Ovarian cancer (OC) is one of the worrisome gynecological cancers worldwide. Given its considerable mortality rate, it is necessary to investigate its oncogenesis. In this study, we used systems biology approaches to describe the key gene modules, hub genes, and regulatory drugs associated with serous OC as the novel biomarkers using weighted gene co-expression network analysis (WGCNA). Our findings have demonstrated that the blue module genes (r = 0.8, p-value = 1e-16) are involved in OC progression. Based on gene enrichment analysis, the genes in this module are frequently involved in biological processes such as the Cyclic adenosine monophosphate (cAMP) signaling pathway and the cellular response to transforming growth factor-beta stimulation. The co-expression network has been built using the correlated module's top hub genes, which are ADORA1, ANO9, CD24P4, CLDN3, CLDN7, ELF3, KLHL14, PRSS8, RASAL1, RIPK4, SERINC2, and WNT7A. Finally, a drug-target network has been built to show the interaction of the FDA-approved drugs with hub genes. Our results have discovered that ADORA1, ANO9, SERINC2, and KLHL14 are hub genes associated with serous OC. These genes can be considered as novel candidate target genes for treating OC.

The coronavirus disease-2019 (COVID-19) pandemic has caused an enormous loss of lives. Various clinical trials of vaccines and drugs are being conducted worldwide; nevertheless, as of today, no effective drug exists for COVID-19. The identification of key genes and pathways in this disease may lead to finding potential drug targets and biomarkers. Here, we applied weighted gene co-expression network analysis and LIME as an explainable artificial intelligence algorithm to comprehensively characterize transcriptional changes in bronchial epithelium cells (primary human lung epithelium (NHBE) and transformed lung alveolar (A549) cells) during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Our study detected a network that significantly correlated to the pathogenicity of COVID-19 infection based on identified hub genes in each cell line separately. The novel hub gene signature that was detected in our study, including PGLYRP4 and HEPHL1, may shed light on the pathogenesis of COVID-19, holding promise for future prognostic and therapeutic approaches. The enrichment analysis of hub genes showed that the most relevant biological process and KEGG pathways were the type I interferon signaling pathway, IL-17 signaling pathway, cytokine-mediated signaling pathway, and defense response to virus categories, all of which play significant roles in restricting viral infection. Moreover, according to the drug–target network, we identified 17 novel FDA-approved candidate drugs, which could potentially be used to treat COVID-19 patients through the regulation of four hub genes of the co-expression network. In conclusion, the aforementioned hub genes might play potential roles in translational medicine and might become promising therapeutic targets. Further in vitro and in vivo experimental studies are needed to evaluate the role of these hub genes in COVID-19.

The coronavirus disease 2019 (COVID-19) outbreak is an ongoing global health emergence, but the pathogenesis remains unclear. Here, we applied weighted gene co-expression network analysis to comprehensively characterize transcriptional changes in bronchial epithelium cells (NHBE and A549 cells) during SARS-CoV-2 infection. Our analysis identified a network highly correlated to COVID-19 pathogenicity based on MX1, IFIT1, ISG15, IFI6, DDX60, IRF9, PARP9, PGLYRP4, IL36G, SAA2 and IL-8 hub genes. The results also indicated a unique transcriptional signatures of infected cells including IFI6 and IRF9 as novel gene candidates and suggested their prospective mechanism in COVID-19 pathogenesis. The result of hub genes enrichment showed that the most correlation topic in biological process and KEGG were type I interferon signaling pathway, IL-17 signaling pathway, cytokine mediated signaling pathway, and defense response to virus categories which all play significant roles in restricting viral infection. Also according to the drug-target network, we recognized 54 FDA-approved drug candidates for other indications could potentially use for the treatment of COVID-19 patients through regulation of six hub genes of the co-expression network. Our findings also showed that the 19 experimentally validated miRNAs regulated the co-expression network through 5 hub genes (SLC19A3, FAM13A, PLA2G16, and HRASLS5). In conclusion, these hub genes had potential roles in the translational medicine and might become promising therapeutic targets further in vitro and in vivo experimental studies are needed to evaluate the role of above mentioned genes in COVID-19.

Introduction: Tetralogy of Fallot (TOF) is the most common cyanotic form of congenital heart defects. However, there is no effective therapeutic approach and current therapies have limited curative efficacy. Moreover, the exact etiology of TOF has remained largely unknown. Improved understanding of molecular mechanisms can give an insight into TOF pathogenesis and development of therapeutic approaches. Methods: Here, we conducted a systematic study on the right ventricular myocardium of 24 infants (16 ToF/8 control) using weighted gene co-expression network analysis (WGCNA) to identify meaningful modules or candidate biomarkers. Results: Co-expression network analysis by WGCNA suggested that a highly preserved turquoise module with 2,493 genes and a P-value of 3×10-11 was significantly correlated to TOF. The top 5 hub genes of this module were PSMA2, MYL12A, C11ORF71, COMMD6, and CREG1. The result of turquoise module enrichment showed that the most correlation topic in biological processes and KEGG pathways were positive regulation of cardiac neural crest migration involved in outflow tract morphogenesis and positive regulation of neural crest cell differentiation. Also, we recognized 4 FDA-approved drug candidates for other indications could potentially use for the treatment of TOF patients through regulation of two hub genes of the co-expression network (PSMA2 and NDUFA4). Our findings also showed that the 13 experimentally validated microRNAs regulated the co-expression network through 5 hub genes. Conclusion: We systematically recognized co-expressed gene modules and hub genes associated with TOF progression, which offered insights into the mechanisms underlying TOF progression and some potential drugs for the treatment of TOF.