In Silico Prediction of Functional SNPs Interrupting Antioxidant Defense Genes in Relation to COVID-19 Progression.

The excessive production of reactive oxygen species and weakening of antioxidant defense system play a pivotal role in the pathogenesis of different diseases. Extensive differences observed among individuals in terms of affliction with cancer, cardiovascular disorders, diabetes, bacterial, and viral infections, as well as response to treatments can be partly due to their genomic variations. In this work, we attempted to predict the effect of SNPs of the key genes of antioxidant defense system on their structure, function, and expression in relation to COVID-19 pathogenesis using in silico tools. In addition, the effect of SNPs on the target site binding efficiency of SNPs was investigated as a factor with potential to change drug response or susceptibility to COVID-19. According to the predicted results, only six missense SNPs with minor allele frequency (MAF) ≥ 0.1 in the coding region of genes GPX7, GPX8, TXNRD2, GLRX5, and GLRX were able to strongly affect their structure and function. Our results predicted that 39 SNPs with MAF ≥ 0.1 led to the generation or destruction of miRNA-binding sites on target antioxidant genes from GPX, PRDX, GLRX, TXN, and SOD families. The results obtained from comparing the expression profiles of mild vs. severe COVID-19 patients using GEO2R demonstrated a significant change in the expression of approximately 250 miRNAs. The binding efficiency of 21 of these miRNAs was changed due to the elimination or generation of target sites in these genes. Altogether, this study reveals the fundamental role of the SNPs of antioxidant defense genes in COVID-19 progression and susceptibility of individuals to this virus. In addition, different responses of COVID-19 patients to antioxidant defense system enhancement drugs may be due to presence of these SNPs in different individuals.

Meta-analysis of microarray data to determine gene indicators involved in cisplatin resistance in non-small cell lung cancer.

BACKGROUND: Lung cancer is a major cause of cancer-related mortality worldwide, with a 5-year survival rate of approximately 22%. Cisplatin is one of the standard first-line chemotherapeutic agents for non-small cell lung cancer (NSCLC), but its efficacy is often limited by the development of resistance. Despite extensive research on the molecular mechanisms of chemoresistance, the underlying causes remain elusive and complex. AIMS: We analyzed three microarray datasets to find the gene signature and key pathways related to cisplatin resistance in NSCLC. METHODS AND RESULTS: We compared the gene expression of sensitive and resistant NSCLC cell lines treated with cisplatin. We found 274 DEGs, including 111 upregulated and 163 downregulated genes, in the resistant group. Gene set enrichment analysis showed the potential roles of several DEGs, such as TUBB2B, MAPK7, TUBAL3, MAP2K5, SMUG1, NTHL1, PARP3, NTRK1, G6PD, PDK1, HEY1, YTHDF2, CD274, and MAGEA1, in cisplatin resistance. Functional analysis revealed the involvement of pathways, such as gap junction, base excision repair, central carbon metabolism, and Notch signaling in the resistant cell lines. CONCLUSION: We identified several molecular factors that contribute to cisplatin resistance in NSCLC cell lines, involving genes and pathways that regulate gap junction communication, DNA damage repair, ROS balance, EMT induction, and stemness maintenance. These genes and pathways could be targets for future studies to overcome cisplatin resistance in NSCLC.

The impact of oleuropein on miRNAs regulating cell death signaling pathway in human cervical cancer cells.

Cervical cancer is known as the second most pervasive malignancy in women across the globe. The role played by microRNAs (miRNAs) in the initiation, progression, and metastasis of this cancer has received specific attention. The use of natural compounds leading cancer cells toward apoptosis is a feasible strategy for cancer therapy. Oleuropein, an olive-extracted phenolic substance, displays anticancer properties. Here, it was attempted to assess the role played by oleuropein in cell viability in cervical cancer and changes in the expression of some miRNAs associated with cervical cancer as well as some of their possible target genes selected using bioinformatics analysis. For this purpose, HeLa cell line was exposed to several oleuropein concentrations for 48 and 72 h. After that, 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide assay and flow cytometry were employed to assess cell viability and apoptosis, respectively. In addition, to conduct bioinformatics analysis, Cytoscape computer program was used based on STRING database. Furthermore, to examine the role played by oleuropein in the expression of miRNAs of interest as well as their potential target genes, real-time PCR was employed. The findings indicated that oleuropein reduced cell viability through inducing apoptosis. As a result of treatment with oleuropein, miR-34a, miR-125b, and miR-29a showed increased expression levels, whereas miR-181b, miR-221, and miR-16 showed decreased expression levels. Furthermore, oleuropein reduced the expression of the anti-apoptotic genes Bcl-2 and Mcl1, whereas it elevated the expression of the pro-apoptotic Bid, Fas, and TNFRSF10B genes and the p53 tumor suppressor. Our results indicate that the apoptosis induction is a mechanism of action of oleuropein in HeLa cells. Because of its effect on the reflation of the expression of genes and miRNAs effective in the pathogenesis of cervical cancer, oleuropein shows potential as an effective research tool for developing new natural drugs for treating cervical cancer.

Diagnostic accuracy of serum derived exosomes for hepatocellular carcinoma: a systematic review and meta-analysis.

INTRODUCTION: Early and non-invasive detection of hepatocellular carcinoma (HCC), which is usually asymptomatic, can improve overall survival outcomes. The objective of this systematic review and meta-analysis was to evaluate the diagnostic accuracy of serum-derived exosomes for diagnosing HCC. METHODS: PubMed, Web of Science, and Scopus databases were searched for relevant studies up to April 2023. The quality of included studies was assessed using the QUADAS-2 checklist, and data were extracted. Statistical analysis was performed on 18 studies from 3,993 records, and a diagnostic meta-analysis was conducted. Biomarkers were categorized into four groups based on their type (exosomal miRNAs, exosomal RNAs, alpha-fetoprotein (AFP), and exosomal RNAs+AFP panel), and a meta-analysis was conducted for each category separately. RESULTS: The highest pooled sensitivity was 0.86 for exosomal miRNAs, and exosomal RNAs+AFP had the highest pooled specificity; (0.89). Furthermore, exosomal RNAs+AFP had the highest pooled positive likelihood ratio; (7.55), the highest pooled diagnostic odds ratio (35.96) and the highest pooled area under the curve (0.93). Exosomal miRNAs had the lowest pooled negative likelihood ratio; (0.17). CONCLUSIONS: The diagnostic accuracy of exosomal biomarkers is superior to that of AFP, and combining the two in a panel yields the better results.

Acute Kidney Injury (AKI) in COVID-19: In silico Identification of LncRNA-MiRNA-Gene Networks and Key Transcription Factors.

PURPOSE: Acute kidney injury (AKI) accounts for up to 29% of severe COVID-19 cases and increases mortality among these patients. Viral infections participate in the pathogenesis of diseases by changing the expression profile of normal transcriptome. This study attempts to identify LncRNA-miRNA-gene and TF-gene networks as gene expression regulating networks in the kidney tissues of COVID-19 patients. METHODS: In this analysis, four kidney libraries from the GEO repository were considered. To conduct the preprocessing, Deseq2 software in R was used for the purpose of data normalization and log2 transformation. In addition, pre- and post-normalization, PCA and box plots were developed using ggplot2 software in R for quality control. The expression profiles of the kidney samples of COVID-19 patients and control individuals were compared using DEseq2 software in R. The considered significance thresholds for DEGs were Adj P value < 0.05 and |logFC| >2. Then, to predict molecular interactions in lncRNA-miRNA-gene networks, different databases, including DeepBase v3.0, miRNATissueAtlas2, DIANA-LncBase v3, and miRWalk, were used. Furthermore, by employing ChEA databases, interactions at the TF-Gene level were obtained. Finally, the obtained networks were plotted using Stringdb and Cytoscape v8. RESULTS: Results obtained from the comparison of the post-mortem kidney tissue samples of the COVID-19 patients with the healthy kidney tissue samples showed significant changes in the expression of more than 2000 genes. In addition, predictions regarding the miRNA-gene interaction network based on DEGs obtained from this meta-analysis showed that 11 miRNAs targeted the obtained DEGs. Interestingly, in the kidney tissue, these 11 miRNAs interacted with LINC01874, LINC01788, and LINC01320, which have high specificity for this tissue. Moreover, four transcription factors of EGR1, SMAD4, STAT3, and CHD1 were identified as key transcription factors regulating DEGs. Taken together, the current study showed several dysregulated genes in the kidney of patients affected with COVID-19. CONCLUSION: This study suggests lncRNA-miRNA-gene networks and key TFs as new diagnostic and therapeutic targets for experimental and preclinical studies.

In silico identification of potential miRNAs -mRNA inflammatory networks implicated in the pathogenesis of COVID-19.

COVID-19 has been found to affect the expression profile of several mRNAs and miRNAs, leading to dysregulation of a number of signaling pathways, particularly those related to inflammatory responses. In the current study, a systematic biology procedure was used for the analysis of high-throughput expression data from blood specimens of COVID-19 and healthy individuals. Differentially expressed miRNAs in blood specimens of COVID-19 vs. healthy specimens were then identified to construct and analyze miRNA-mRNA networks and predict key miRNAs and genes in inflammatory pathways. Our results showed that 171 miRNAs were expressed as outliers in box plot and located in the critical areas according to our statistical analysis. Among them, 8 miRNAs, namely miR-1275, miR-4429, miR-4489, miR-6721-5p, miR-5010-5p, miR-7110-5p, miR-6804-5p and miR-6881-3p were found to affect expression of key genes in NF-KB, JAK/STAT and MAPK signaling pathways implicated in COVID-19 pathogenesis. In addition, our results predicted that 25 genes involved in above-mentioned inflammatory pathways were targeted not only by these 8 miRNAs but also by other obtained miRNAs (163 miRNAs). The results of the current in silico study represent candidate targets for further studies in COVID-19.