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Abstract. Radiation-induced lung injury (RILI) is a common complication associated with thoracic radiotherapy. The aim of the present study was to investigate the effects of a single 15-Gy dose of right-thoracic lung irradiation on the expression levels of matrix metalloproteinases (MMPs) and other proteins in the alveolar epithelial type II (AE2) cells of Bama minipigs. All minipigs received either right-thoracic irradiation or sham irradiation under anesthesia, and were sacrificed at 4, 8, 12 or 24 weeks after irradiation. Collagen deposition was measured using Masson's trichrome staining. Surfactant protein A (SP-A), transforming growth factor β1 (TGFβ1), MMP2, MMP9, vimentin and E-cadherin protein expression levels were evaluated using western blot analysis, and the MMP2 and MMP9 gelatinase activities were tested using gelatin zymography. SP-A and α-smooth muscle actin (α-SMA) co-localization was visualized using double immunofluorescence staining. At each time-point following irradiation, a significant increase in TGFβ1, α-SMA, MMP2, MMP9 and vimentin protein expression levels and MMP2 and MMP9 gelatinase activity were observed in the irradiated lungs compared with the sham-irradiated controls. By contrast, SP-A and E-cadherin protein expression levels decreased in a time-dependent manner post-irradiation. SP-A and α-SMA co-localization was observed in irradiated alveolar epithelial cells. These data demonstrate that E-cadherin, SP-A, MMP2 and MMP9 may function as sensitive predictors of RILI. Epithelial-mesenchymal transition (EMT) occurs in the irradiated lungs of Bama minipigs, and MMP2 and MMP9 may contribute to EMT in AE2 cells by regulating TGFβ1. Therefore, EMT may serve a crucial function in the development of RILI.

In this study, bioinformatics tools were used to identify key genes to study the molecular mechanism of nasopharyngeal carcinoma (NPC) development and to explore the correlation of these key genes with the recurrence and metastasis of NPC. The GSE61218 microarray dataset obtained from the Gene Expression Omnibus Database (GEO) was used. The limma R package was used to screen differentially expressed genes (DEGs) between NPC and normal nasopharyngeal (NP) tissues. KEGG functional enrichment was performed on these selected DEGs. Protein-protein interaction (PPI) networks were constructed using Cytoscape software to identify key node proteins. The NPC-metastasis microarray dataset GSE103611 was obtained from GEO to analyze the expression of DEGs in NPC metastasis. A total of 239 DEGs were identified. DEGs were mainly enriched in oocyte maturation-related pathways, cytokine-related pathways, cell cycle-related pathways, cancer-related pathways, and homologous recombination-related pathways. In addition, the top 10 nodes with the higher degree in the DEG PPI network were as follows: CDK1, CCNB2, BUB1, CCNA2, AURKB, BUB1B, MAD2L1, NDC80, BIRC5, and CENPF. The results indicated that DEGs may be involved in the pathogenesis of NPC by regulating cell cycle and mitosis, which can be used as molecular biomarkers for the diagnosis of NPC. In addition, we identified 87 DEGs with FC > 2 and P < 0.01 from the metastasis spectrum of NPC. The intersection gene between DEGs of NPC and normal NP tissue samples and those of the metastatic spectrum of NPC was identified to be VRK2. The expression of VRK2 in NPC samples was significantly higher than that in normal NP tissue, and similarly, VRK2 expression was significantly upregulated in metastatic samples compared with nonmetastatic samples ( P < 0.05 ). Therefore, VRK2 may be a biomarker for predicting the metastasis of NPC patients after treatment.

Background: This study aimed to investigate prognostic genes in ovarian cancer (OC) and to explore their potential underlying biological mechanisms through a comprehensive bioinformatics analysis. Methods: Common differentially expressed genes (DEGs) in 3 OC datasets from the Gene Expression Omnibus (GEO) (GSE26712, GSE18520, and GSE14407) were screened out. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed by Metascape.The protein-protein interaction (PPI) network of the DEGs was constructed using the STRING database.The prognostic value of DEGs were determined using the Kaplan-Meier plotter. The ONCOMINE and Human Protein Atlas databases were used to verify the expression levels of prognostic genes in OC.Genomic analysis of prognostic genes were also investigated by cBio Cancer Genomics Portal (cBioPortal) database, UCSC Xena browser and UALCAN. Gene set enrichment analysis (GSEA) was used to predict the possible pathways and biological processes of the prognostic genes.Results: Integration of the 3 datasets have found 879 common DEGs. A high expression of structural maintenance of chromosomes protein 4 (SMC4) was revealed in the Kaplan-Meier plotter analysis to be meaningful for the prognosis of OC and was verified at both the mRNA and protein levels. The results from cBioPortal showed that SMC4 alterations accounted for 7 to 18% of genetic alterations in OC, and the majority alterations were copy number amplifications. Finally, the GSEA results showed that samples with SMC4 overexpression were mainly enriched in the cell cycle, spliceosome, ubiquitin mediated proteolysis, and adherens junctions.Conclusions: High SMC4 expression is linked with a poor prognosis in patients with OC and might serve as a prognostic biomarker for the disease.