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Background: Seminoma accounts for the most part of cases of testicular germ cell tumor, which is the most common malignancy among males between ages 15 and 44 years. Understanding the molecular mechanism of tumorigenesis is important for better clinical diagnosis and treatment. Purpose: We performed bioinformatics analysis to better understand seminoma at the genetic level and to explore potential candidate genes or molecules for diagnosis, treatment, and prognosis. Methods: A gene expression profile (GSE8607), containing 40 seminoma samples and three healthy testes samples, was analyzed to identify differentially expressed genes (DEGs) associated with the occurrence of seminoma. Functional annotation was then performed using gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Cytoscape with Search Tool for the Retrieval of Interacting Genes was used to construct a protein-protein interaction (PPI) network of the DEGs and select hub genes. Moreover, validation of expression level and Kaplan-Meier analysis for overall survival were conducted to those hub genes. Results: A total of 1,636 DEGs were identified between seminoma and healthy samples, including 701 up-regulated in seminoma that were enriched in the regulation of immune responses, defense responses, receptor activity, and signal transducer activity; 935 were down-regulated in seminoma and were associated with reproductive processes, kinase activity, and carbohydrate derivative binding. Five hub genes were selected from the PPI network according to the degree of connectivity: IL6, VEGFA, IL10, CCR5, and CXCR4. Among them, high expression levels of CCR5 and CXCR4 were associated with poor prognosis for seminoma patients. Four modules selected from the PPI network revealed that seminoma was connected with the Janus kinase-signal transducers and activators of transcription signaling pathway, chemokine signaling pathway, endocytosis, and cytokine-cytokine receptor interaction. Conclusion: These identified DEGs and hub genes facilitate our knowledge of the underlying molecular mechanism of seminoma and have the potential to be used as diagnostic biomarkers or therapeutic targets for seminoma.
Pubmed ID: 31190870
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Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.
View all literature mentionsSoftware platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.
View all literature mentionsDatabase of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations and are derived from four sources: Genomic Context, High-throughput experiments, (Conserved) Coexpression, and previous knowledge. STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable. The database currently covers 5''214''234 proteins from 1133 organisms. (2013)
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
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