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Identification of key genes in benign prostatic hyperplasia using bioinformatics analysis

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Abstract

Purpose

This study aimed to identify differentially expressed genes (DEGs) and pathways in benign prostatic hyperplasia (BPH) by comprehensive bioinformatics analysis.

Methods

Data of the gene expression microarray (GSE6099) were downloaded from GEO database. DEGs were obtained by GEO2R. Functional and enrichment analyses of selected genes were performed using DAVID database. Protein–protein interaction network was constructed through STRING. Anterior gradient 2 (ARG2) and lumican (LUM) staining in paraffin-embedded specimens from BPH and normal prostate (NP) were detected by immunohistochemistry (IHC). Differences between groups were analyzed by the Student’s t test.

Results

A total of 24 epithelial DEGs and 39 stromal DEGs were determined. The GO analysis results showed that epithelial DEGs between BPH and NP were enriched in biological processes of glucose metabolic process, glucose homeostasis and negative regulation of Rho protein signal transduction. For DEGs in stroma, enriched biological processes included response to ischemia, antigen processing and presentation, cartilage development, T cell costimulation and energy reserve metabolic process. ARG2, as one of the epithelial DEGs, was mainly located in epithelial cells of prostate. In addition, LUM is primarily expressed in the stroma. We further confirmed that compared with NP, the BPH have the lower ARG2 protein level (p = 0.029) and higher LUM protein level (p = 0.003) using IHC.

Conclusions

Our study indicated that there are possible differentially expressed genes in epithelial and stromal cells, such as ARG2 and LUM, which may provide a novel insight for the pathogenesis of BPH.

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Data availability

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Code availability

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Acknowledgements

The authors are very grateful to the urology department of Beijing Tongren Hospital for their selfless help in this work.

Funding

This work was supported by the National Natural Science Foundation of China (Grant No. 81772698 to Hao Ping) and the Open Research Fund from Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beijing Tongren Hospital, Beihang University and Capital Medical University (Grant No. BHTR-KFJJ-202005 to Hao Ping).

Author information

Authors and Affiliations

  1. Department of Urology, Beijing Tongren Hospital, Capital Medical University, No1. Dongjiaomingxiang Street, Dongcheng District, Beijing, 100730, China

    Peng Xiang, Dan Liu, Di Guan, Zhen Du, Wei Yan, Mingdong Wang & Hao Ping

  2. Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University and Capital Medical University, Beijing Tongren Hospital, Beijing, 100730, China

    Peng Xiang & Hao Ping

  3. Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China

    Yongxiu Hao

Authors
  1. Peng Xiang
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  2. Dan Liu
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  3. Di Guan
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  4. Zhen Du
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  5. Yongxiu Hao
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  6. Wei Yan
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  7. Mingdong Wang
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  8. Hao Ping
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Contributions

HP: protocol/project development. PX, MDW and DL: data collection or management. WY, ZD, DG, PX and YXH: data analysis. PX and HP: manuscript writing/editing.

Corresponding author

Correspondence to Hao Ping.

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All the authors declare that there are no conflict of interests.

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This study has been approved by the appropriate ethics committee.

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Xiang, P., Liu, D., Guan, D. et al. Identification of key genes in benign prostatic hyperplasia using bioinformatics analysis. World J Urol 39, 3509–3516 (2021). https://doi.org/10.1007/s00345-021-03625-5

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  • DOI: https://doi.org/10.1007/s00345-021-03625-5

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