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Due to heterogenetic-specific nature of the available biomarkers, the incidence of lung adenocarcinoma (LUAD) is on the rise worldwide. Previously reported LUAD-related hub genes were searched from the medical literature via literature mining and were processed to identify few top genes via degree method. Later, a comprehensive in silico methodology was applied on the selected real hub genes to identify their tumor driving, diagnostic, and prognostic roles in LUAD patients with divers clinicopathological variables. Out of total 145 extracted hub genes, six genes including CDC6, PBK, AURKA, KIF2C, OIP5, and PRC1 were identified as real hub genes. The expression analysis showed that all these genes were significantly up-regulated across LUAD samples of different clinicopathological variables. In addition, a variety of unique correlations among the expression and of real hub genes and some other parameters including promoter methylation status, overall survival (OS), genetic changes, tumor purity, and immune cell infiltration have also been explored in the present study. Moreover, via TFS-miRNA-mRNA regulatory network, one important TF (E2F1) and one important miRNAs (hsa-mir-34a-5p) that targeted all the real hub genes were also identified. Finally, a variety of drugs also predicted to be very useful in treating LUAD. The discovery of the real hub genes, TFS-miRNA-mRNA network, and chemotherapeutic drugs associated with LUAD provides new insights into underlying mechanisms and treatment of LUAD overcoming heterogeneity barriers., Competing Interests: None., (AJCR Copyright © 2023.)

Background: Considering it is one of the major causes of sudden cardiac arrest, the proper management of hypertrophic cardiomyopathy (HCM) is essential. However, efficient treatment options for this disease are still lacking. The discovery of HCM-associated hub genes may help in diagnosis and offer a reliable tool for developing effective therapeutic strategies., Methods: We examined HCM-based gene expression datasets (GSE36961) from the Gene Expression Omnibus (GEO) database for the identification of differentially expressed genes (DEGs), PPI network development, module screening, and shortlisting of hub genes via GEOR2, STRING, and Cytoscape. Moreover, we also used another HCM-based gene expression dataset (GSE32453) for the expression validation of hub genes. Following this, we constructed the lncRNA-cricRNA-miRNA-mRNA regulatory network after retrieving information from the miRTarBase, miRDB, and MiRcode databases. Finally, we used DAVID to perform functional and pathway analysis of the hub genes., Results: From GSE36961, a total of the 262 most significant DEGs, including 162 down-regulated and 76 up-regulated, were identified between HCM patients and normal individuals. Among these DEGs, a total of 10 significantly down-regulated DEGs, including cluster of differentiation 14 (CD14), beta2 Integrin Gene (ITGB2), C1q subcomponent subunit B (C1QB), Cluster of Differentiation 163 (CD163), Hematopoietic Cell-Specific Lyn Substrate 1 (HCLS1), Arachidonate 5-Lipoxygenase Activating Protein (ALOX5AP), Pleckstrin (PLEK), Complement C1q C Chain (C1QC), Fc fragment Of IgE receptor Ig (FCER1G), and tyrosine kinase binding protein (TYROBP), were shortlisted as the hub genes. Pathway enrichment analysis showed that the identified hub genes were involved in the dysregulation of some diverse pathways in HCM patients. Such as, Pertussis, Complement and coagulation cascade, Legnionellosis, Asthma, Staphylococcus aureus infection, etc. Lastly, we also explored hub genes' regulatory 2 MicroRNAs (miRNAs, has-mir-7-5p and has-mir-27a-3p), one Long non-coding RNAs (lncRNA, OIP5-AS1-201), and one Circular RNA (cricRNA, CDR1as) via lncRNA-cricRNA-miRNA-mRNA regulatory network., Conclusion: Our study revealed that ten hub genes (CD14, ITGB2, C1QB, CD163, HCLS1, ALOX5AP, PLEK, C1QC, FCER1G, and TYROBP) are involved in the development and progression of HCM. These genes can potentially be used as biomarkers and therapeutic targets for HCM patients., Competing Interests: None., (AJTR Copyright © 2022.)

Objectives: Cervical Squamous Cell Carcinoma (CESC) is one of the most fatal female malignancies, and the underlying molecular mechanisms governing this disease have not been fully explored. In this research, we planned to conduct the analysis of Gene Expression Omnibus (GEO) cervical squamous cell carcinoma microarray datasets by a detailed in silico approach and to explore some novel biomarkers of CESC., Methods: The top commonly differentially expressed genes (DEGs) from the GSE138080 and GSE113942 datasets were analyzed by Limma package-based GEO2R tool. The protein-protein interaction (PPI) network of the DEGs was drawn through Search Tool for the Retrieval of Interacting Genes (STRING), and top 6 hub genes were obtained from Cytoscape. Expression analysis and validation of hub genes expression in CESC samples and cell lines were done using UALCAN, OncoDB, GENT2, and HPA. Additionally, cBioPortal, Gene set enrichment analysis (GSEA) tool, Kaplan-Meier (KM) plotter, ShinyGO, and DGIdb databases were also used to check some important values of hub genes in CESC., Results: Out of 79 DEGs, the minichromosome maintenance complex component 4 (MCM4), nucleolar and spindle-associated protein 1 (NUSAP1), cell division cycle associated 5 (CDCA5), cell division cycle 45 (CDC45), denticleless E3 ubiquitin protein ligase homolog (DTL), and chromatin licensing and DNA replication factor 1 (CDT1) genes were regarded as hub genes in CESC. Further analysis revealed that the expressions of all these hub genes were significantly elevated in CESC cell lines and samples of diverse clinical attributes. In this study, we also documented some important correlations between hub genes and some other diverse measures, including DNA methylation, genetic alterations, and Overall Survival (OS). Last, we also identify hub genes associated ceRNA network and 31 important chemotherapeutic drugs., Conclusion: Through detailed in silico methodology, we identified 6 hub genes, including MCM4, NUSAP1, CDCA5, CDC45, DTL, and CDT1, which are likely to be associated with CESC development and diagnosis., Competing Interests: None., (AJTR Copyright © 2022.)