Identification of core genes associated with prostate cancer progression and outcome via bioinformatics analysis in multiple databases

Abstract

The morbidity and mortality of prostate carcinoma has increased in recent years and has become the second most common ale malignant carcinoma worldwide. The interaction mechanisms between different genes and signaling pathways, however, are still unclear. Methods Variation analysis of GSE38241, GSE69223, GSE46602 and GSE104749 were realized by GEO2R in Gene Expression Omnibus database. Function enrichment was analyzed by DAVID.6.8. Furthermore, the PPI network and the significant module were analyzed by Cytoscape, STRING and MCODE.GO. Pathway analysis showed that the 20 candidate genes were closely related to mitosis, cell division, cell cycle phases and the p53 signaling pathway. A total of six independent prognostic factors were identified in GSE21032 and TCGA PRAD. Oncomine database and The Human Protein Atlas were applied to explicit that six core genes were over expression in prostate cancer compared to normal prostate tissue in the process of transcriptional and translational. Finally, gene set enrichment were performed to identified the related pathway of core genes involved in prostate cancer. Result Hierarchical clustering analysis revealed that these 20 core genes were mostly related to carcinogenesis and development. CKS2, TK1, MKI67, TOP2A, CCNB1 and RRM2 directly related to the recurrence and prognosis of prostate cancer. This result was verified by TCGA database and GSE21032. Conclusion These core genes play a crucial role in tumor carcinogenesis, development, recurrence, metastasis and progression. Identifying these genes could help us to understand the molecular mechanisms and provide potential biomarkers for the diagnosis and treatment of prostate cancer.

Environmental Phenol and Paraben Exposure Risks and Their Potential Influence on the Gene Expression Involved in the Prognosis of Prostate Cancer

“…In Ref. [ 84 ], it was reported that UBE2C, TOP2A, and CCNB1 were associated with PCa prognosis and higher expression in PCa samples than in normal tissues. RRM2 is associated with poor overall survival of breast cancer patients and can become a useful target for diagnosing and treating patients [ 74 ].…”

“…RRM2 is associated with poor overall survival of breast cancer patients and can become a useful target for diagnosing and treating patients [ 74 ]. Ubiquitin-conjugating enzyme E2C (UBE2C) was highly expressed in PCa compared with normal tissue in TCGA; the expression was also more highly associated with the Gleason score (>7) of PCa, which plays as an independent prognostic factor of PCa, and recreated a critical role in the pathway of PCa (WNT-β-catenin signaling pathway and NOTCH signaling pathway) [ 84 ]. Moreover, UBE2C was reported high in breast cancer, indicated to be an independent prognostic factor connected with the recurrence and death, and associated with a shorter survival period of breast cancer patients.…”

Identification of UBE2C as hub gene in driving prostate cancer by integrated bioinformatics analysis

“…Cytoscape functioned as a network graph, with differential expressed molecules represented as nodes and intermolecular interactions represented as links, that is, edges, between nodes [ 11 ]. In this study, the combined score represented intermolecular interactions and the protein pairs with combined score > 0.4 were selected to construct the PPI network [ 21 ]. Nodes were drawn in different sizes and colors, which represented the node degree and the regulation (up or down), respectively [ 18 ].…”

Identification of crucial genes and pathways associated with prostate cancer in multiple databases

“…Because of high-throughput sequencing technology and bioinformatics methods, it is easier to screen for differentially expressed genes (DEGs) to discover inner signaling networks and relationships between genes. 4 Fibroblast growth factor 2 ( FGF2 ), 5 cyclin kinase subunit 2 ( CKS2 ), 6 RING finger protein 7 ( RNF7 ), 7 cyclin-dependent kinase 1 ( CDK1 ), 8 and other core genes were screened out based on their significant effects on the development and progression of PCa. However, several studies have indicated that there are clear differences among them.…”