Journal of Cancer Research and Clinical Oncology

, Volume 143, Issue 12, pp 2571–2579 | Cite as

Identification of prognostic markers of high grade prostate cancer through an integrated bioinformatics approach

  • Hai Huang
  • Qin Zhang
  • Chen Ye
  • Jian-Min Lv
  • Xi Liu
  • Lu Chen
  • Hao Wu
  • Lei Yin
  • Xin-Gang CuiEmail author
  • Dan-Feng XuEmail author
  • Wen-Hui LiuEmail author
Original Article – Clinical Oncology



Prostate cancer is one of the leading causes of cancer death for male. In the present study, we applied an integrated bioinformatics approach to provide a novel perspective and identified some hub genes of prostate cancer.


Microarray data of fifty-nine prostate cancer were downloaded from Gene Expression Omnibus. Gene Ontology and pathway analysis were applied for differentially expressed genes between high and low grade prostate cancer. Weighted gene coexpression network analysis was applied to construct gene network and classify genes into different modules. The most related module to high grade prostate cancer was identified and hub genes in the module were revealed. Ingenuity pathway analysis was applied to check the chosen module’s relationship to high grade prostate cancer. Hub gene’s expression profile was verified with clinical samples and a dataset from The Cancer Genome Atlas project.


3193 differentially expressed genes were filtered and gene ontology and pathway analysis revealed some cancer- and sex hormone-related results. Weighted gene coexpression network was constructed and genes were classified into six modules. The red module was selected and ingenuity pathway analysis confirmed its relationship with high grade prostate cancer. Hub genes were identified and their expression profile was also confirmed.


The present study applied integrate bioinformatics approaches to generate a holistic view of high grade prostate cancer and identified hub genes could serve as prognosis markers and potential treatment targets.


Prostate cancer WGCNA Prognostic marker Gene ontology Pathway analysis Hub gene 



This work was supported by Grants from the National Natural Science Foundation of China (Nos. 81172191; 81602238); the General Program of Shanghai Municipal Commission of Health and Family Planning (No. 201440511); The Key Basic Research Foundation of Shanghai Committee of Science and Technology of China (No. 14JC1491200).

Compliance with ethical standards

Conflict of interest

The authors declare no potential conflicts of interests.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the ethics committee of Shanghai Changzheng Hospital and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.


No funding was received.

Informed consent

Written informed consent was exempted because of the retrospective study design.

Supplementary material

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Department of Urinary Surgery, Ruijin HospitalShanghai Jiaotong University School of MedicineShanghaiChina
  2. 2.Department of Urinary Surgery, Changzheng HospitalSecond Military Medical UniversityShanghaiChina
  3. 3.National Center for Liver CancerShanghaiChina
  4. 4.Department of Urinary Surgery, Changhai HospitalSecond Military Medical UniversityShanghaiChina
  5. 5.BGI-WuhanWuhan BGI Clinical Laboratory Limited CompanyWuhanChina
  6. 6.Department of Urinary Surgery, Third Affiliated HospitalSecond Military Medical UniversityShanghaiChina
  7. 7.Department of Plastic and Reconstructive Surgery, Shanghai Ninth People’s HospitalShanghai Jiao Tong University School of MedicineShanghaiChina

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