Identification and characterization of biomarkers and their functions for docetaxel‑resistant prostate cancer cells

Deng,Leihong; Gu,Xiaopeng; Zeng,Tao; Xu,Fanghua; Dong,Zhifeng; Liu,Chao; Chao,Haichao

doi:10.3892/ol.2019.10623

Identification and characterization of biomarkers and their functions for docetaxel‑resistant prostate cancer cells

Authors:
- Leihong Deng
- Xiaopeng Gu
- Tao Zeng
- Fanghua Xu
- Zhifeng Dong
- Chao Liu
- Haichao Chao
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Affiliations: Medical Department of The Graduate School, Nanchang University, Nanchang, Jiangxi 330006, P.R. China, Department of Orthopedics, Zhoushan Guhechuan Hospital, Zhoushan, Zhejang 316000, P.R. China, Department of Urology, Jiangxi Provincial People's Hospital Affiliated to Nanchang University, Nanchang, Jiangxi 330006, P.R. China, Pathology Department, Jiangxi Provincial People's Hospital Affiliated to Nanchang University, Nanchang, Jiangxi 330006, P.R. China, Laboratory of Clinical Medicine, Jiangxi Provincial People's Hospital Affiliated to Nanchang University, Nanchang, Jiangxi 330006, P.R. China
Published online on: July 16, 2019 https://doi.org/10.3892/ol.2019.10623
Pages: 3236-3248
Copyright: © Deng et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Docetaxel treatment is a standard chemotherapy strategy for castration‑resistant prostate cancer (CRPC), and patients with CRPC eventually develop resistance to treatment. However, little is understood regarding the underlying mechanism of resistance. The present study aimed to identify the underlying crucial genes and regulatory networks associated with docetaxel resistance in prostate cancer using bioinformatics analyses. For this purpose, one expression profile dataset (GSE33455), which included two docetaxel‑sensitive and two docetaxel‑resistant cell lines, was downloaded from the Gene Expression Omnibus database, and analyses of differential gene expression and function enrichment were performed. A protein‑protein interaction (PPI) network was constructed, and the associated hub genes were investigated using the Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape software. A total of 756 differentially expression genes (DEGs) were identified, including 509 downregulated and 247 upregulated genes. Enrichment analysis revealed that the DEGs were associated with the interferon‑γ‑mediated signaling pathway, protein binding, bicellular tight junctions and cancer pathways. Two modules were screened from the PPI network, and the corresponding genes were identified to be largely enriched in the interferon‑γ‑mediated signaling pathway and the negative regulators of the DExD/H‑Box helicase 58/interferon induced with helicase C domain 1 signaling pathway, and enriched in cell‑cell adhesion and the Rap1 signaling pathway. Among the ten hub genes, epidermal growth factor receptor, spleen tyrosine kinase (SYK), intracellular adhesion molecule 1 (ICAM1), interleukin (IL)6, CXC motif chemokine ligand 8 (CXCL8), cyclin dependent kinase 1 and CD44 molecule (CD44) were significantly differentially expressed in prostate cancer tissues compared with healthy tissues based on The Cancer Genome Atlas data. The Gene Expression Profiling Interactive Analysis database revealed that ICAM1 was positively associated with IL6 and CXCL8, and epidermal growth factor receptor was positively associated with CD44 and SYK. Additionally, ten hub genes, which were identified to be associated with the drug resistance of docetaxel in prostatic carcinoma in the present study, were predominantly associated with tumor progression and metastasis. Reverse transcription‑quantitative PCR analysis performed on docetaxel‑sensitive and docetaxel‑resistant prostate cancer cell lines demonstrated that certain hub genes, including CDK1, 2'‑5'‑oligoadenylate synthetase 3, CXCL8 and CDH1, were highly expressed in the docetaxel‑resistant cell lines, which confirmed the bioinformatics results. In conclusion, the present study identified a number of important genes that are associated with the molecular mechanism of docetaxel resistance by integrated bioinformatical analysis, and these genes and regulatory networks may assist with identifying potential gene therapy targets for CRPC. Further functional analyses are required to validate the current findings.

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