RESUMO
The mechanisms behind prostate adenocarcinoma (PRAD) pathogenicity remain to be understood due to tumor heterogeneity. In the current study, we identified by microarray technology six eligible real hub genes from already identified hub genes through a systematic in silico approach that could be useful to lower the heterogenetic-specific barriers in PRAD patients for diagnosis, prognosis, and treatment. For this purpose, microarray technology-based, already-identified PRAD-associated hub genes were initially explored through extensive literature mining; then, a protein-protein interaction (PPI) network construction of those hub genes and its analysis helped us to identify six most critical genes (real hub genes). Various online available expression databases were then used to explore the tumor driving, diagnostic, and prognostic roles of real hub genes in PRAD patients with different clinicopathologic variables. In total, 124 hub genes were extracted from the literature, and among those genes, six, including CDC20, HMMR, AURKA, CDK1, ASF1B, and CCNB1 were identified as real hub genes by the degree method. Further expression analysis revealed the significant up-regulation of real hub genes in PRAD patients of different races, age groups, and nodal metastasis status relative to controls. Moreover, through correlational analyses, different valuable correlations between treal hub genes expression and different other data (promoter methylation status, genetic alterations, overall survival (OS), tumor purity, CD4+ T, CD8+ T immune cells infiltration, and different other mutant genes and a few more) across PRAD samples were also documented. Ultimately, from this study, a few important transcription factors (TFS), miRNAs, and chemotherapeutic drugs showing a great therapeutic potential were also identified. In conclusion, we have discovered a set of six real hub genes that might be utilized as new biomarkers for lowering heterogenetic-specific barriers in PRAD patients for diagnosis, prognosis, and treatment.
RESUMO
OBJECTIVES: Using different online available databases and Bioinformatics tools, we extensively studied the role STAT1 across different cancers. METHODS: STAT1 mRNA, protein expression, and promoter methylation were analyzed and validated using UALCAN, GENT2, Human Protein Atlas (HPA), and MEXPRESS. Furthermore, the potential prognostic values were evaluated through KM plotter. Then, cBioPortal was utilized to examine the STAT1-related genetic mutations, while pathway enrichment analysis was performed using DAVID. To identify STAT1 targeted microRNAs (miRNAs) and transcription factors (TFs) we used Enricher. Moreover, a correlational analysis between STAT1 expression tumor purity and CD8+ T immune cells and a gene-drug interaction network analysis was performed using TIMER, CTD, and Cytoscape. RESULTS: In 23 major human cancers, STAT1 expression was notably up-regulated relative to corresponding controls. As well, the elevated expression of STAT1 was exclusively found to be associated with the reduced overall survival (OS) of Esophageal Carcinoma (ESCA), Kidney Renal Clear Cell Carcinoma (KIRC), and Lung adenocarcinoma (LUAD) patients. This implies that STAT1 plays a significant role in the development and progression of these three cancers. Further pathway analysis indicated that STAT1 enriched genes were involved in six critical pathways, while a few interesting correlations were also documented between STAT1 expression and promoter methylation level, tumor purity, CD8+ T immune cells infiltration, and genetic alteration. In addition, we have also predicted a few miRNAs, TFs, and chemotherapeutic drugs that could regulate the STAT1 expression. CONCLUSION: The current study revealed the shared oncogenic, diagnostic, and prognostic role of STAT1 in ESCA, KIRC, and LUAD.
