML38 on migration, invasion, and apoptosis of lung adenocarcinoma cells were analyzed by scratch assay, cells passing through pores of a specific size assay, and flow cytometry. The results showed that silica could induce pulmonary fibrosis, immune cell infiltration, and upregulation of NRF2, CDK1, and VDAC1 in mice (p < 0.001), and inhibit the autophagic flux of macrophages and reduce ROS levels. ML385 can reverse these effects (p < 0.05). This protocol provides a complete experimental process from in vivo model construction to in vitro mechanism research, offering an operational technical path for studying the molecular mechanism of silica-related lung adenocarcinoma and therapeutic strategies targeting NRF2.