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ABSTRACT: Background
Prostate cancer (Pca) remains one of the leading adult malignancies. PTEN (Phosphatase and Tensin Homolog) mutant is the top common mutated genes in prostate cancer, which makes it a promising biomarker in future individualized treatment.Methods
We obtained gene expression data of prostate cancer from TCGA (The Cancer Genome Atlas) database for analysis. We analyzed the DEGs (differentially expressed genes), and used online tools or software to analyze Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene set enrichment analysis (GSEA), Search Tool for the Retrieval of Interacting Genes/Proteins, and Molecular Complex Detection.Results
Latest TCGA data showed PTEN mutation in about 22% patients. 1736 DEGs in total were identified. Results of gene functional enrichment analyses showed that muscle contraction, negative regulation of growth and multiple metabolic progression were significantly enriched. GNG13, ACTN2, POTEE, ACTA1, MYH6, MYH3, MYH7, MYL1, TNNC1 and TNNC2 were the top ten hub genes. Patients with PTEN mutation showed relatively decreased mRNA expression level of PTEN. Survival analysis indicated the risk of disease recurrence in patients with PTEN mutation.Conclusions
Our findings suggested that PTEN mutation in prostate cancer may induce changes in a variety of genes and pathways and affect disease progression, suggesting the significance of PTEN mutation in individualized treatment of prostate cancer.
SUBMITTER: Sun J
PROVIDER: S-EPMC6889628 | biostudies-literature | 2019 Dec
REPOSITORIES: biostudies-literature
Sun Jian J Li Shugen S Wang Fei F Fan Caibin C Wang Jianqing J
BMC medical genetics 20191202 1
<h4>Background</h4>Prostate cancer (Pca) remains one of the leading adult malignancies. PTEN (Phosphatase and Tensin Homolog) mutant is the top common mutated genes in prostate cancer, which makes it a promising biomarker in future individualized treatment.<h4>Methods</h4>We obtained gene expression data of prostate cancer from TCGA (The Cancer Genome Atlas) database for analysis. We analyzed the DEGs (differentially expressed genes), and used online tools or software to analyze Gene ontology (G ...[more]