It is believed that matrix metalloproteinases (MMPs) play important roles in follicular development and pathogenesis of polycystic ovary syndrome (PCOS). However, conflicting results are available about the alteration of MMP2 and MMP9 concentrations or activities in PCOS. In fact, there is no study entirely investigating both concentration and activity of these MMPs and serum levels of their tissue inhibitors TIMP2 and TIMP1, as well as lipocalin-bound form of MMP9 (MMP9/NGAL). Therefore, the thoroughness of previous studies is questionable. This study was conducted to determine circulatory concentration of MMP2, MMP9, MMP9/NGAL complex, TIMP1 and TIMP2 as well as gelatinase activities of MMP2, MMP9 and MMP9/NGAL complex in women with PCOS and controls. Mean age and BMI as well as serum levels of total cholesterol, triacylglycerol, HDL-C, LDL-C, fasting blood sugar (FBS), insulin, estradiol and sex hormone-binding globulin did not differ between groups, whereas a marked decrease in FSH and significant increases in LH, LH/FSH ratio, testosterone and free androgen index were observed. Women with PCOS and controls showed closed concentrations of MMP2, MMP9, MMP9/NGAL, TIMP1 and TIMP2. Gelatinase activity of MMP9 was found significantly higher in PCOS than in controls (64.53G15.32 vs 44.61G18.95 respectively) while patients and healthy subjects showed similar activities of MMP2 and MMP9/NGAL complex. Additionally, PCOS patients showed a higher MMP9/TIMP1 ratio compared with control women. Direct correlations were also observed between circulatory MMP9 level and the concentration and activity of MMP9/NGAL complex. In conclusion, based on the results of present study, we believe that MMP9 may be involved in the pathogenesis of PCOS.Reproduction (2016) 151 305-311

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Background: Gastric cancer (GC) is a complex disorder with an inadequate response to treatment. Although many efforts have been made to clarify the development of GC, the exact etiology and molecular mechanisms of this malignancy remain unclear. This study was designed to identify and characterize essential associated genes with GC to construct a prognostic model. Methods: In this Insilco study, the gene expression microarray dataset GSE122401 was downloaded from the Gene Expression Omnibus (GEO). The raw data were processed and quantile-normalized with the edgeR package of R ver.3.5.3. The module-trait relationship and hub-genes associated with GC were analyzed with Weighted Gene Co-expression Network Analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by Cluepedia and Enrichr Database. Finally, hubgenes were screened and validated by GEPIA online database. Results: According to the WGCNA results, the blue module was found to be strongly correlated with the GC (r=0.91, p-value=1e-57). DEGs analysis was performed by edgeR package of R and indicated a total of 47 genes as hub-genes. Verifying the hub-genes expression using GEPIA online database showed a significantly increased level of ACAN gene expression in primary cancer cell line compared to metastatic cell line. On the other hand, the expression of MDFI and CHST1 genes in primary cell lines were lower compared to metastatic cancer cell lines. Conclusions: This study provides a framework of the co-expression gene modules ACAN, MDFI, and CHST1 as hub-genes. These hub-genes might offer candidate biomarkers to targeted therapy against GC. Further experiment validation and animal models are needed to reveal the exact mechanism of the above-mentioned genes in the pathogenesis and prognoses of GC.

Background and Methods Colorectal cancer (CRC) is considered one of the most common malignancies worldwide. The diagnosis and prognosis of the patients are very poor. In this study, we used in‐silico analysis and experimental techniques to investigate novel co‐expression genes and their associated miRNA networks in CRC. For this purpose, we conducted a comprehensive transcriptome analysis using online bulk and single‐cell RNA‐seq datasets. We then validated the results on tissue samples from cancerous and adjacent normal tissues from CRC patients by RT‐qPCR. Results Using a weighted gene co‐expression network algorithm, we identified SLC4A4 as a significantly downregulated hub gene in the CRC. The single‐cell analysis indicated that the expression level of SLC4A4 in Paneth cells is higher than in other cell populations. Further computational analysis suggested hsa‐miR‐223‐3p and hsa‐miR‐106a‐5p as two specific hub‐miRNAs for the SLC4A4 gene. RT‐qPCR analysis showed a 2.60‐fold downregulation of SLC4A4 . Moreover, hsa‐miR‐223‐3p and hsa‐miR‐106a‐5p showed an increased expression level of 5.58‐fold and 9.66‐fold in CRC samples, respectively. Based on the marginal model analysis, by increasing the expression of hsa‐miR‐106a‐5p, the average expression of the SLC4A4 gene significantly decreased by 103 units. Furthermore, ROC curves analysis indicated statistically significant for diagnostic ability of SLC4A4 (AUC: 0.94, Sensitivity: 95.5%, Specificity: 95.5%) and hsa‐miR‐106a‐5p (AUC: 0.72, Sensitivity: 72.7%, Specificity: 100%). Conclusion This study provides a framework of co‐expression gene modules and miRNAs of CRC, which identifies some important biomarkers for CRC pathogenicity and diagnosis. Further experimental evidence will be required to support this study and validate the precise molecular pathways.