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Identifying FBLN1 (Gene ID: 2192) as a Potential Melanoma Biomarker for Melanoma based on an Analysis of microRNA Expression Profiles in the GEO and TCGA Databases.

ABSTRACT: Aims: We analyzed and compared the gene expression profiles (GSE92763) from normal melanocytes with malignant melanoma cell lines to identify genes that were differentially expressed that could serve as potential biomarkers for melanoma diagnosis. Materials and Methods: Gene expression profiles from the GSE92763 dataset were downloaded from the Gene Expression Omnibus (GEO) database. By comparing normal human melanocytes with multiple melanoma cell lines we identified 127 differentially expressed genes whose expression was altered. These data were used to identify hub genes associated with protein-protein interaction networks using Cytoscape software. To explore the biological functions of the aforementioned hub genes, we utilized the clusterProfiler package in R studio to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. We then used the Gene Expression Profiling Interactive Analysis (GEPIA) website to determine the association of these hub genes with overall survival (OS). In addition, we utilized the Oncomine and Cancer Cell Line Encyclopedia (CCLE) databases to further analyze and compare the expression of these key genes associated with melanoma with other tumor types. Results: The hub genes included three upregulated and seven downregulated genes, which were linked with extracellular junctions, migration, paracrine and proliferation functions based on GO. In addition, we performed a confirmatory analysis of the hub genes using The Cancer Genome Atlas (TCGA) database. This analysis revealed that the expression of the Fibulin 1 (FBLN1; gene ID: 2192) gene was significantly downregulated in melanomas, and that its expression level in melanoma patients was significantly associated with OS with high expressors having better OS (log-rank p = 0.0034, hazard ratio = 1.5, p = 0.0036). We further analyzed the expression of FBLN1 in melanoma using the TCGA and Oncomine databases, and confirmed that FBLN1 is expressed at lower levels than in other cells (p = 2.03E^-15, t = -15.586). FBLN1 has extremely high DNA copy number and low messenger RNA expression in melanoma cell lines according to the CCLE analysis. Conclusion: These results suggest that FBLN1 expression may be utilized as a biomarker and essential prognostic factor for melanoma; as well as provide an important theoretical basis for the development of melanoma treatments.

SUBMITTER: Liu XT

PROVIDER: S-EPMC7821436 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUNDS:Lung adenocarcinoma (LUAD) is one of the most common malignancies, and is a serious threat to human health. The aim of the present study was to assess potential biomarkers for the prognosis of LUAD through the analysis of gene expression microarrays. METHODS:The gene expression data for GSE118370 was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between normal lung and LUAD samples were screened using the R language. The DAVID database was used to analyze the functions and pathways of DEGs. The STRING database was used to the map protein-protein interaction (PPI) networks, and these were visualized with the Cytoscape software. Finally, the prognostic analysis of the hub gene in the PPI network was performed using the Kaplan-Meier tool. RESULTS:A total of 406 downregulated and 203 upregulated DEGs were identified. The GO analysis results revealed that downregulated DEGs were significantly enriched in angiogenesis, calcium ion binding and cell adhesion. The upregulated DEGs were significantly enriched in the extracellular matrix disassembly, collagen catabolic process, chemokine-mediated signaling pathway and endopeptidase inhibitor activity. The KEGG pathway analysis revealed that downregulated DEGs were enriched in neuroactive ligand-receptor interaction, hematopoietic cell lineage and vascular smooth muscle contraction, while upregulated DEGs were enriched in phototransduction. In addition, the top 10 hub genes and the most closely interacting modules of the top 3 proteins in the PPI network were screened. Finally, the independent prognostic value of each hub gene in LUAD patients was analyzed through the Kaplan-Meier plotter. Seven hub genes (ADCY4, S1PR1, FPR2, PPBP, NMU, PF4, and GCG) were closely correlated to overall survival time. CONCLUSION:The discovery of these candidate genes and pathways reveals the etiology and molecular mechanisms of LUAD, providing ideas and guidance for the development of new therapeutic approaches to LUAD.

Project description:BackgroundRecent studies have shown that pyroptosis is related to cancer development. Our previous study also found that gasdermins (GSDMs) was associated with the tumor immune microenvironment. Therefore, we wanted to observe the relationship between pyroptosis and the immune microenvironment and prognosis of skin cutaneous melanoma (SKCM).MethodsPyroptosis-related genes were used for pan-cancer prognostic analysis using the GEPIA2 online analysis website. Prognosis-related genes were clustered using R software and related R packages, and the best clustering results were screened for prognosis analysis. The prognosis-related genes were also used to establish a prognosis-related model. Assess the predictive power of a model by comparing area under the curve (AUC). The t-test was used to analyze the differences of immune-related indicators between the two clusters and between high and low risk groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed on the differential genes.ResultsBy clustering the prognosis-related genes, SKCM could be divided into 2 clusters with significant differences in prognosis P<0.05. A prognostic model can be established using prognosis-related genes. The AUC value of 1 year, 2 years and 3 years was 0.696, 0.702 and 0.664, respectively. The risk score was significantly associated with prognosis in both univariate and multivariate Cox analyses P<0.001. The low-risk group or C2 cluster with better prognosis had higher expression of pyroptosis-related genes, and tended to have a lower exclusion score, greater chemokine expression, more immune cells and higher immune score. However, the C2 cluster or low-risk group was also associated with a higher dysfunction score. At the same time, the C2 or low-risk group was more suitable for immunotherapy because of the higher immunophenoscore (IPS) score P<0.001. Correlation analysis also demonstrated that the risk score was positively correlated with the gene expression of most immunoinhibitors, MHC molecules, immunostimulators, and chemokines and their receptors.ConclusionsPyroptosis is associated with melanoma immune microenvironment, immunotherapy response, and prognoses. The constructed risk scores could effectively predict the characteristics of the immune microenvironment, the sensitivity to immunotherapy, and the prognosis of melanoma patients.

Dataset Information

Identifying FBLN1 (Gene ID: 2192) as a Potential Melanoma Biomarker for Melanoma based on an Analysis of microRNA Expression Profiles in the GEO and TCGA Databases.

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