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. 2021 Dec;12(1):5149-5161.
doi: 10.1080/21655979.2021.1960775.

Identification of candidate biomarkers correlated with poor prognosis of breast cancer based on bioinformatics analysis

Gang Chen  1 , Mingwei Yu  2 , Jianqiao Cao  1 , Huishan Zhao  3 , Yuanping Dai  4 , Yizi Cong  1 , Guangdong Qiao  1
Affiliations

Identification of candidate biomarkers correlated with poor prognosis of breast cancer based on bioinformatics analysis

Gang Chen et al. Bioengineered. 2021 Dec.

Abstract

Breast cancer (BC) is a malignancy with high incidence among women in the world. This study aims to screen key genes and potential prognostic biomarkers for BC using bioinformatics analysis. Total 58 normal tissues and 203 cancer tissues were collected from three Gene Expression Omnibus (GEO) gene expression profiles, and then the differential expressed genes (DEGs) were identified. Subsequently, the Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway were analyzed to investigate the biological function of DEGs. Additionally, hub genes were screened by constructing a protein-protein interaction (PPI) network. Then, we explored the prognostic value and molecular mechanism of these hub genes using Kaplan-Meier (KM) curve and Gene Set Enrichment Analysis (GSEA). As a result, 42 up-regulated and 82 down-regulated DEGs were screened out from GEO datasets. The DEGs were mainly related to cell cycles and cell proliferation by GO and KEGG pathway analysis. Furthermore, 12 hub genes (FN1, AURKA, CCNB1, BUB1B, PRC1, TPX2, NUSAP1, TOP2A, KIF20A, KIF2C, RRM2, ASPM) with a high degree were identified initially, among which, 11 hub genes were significantly correlated with the prognosis of BC patients based on the Kaplan-Meier-plotter. GSEA reviewed that these hub genes correlated with KEGG_CELL_CYCLE and HALLMARK_P53_PATHWAY. In conclusion, this study identified 11 key genes as BC potential prognosis biomarkers on the basis of integrated bioinformatics analysis. This finding will improve our knowledge of the BC progress and mechanisms.

Keywords: Bioinformatics; breast cancer; gene expression omnibus; hub genes; prognosis biomarker.

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Conflict of interest statement

No potential conflict of interest was reported by the author(s).

Figures

Figure 1.
Figure 1.
DEGs of three GEO profiles
Figure 2.
Figure 2.
GO function and KEGG pathway analysis of DEGs
Figure 3.
Figure 3.
PPI analysis of hub genes of DEGs
Figure 4.
Figure 4.
Expression validation of 13 hub targets in BC compared with adjacent tissues from TCGA data sets
Figure 5.
Figure 5.
Non-hub genes validation in BC compared with adjacent tissues from patients
Figure 6.
Figure 6.
The prognostic gene signature of hub genes in the BC patients
Figure 7.
Figure 7.
Enrichment plots from GSEA
See this image and copyright information in PMC

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This work was supported by Shandong Medical and Health Science and Technology Development Project [202004081034].