Identification of potential driving genes in prostatic cancer using complex network analysis

ABSTRACT

Prostatic cancer is a complex cancer that many factors contribute to. In clinical practice, statins and oral anti-diabetic drugs, is the main adjuvant treatment for prostatic cancer patients. In this paper, a kind of typical complex network – the sample specific network (SSN) was used to screen out differentially expressed genes (DEGs) between prostatic cancer and normal tissue. And by the degree of SSN, driving mutation genes (DMGs) were determined. Pearson correlation coefficient was used to construct SSN, in order to describe the special characteristics of the sample. In this way, people can realise personalised medical service. After the prediction of the degree top 30, top 20, top 10, and top 5 genes, the accuracy of prediction of driving genes with the top 5 genes is the highest. Different single samples of SSN from prostate cancer have specificity, but there is a common edge or network with the specific subnetwork of driving gene. The driving genes of prostate cancer can be predicted by our method.

KEYWORDS:

• Prostatic cancer
• driving genes
• complex network
• personalised medical service

Acknowledgments

The authors wish to acknowledge reviewers, for their help in checking the outcome of this study and giving some effective suggestions. And the authors hope to acknowledge cats they met in life, including XiaoJu, Niaoniao, XiaoJinggai and others, for their support and encouragement.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

TaekWon Zeyuan Song

Taekwon Zeyuan Song now is a graduate student in Shandong University(Weihai), before that he obtained his bachelor degree of statistics. His research area is biostatistics, PDEs and computational science.

Xiao-Cong Zhen

Xiao-Cong Zhen graduated from Shenyang Normal University in mathematics and applied mathematics, where she gained a lot of trainings in applied mathematics. Her research interest is in applied mathematics and graph theory.

Wensuo Gao

Wensuo Gao is a doctor in urology department in Weishan People’s Hospital and has received much experience in clinical practice. He graduated from Weifang Medical University and his research is mainly on urology.

Wenyan Zhu

Wenyan Zhu worked as a gynecologist for almost 30 years in Weishan People’s Hospital. Before that, she studied at Jining Medical University and Weifang Medical University, with specialized in clinical medicine and nursing respectively. Her research is mainly on medical quality management, archival science and informatics.