Cancer is a fatal malignancy and its increasing worldwide prevalence demands the discovery of more sensitive and reliable molecular biomarkers. To investigate the GINS1 expression level and its prognostic value in distinct human cancers using a series of multi-layered in silico approach may help to establish it as a potential shared diagnostic and prognostic biomarker of different cancer subtypes. The GINS1 mRNA, protein expression, and promoter methylation were analyzed using UALCAN and Human Protein Atlas (HPA), while mRNA expression was further validated via GENT2. The potential prognostic values of GINS1 were evaluated through KM plotter. Then, cBioPortal was utilized to examine the GINS1-related genetic mutations and copy number variations (CNVs), while pathway enrichment analysis was performed using DAVID. Moreover, a correlational analysis between GINS1 expression and CD8+ T immune cells and a the construction of gene-drug interaction network was performed using TIMER, CDT, and Cytoscape. The GINS1 was found down-regulated in a single subtypes of human cancer while commonly up-regulated in 23 different other subtypes. The up-regulation of GINS1 was significantly correlated with the poor overall survival (OS) of Liver Hepatocellular Carcinoma (LIHC), Lung Adenocarcinoma (LUAD), and Kidney renal clear cell carcinoma (KIRC). The GINS1 was also found up-regulated in LIHC, LUAD, and KIRC patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of GINS1 in two diverse pathways, while few interesting correlations were also documented between GINS1 expression and its promoter methylation level, CD8+ T immune cells level, and CNVs. Moreover, we also predicted few drugs that could be used in the treatment of LIHC, LUAD, and KIRC by regulating the GINS1 expression. The expression profiling of GINS1 in the current study has suggested it a novel shared diagnostic and prognostic biomarker of LIHC, LUAD, and KIRC.
In light of the increased demand for reliable cancer-associated biomarkers and ANLN oncogenic potential, the present study aimed to investigate ANLN's role in 24 human cancers. Methods: The UALCAN, Kaplan-Meier (KM) plotter, TNM Plot, GENT2, GEPIA, HPA, cBioPortal, STRING, Enrichr, TIMER, Cytoscape, DAVID, MuTarget, and CTD online databases and bioinformatic tools were used in this study. Results: In three of the cancers analyzed, ANLN expression was downregulated in tumor tissue, while it was overexpressed in the 21 other types of tumor tissue relative to controls. In CESC, ESCA, HNSC, and KIRC patients, ANLN overexpression was correlated with shorter overall survival, relapse-free survival, and metastasis. This suggests that ANLN is significantly involved in the development and progression of these four cancers. Further expression analysis revealed upregulation of ANLN in CESC, ESCA, HNSC, and KIRC patients with different clinical characteristics, regardless of the heterogeneity barrier. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that ANLN-associated genes were coexpressed with ANLN and were included in diverse BP, MF, and KEGG terms. Moreover, some interesting correlations were also documented between ANLN expression and its promoter-methylation level, genetic alterations, other mutant genes, and CD8 + T-and CD4 + T-cell infiltration. Moreover, we also identified ANLN-associated transcription factors, miRNAs, and chemotherapeutic drugs. Conclusion:This pan-cancer study revealed the novel diagnostic and prognostic role of ANLN across four cancers, regardless of heterogeneity.
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