Open Access

Identification of potential diagnostic and prognostic biomarkers for prostate cancer

  • Authors:
    • Qiang Zhang
    • Xiujuan Yin
    • Zhiwei Pan
    • Yingying Cao
    • Shaojie Han
    • Guojun Gao
    • Zhiqin Gao
    • Zhifang Pan
    • Weiguo Feng
  • View Affiliations

  • Published online on: August 16, 2019     https://doi.org/10.3892/ol.2019.10765
  • Pages: 4237-4245
  • Copyright: © Zhang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Prostate cancer (PCa) is one of the most common malignant tumors worldwide. The aim of the present study was to determine potential diagnostic and prognostic biomarkers for PCa. The GSE103512 dataset was downloaded, and the differentially expressed genes (DEGs) were screened. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein‑protein interaction (PPI) analyses of DEGs were performed. The result of GO analysis suggested that the DEGs were mostly enriched in ‘carboxylic acid catabolic process’, ‘cell apoptosis’, ‘cell proliferation’ and ‘cell migration’. KEGG analysis results indicated that the DEGs were mostly concentrated in ‘metabolic pathways’, ‘ECM‑receptor interaction’, the ‘PI3K‑Akt pathway’ and ‘focal adhesion’. The PPI analysis results showed that Golgi membrane protein 1 (GOLM1), melanoma inhibitory activity member 3 (MIA3), ATP citrate lyase (ACLY) and G protein subunit β2 (GNB2) were the key genes in PCa, and the Module analysis revealed that they were associated with ‘ECM‑receptor interaction’, ‘focal adhesion’, the ‘PI3K‑Akt pathway’ and the ‘metabolic pathway’. Subsequently, the gene expression was confirmed using Gene Expression Profiling Interactive Analysis and the Human Protein Atlas. The results demonstrated that GOLM1 and ACLY expression was significantly upregulated (P<0.05) in PCa compared with that in normal tissues. Receiver operating characteristic and survival analyses were performed. The results showed that area under the curve values of these genes all exceeded 0.85, and high expression of these genes was associated with poor survival in patients with PCa. In conclusion, this study identified GOLM1 and ACLY in PCa, which may be potential diagnostic and prognostic biomarker of PCa.

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October 2019
Volume 18 Issue 4

Print ISSN: 1792-1074
Online ISSN:1792-1082

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APA
Zhang, Q., Yin, X., Pan, Z., Cao, Y., Han, S., Gao, G. ... Feng, W. (2019). Identification of potential diagnostic and prognostic biomarkers for prostate cancer. Oncology Letters, 18, 4237-4245. https://doi.org/10.3892/ol.2019.10765
MLA
Zhang, Q., Yin, X., Pan, Z., Cao, Y., Han, S., Gao, G., Gao, Z., Pan, Z., Feng, W."Identification of potential diagnostic and prognostic biomarkers for prostate cancer". Oncology Letters 18.4 (2019): 4237-4245.
Chicago
Zhang, Q., Yin, X., Pan, Z., Cao, Y., Han, S., Gao, G., Gao, Z., Pan, Z., Feng, W."Identification of potential diagnostic and prognostic biomarkers for prostate cancer". Oncology Letters 18, no. 4 (2019): 4237-4245. https://doi.org/10.3892/ol.2019.10765