J Cancer 2019; 10(22):5469-5482. doi:10.7150/jca.29032
Identification of biomarker microRNA-mRNA regulatory pairs for predicting the docetaxel resistance in prostate cancer
1. Department of Pathology, The Second Affiliated Hospital of Soochow University, Suzhou, China
2. Department of Radiotherapy & Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China
3. Department of Radiation Oncology, The Affiliated Suzhou Science & Technology Town Hospital of Nanjing Medical University, Suzhou, China
4. Department of Thoracic Surgery, Suzhou BenQ Hospital, Suzhou, China
5. Tongda College of Nanjing University of Post and Telecommunications, Yangzhou, China
6. Department of Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China
*These authors contributed equally to this work.
Tu J, Peng Q, Shen Y, Hong Y, Zhu J, Feng Z, Zhou P, Fan S, Zhu Y, Zhang Y. Identification of biomarker microRNA-mRNA regulatory pairs for predicting the docetaxel resistance in prostate cancer. J Cancer 2019; 10(22):5469-5482. doi:10.7150/jca.29032. Available from http://www.jcancer.org/v10p5469.htm
Background: Docetaxel resistance is a cursing problem with adverse effects on the therapeutic efficacy of prostate cancer (PCa), involving interactions among multiple molecular components. Single or limited molecules are not strong enough as prediction biomarkers of drug resistance. Network biomarkers are considered to outperform individual markers in disease characterization.
Methods: In this study, key microRNAs (miRNAs) as biomarkers were identified from the PubMed citations and miRNA expression profiles. Targets of miRNAs were predicted and enriched by biological function analysis. Key target mRNAs of the biomarker miRNAs were screened from protein-protein interaction network and gene expression profiles, respectively. The results were validated by the assessment of their predictive power and system biological analysis.
Results: With this approach, we identified 13 miRNAs and 31 target mRNAs with 66 interactions in the constructed network. Integrative functional enrichment analysis and literature exploration further confirmed that the network biomarkers were highly associated with the development of docetaxel resistance.
Conclusions: The findings from our results demonstrated that the identified network biomarkers provide a useful tool for predicting the docetaxel resistance and may be helpful for serving as prediction biomarkers and therapeutic targets. However, it is necessary to conduct biological experiments for further investigating their roles in the development of docetaxel resistance.
Keywords: Docetaxel resistance, Network biomarkers, Bioinformatics analysis, Prostate cancer