Bioinformatic analysis reveals novel biomarkers and candidate drug compositions in prostate cancer

Journal Title: TMR Integrative Medicine - Year 2020, Vol 4, Issue 4

Abstract

As prostate cancer (PC) patients do more and more genome sequencing, we can predict prognosis through individual oncogenic mutations. Although great success have been made to clarify the incidence of PC, the mechanisms was not completely understood. Recurrence and metastasis of PC remains to be resolved, and novel therapeutic targets need to be found urgently. Microarray datasets GSE6919, GSE55945 and GSE46602 about the PC tissues vs. normal organizations, were obtained from Gene Expression Omnibus. In this study, 86 differentially expressed genes were determined having more important clinical significance in the process of PC. 29 hub genes significantly enriched in biological processes were analyzed using Cytoscape. The function of these hub genes included the effect of cellular process, skeletal system development, cholesterol transport, regulation of protein oligomerization and cellular component biogenesis, enzyme inhibitor activity and so on. The three of these hub genes were picked out because of their relationships, which can be used as a potential target for the diagnosis and the direction of therapy. And drug predictions were designed for these candidate target molecules, providing direction for future treatment of PC.

Authors and Affiliations

Yi-Dan Sun, Ying Zhang, Shi-Qi Ren, Zi-Heng Wang, Pei-Ying Yang, Ying-Jie Jia

Keywords

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  • EP ID EP678611
  • DOI 10.12032/TMRIM202004004
  • Views 260
  • Downloads 0

How To Cite

Yi-Dan Sun, Ying Zhang, Shi-Qi Ren, Zi-Heng Wang, Pei-Ying Yang, Ying-Jie Jia (2020). Bioinformatic analysis reveals novel biomarkers and candidate drug compositions in prostate cancer. TMR Integrative Medicine, 4(4), -. https://europub.co.uk/articles/-A-678611