Discovering therapeutic possibilities for polycystic ovary syndrome by targeting XIST and its associated ceRNA network through the analysis of transcriptome data.

Long non-coding RNA (lncRNA) regulates many physiological processes by acting as competitive endogenous RNA (ceRNA). The dysregulation of lncRNA X-inactive specific transcript (XIST) has been shown in various human disorders. However, its role in the pathogenesis of polycystic ovary syndrome (PCOS) is yet to be explored. This study aimed to explore the underlying mechanism of XIST in the pathogenesis of PCOS, specifically through dataset functional analysis. GEO PCOS datasets including RNA-seq, microarray, and miRNA-seq in granulosa cells (GCs) and blood, were examined and comprehensively analyzed. Enrichment analysis, ROC curve constructions, lncRNA-miRNA-mRNA interaction network analyses, and qRT-PCR validation were performed followed by a series of drug signature screenings. Our results revealed significant dysregulation in the expression of 1131 mRNAs, 30 miRNAs, and XIST in GCs of PCOS patients compared to healthy individuals. Of the120 XIST-correlated upregulated genes, 25 were enriched in inflammation-related pathways. Additionally, 5 miRNAs were identified as negative regulators of XIST-correlated genes. Accordingly, a ceRNA network containing XIST-miRNAs-mRNAs interactions was constructed. Furthermore, 6 genes, including AQP9, ETS2, PLAU, PLEK, SOCS3, and TNFRSF1B served as both GCs and blood-based biomarkers. By analyzing the number of interactions among XIST, miRNAs, and mRNAs, we pinpointed ETS2 as the pivotal gene within the ceRNA network. Our findings reveal a novel XIST- hsa-miR-146a-5p, hsa-miR-144-3p, and hsa-miR-1271-5p-ETS2 axis that comprehensively elucidates the XIST-associated mechanism underlying PCOS onset. qRT-PCR analysis further confirmed the, overexpression of both XIST and ETS2 . Furthermore, our results demonstrated that XIST and ETS2 were correlated with some assisted reproductive technologies outcomes. Finally, we identified two novel compounds including, methotrexate/folate and threonine using drug-gene interaction databases for PCOS management. These findings provide novel insights into the molecular etiology, diagnosis, and potential therapeutic interventions for PCOS.

Integrative Bioinformatics Analysis of The Cell Division Cycle and Ribosomal Pathways in The Rat Varicocele: Implications for Drug Discovery.

OBJECTIVE: Varicocele is a common cause of male infertility, affecting a substantial proportion of infertile men. Recent studies have employed transcriptomic analysis to identify candidate genes that may be implicated in the pathogenesis of this condition. Accordingly, this study sought to leverage rat gene expression profiling, along with protein-protein interaction networks, to identify key regulatory genes, related pathways, and potentially effective drugs for the treatment of varicocele. MATERIALS AND METHODS: In this in-silico study, differentially expressed genes (DEGs) from the testicular tissue of 3 rats were screened using the edgeR package in R software and the results were compared to 3 rats in the control group. Data was obtained from GSE139447. Setting a -11 and P<0.05 as cutoff points for statistical significance, up and down-regulated genes were identified. Based on Cytoscape plugins, protein-protein interaction (PPI) networks were drawn, and hub genes were highlighted. ShinyGO was used for pathway enrichment. Finally, effective drugs were identified from the drug database. RESULTS: Among the 1277 DEGs in this study, 677 genes were up-regulated while 600 genes were down-regulated in rats with varicocele compared to the control group. Using protein-protein interaction networks, we identified the top five up-regulated genes and the top five down-regulated genes. Enrichment analysis showed that the up-regulated genes were associated with the cell division cycle pathway, while the down-regulated genes were linked to the ribosome pathway. Notably, our findings suggested that dexamethasone may be a promising therapeutic option for individuals with varicocele. CONCLUSION: The current investigation indicates that in varicocele the cell division cycle pathway is up-regulated while the ribosome pathway is down-regulated compared to controls. Based on these findings, dexamethasone could be considered a future candidate drug for the treatment of individuals with varicocele.

Identification of genes with high heterogeneity of expression as a predictor of different prognosis and therapeutic responses in colorectal cancer: a challenge and a strategy.

BACKGROUND: Molecular heterogeneity is one of the most important concerns in colorectal cancer (CRC), which results in a wide range of therapy responses and patient prognosis. We aimed to identify the genes with high heterogeneity of expression (HHE) and their relation with prognosis and drug resistance. METHODS: Two cohort studies, the cancer genome atlas (TCGA) and the GSE39582, were used to discover oncogenes genes with HHE. The relationship between identified genes with clinical and genomic characteristics was evaluated based on TCGA data. Also, the GDSC and CCLE data were used for drug resistance and sensitivity. Sixty CRC samples were used to validate the obtained data by RT-qPCR. RESULTS: Findings revealed that 132 genes with HHE were found to be up-regulated in both cohorts and were enriched in pathways such as hypoxia, angiogenesis, and metastasis. Forty-nine of selected genes related to clinical and genomic variables, including stage, common mutations, the tumor site, and microsatellite state that were ignored. The expression level of CXCL1, SFTA2, SELE, and SACS as genes with HHE were predicted survival patients, and RT-qPCR results demonstrated that levels of SELE and SACS had HHE in CRC samples. The expression of many identified genes like BGN, MMP7, COL11A1, FAP, KLK10, and TNFRSE11B was associated with resistance to chemotherapy drugs. CONCLUSIONS: Some genes expression, including SELE, SACS, BGN, KLK10, COL11A1, and TNFRSE11B have an oncogenic function with HHE, and their expression can be used as indicators for differing treatment responses and survival rates in CRC.