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The differences in molecular mechanisms between osteochondroma and bizarre parosteal osteochondromatous proliferation (BPOP) remain to be fully elucidated. In the present study, the differentially expressed genes between BPOP and osteochondroma were obtained from the Gene Expression Omnibus online database, and the associations among these genes were analyzed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) online bioinformatics software. The results revealed several differentially expressed genes between human BPOP and osteochondroma. These differentially expressed genes were also enriched in different subgroups based on the analysis using DAVID online software, including ‘transforming growth factor β receptor signaling pathway’, ‘BMP signaling pathway’, ‘Wnt receptor signaling pathway’, ‘response to chemical stimulus’, ‘regulation of inflammatory response’, ‘response to stress’, ‘glycosaminoglycan binding’, ‘polysaccharide binding’, ‘extracellular matrix structural constituent’ and ‘growth factors binding’. Taken together, these findings led to the conclusion that different gene regulatory mechanisms exist between BPOP and osteochondroma. Environmental stimulation and inflammation may contribute to BPOP or osteochondroma, and differences in extracellular matrix may contribute to differences in biological characteristics between BPOP and osteochondroma.

Ovarian cancer is a major cause of mortality in women. However, the molecular events underlying the pathogenesis of the disease are yet to be fully elucidated. In the present study, an integrated bioinformatics analysis was performed to identify core genes involved in serous epithelial ovarian cancer. A total of three expression datasets were downloaded from the Gene Expression Omnibus database, and included 46 serous epithelial ovarian cancer and 30 ovarian surface epithelium samples. The three datasets were merged, and batch normalization was performed. The normalized merged data were subsequently analyzed for differentially expressed genes (DEGs). In total, 2,212 DEGs were identified, including 1,300 upregulated and 912 downregulated genes. Gene Ontology analysis revealed that these DEGs were primarily involved in 'regulation of cell cycle', 'mitosis', 'DNA packaging' and 'nucleosome assembly'. The main cellular components included 'extracellular region part', 'chromosome', 'extracellular matrix' and 'condensed chromosome kinetochore', whereas the molecular functions included 'Calcium ion binding', 'polysaccharide binding', 'enzyme inhibitor activity', 'growth factor activity', 'cyclin-dependent protein kinase regulator activity', 'microtubule motor activity' and 'Wnt receptor activity'. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that these DEGs were predominantly involved in 'Wnt signaling pathway', 'pathways in cancer', 'PI3K-Akt signaling pathway', 'cell cycle', 'ECM-receptor interaction', 'p53 signaling pathway' and 'focal adhesion'. The 20 most significant DEGs were identified from the protein-protein interaction network, and Oncomine analysis of these core genes revealed that 13 were upregulated and two were downregulated in serous epithelial ovarian cancer. Survival analysis revealed that cyclin B1, polo like kinase 1, G protein subunit γ transducin 1 and G protein subunit γ 12 are key molecules that may be involved in the prognosis of serous epithelial ovarian cancer. These core genes may provide novel treatment targets, although their roles in the carcinogenesis and prognosis of serous epithelial ovarian cancer require further study.

Goats are an important source of fibers. In the present study microarray technology was used to investigate the potential genes primarily involved in hair and cashmere growth in the Laiwu black goat. A total of 655 genes differentially expressed in body (hair‑growing) and groin (hairless) skin were identified, and their potential association with hair and cashmere growth was analyzed. The majority of genes associated with hair growth regulation could be assigned to intracellular, intracellular organelle, membrane‑bound vesicle, cytoplasmic vesicle, pattern binding, heparin binding, polysaccharide binding, glycosaminoglycan binding and cytoplasmic membrane‑bound vesicle categories. Numerous genes upregulated in body compared with groin skin contained common motifs for nuclear factor 1A, Yi, E2 factor (E2F) and cyclic adenosine monophosphate response element binding (CREB)/CREBβ binding sites in their promoter region. The promoter region of certain genes downregulated in body compared with groin skin contained three common regions with LF‑A1, Yi, E2F, Collier/Olfactory‑1/early B‑cell factor 1, peroxisome proliferator‑activated receptor α or U sites. Thus, the present study identified molecules in the cashmere‑bearing skin area of the Laiwu black goat, which may contribute to hair and cashmere traits.

Breast carcinoma is one of the most common types of malignant neoplasms, and is associated with high rates of morbidity and mortality. Altered gene expression is critical in the development of breast cancer. To identify the important differentially expressed genes and microRNAs in breast carcinoma, mRNA (GSE26910, GSE42568, and GSE89116) and microRNA (GSE35412) microarray datasets were downloaded from the Gene Expression Omnibus database. The differentially expressed microRNA expression data were extracted with GEO2R online software. The DAVID online database was used to perform a function and pathway enrichment analysis of the key identified differentially expressed genes. A protein-protein interaction (PPI) network was constructed using the STRING online database, and visualized in Cytoscape software. The effect of the expression level of the key identified genes on overall survival (OS) time was analyzed by using the Kaplan-Meier Plotter online database. Furthermore, the online miRNA databases TargetScan, microT-CDS, and TarBase were used to identify the target genes of the differentially expressed miRNAs. A total of 254 differentially expressed genes were identified, which were enriched in cell adhesion, polysaccharide binding, extracellular region part and ECM-receptor interactions. The PPI network contained 250 nodes and 375 edges. Five differentially expressed genes were found to be significantly negatively correlated with the differentially expressed miRNAs, which were potentially also target genes for miRNAs. Four of the five genes, including AKAP12, SOPB, TCF7L2, COL12A1 and TXNIP were downregulated, and were associated with the OS of patients with breast carcinoma. In addition, a total of 130 differentially expressed miRNAs were identified. In conclusion, these results constitute a novel model for miRNA-mRNA differential expression patterns, and further studies may provide potential targets for diagnosing and understanding the mechanisms of breast carcinoma.