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

PeerJ

article

Yutao Wang¹  Jianfeng Wang¹  Kexin Yan²  Jiaxing Lin¹  Zhenhua Zheng¹  Jianbin Bi¹ 

[1] Department of Urology, The First Hospital of China Medical University;Department of Dermatology, The First Hospital of China Medical University

关键词: Prostate cancer;    Prognosis factor;    Biomarkers;    GEO;    TCGA;   

DOI  :  10.7717/peerj.8786

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

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.

【 授权许可】

CC BY