Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jan 29;41(1):BSR20203973.
doi: 10.1042/BSR20203973.

Identification of KIF4A and its effect on the progression of lung adenocarcinoma based on the bioinformatics analysis

Yexun Song  1 , Wenfang Tang  2 , Hui Li  2
Affiliations

Identification of KIF4A and its effect on the progression of lung adenocarcinoma based on the bioinformatics analysis

Yexun Song et al. Biosci Rep. .

Abstract

Background: Lung adenocarcinoma (LUAD) is the most frequent histological type of lung cancer, and its incidence has displayed an upward trend in recent years. Nevertheless, little is known regarding effective biomarkers for LUAD.

Methods: The robust rank aggregation method was used to mine differentially expressed genes (DEGs) from the gene expression omnibus (GEO) datasets. The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to extract hub genes from the protein-protein interaction (PPI) network. The expression of the hub genes was validated using expression profiles from TCGA and Oncomine databases and was verified by real-time quantitative PCR (qRT-PCR). The module and survival analyses of the hub genes were determined using Cytoscape and Kaplan-Meier curves. The function of KIF4A as a hub gene was investigated in LUAD cell lines.

Results: The PPI analysis identified seven DEGs including BIRC5, DLGAP5, CENPF, KIF4A, TOP2A, AURKA, and CCNA2, which were significantly upregulated in Oncomine and TCGA LUAD datasets, and were verified by qRT-PCR in our clinical samples. We determined the overall and disease-free survival analysis of the seven hub genes using GEPIA. We further found that CENPF, DLGAP5, and KIF4A expressions were positively correlated with clinical stage. In LUAD cell lines, proliferation and migration were inhibited and apoptosis was promoted by knocking down KIF4A expression.

Conclusion: We have identified new DEGs and functional pathways involved in LUAD. KIF4A, as a hub gene, promoted the progression of LUAD and might represent a potential therapeutic target for molecular cancer therapy.

Keywords: Bioinformatical analysis; Biomarker; Differentially expressed genes; KIF4A; Lung adenocarcinoma.

PubMed Disclaimer

Conflict of interest statement

The authors declare that there are no competing interests associated with the manuscript.

Figures

Figure 1
Figure 1. Identification of DEGs from GSE85716, GSE32863, and GSE116959 datasets
(A–C) Volcano plot showing the DEGs of the GSE85716, GSE32863, and GSE116959 datasets. (D) Hierarchical clustering comparing the top 20 up-regulated and down-regulated genes in adjacent normal lung tissues and LUAD tissues.
Figure 2
Figure 2. Functional characteristics analyses of robust DEGs
GO enrichment analyses of (A) the up-regulated DEGs and (B) the down-regulated DEGs. KEGG pathway enrichment analyses of (C) the up-regulated DEGs and (D) the down-regulated DEGs.
Figure 3
Figure 3. Establishment of the PPI network and modules analyses of genes in LUAD
(A) The overall PPI network in LUAD. (B) The PPI network of module 1 in LUAD. (C) The PPI network of module 2 in LUAD.
Figure 4
Figure 4. Validation of the expression of seven hub genes in LUAD samples based on the Oncomine database
The expression levels of (A) BIRC5, (B) DLGAP5, (C) CENPF, (D) KIF4A, (E) TOP2A, (F) AURKA, and (G) CCNA2 in LUAD were obtained from the Oncomine database.
Figure 5
Figure 5. Identification of the expression of the seven hub genes in LUAD samples in the TCGA database
Box plots show the expression of (A) BIRC5, (B) DLGAP5, (C) CENPF, (D) KIF4A, (E) TOP2A, (F) AURKA, and (G) CCNA2 in LUAD from the TCGA database. *P<0.05.
Figure 6
Figure 6. Overall survival analyses of the seven hub genes in LUAD on the basis of the TCGA and GTEx data in GEPIA
Statistical graphs indicate the results of overall survival analyses of (A) BIRC5, (B) DLGAP5, (C) CENPF, (D) KIF4A, (E) TOP2A, (F) AURKA, and (G) CCNA2 in LUAD. Red lines represent the high expression of genes and the blue lines represent low expression of genes.
Figure 7
Figure 7. Disease-free survival analyses of the seven hub genes in LUAD based on TCGA and GTEx data in GEPIA
In accordance with the TCGA and GTEx data in GEPIA, the disease-free survival of the seven hub genes are shown: (A) BIRC5, (B) DLGAP5, (C) CENPF, (D) KIF4A, (E) TOP2A, (F) AURKA, and (G) CCNA2.
Figure 8
Figure 8. CENPF, DLGAP5, and KIF4A expression was positively correlated with the clinical stage of LUAD
The levels of CENPF, DLGAP5, and KIF4A expression were analyzed in different stages of LUAD.
Figure 9
Figure 9. KIF4A was significantly up-regulated in LUAD cells
(A) mRNA expression levels of KIF4A in the LUAD cells were higher than those in normal bronchial epithelial cells. (B) Expression of KIF4A protein in the LUAD cell lines was higher than in normal bronchial epithelial cells. (C) The protein expression levels of KIF4A targeted by siRNA-1, siRNA-2, and siRNA-3. *, P-value<0.05; **, P-value<0.01.
Figure 10
Figure 10. Silencing KIF4A inhibited proliferation, migration, and promoted apoptosis in the A549 cell line
(A and B) Silencing KIF4A suppressed the migration of A549 cells. (C and D) KIF4A knockdown decreased cell proliferation capacity of A549 cells. (E and F) KIF4A knockdown promoted the apoptotic rate of A549 cells; *, P-value<0.05.
See this image and copyright information in PMC

References

    1. Gazdar A.F. and Zhou C. (2018) Lung cancer in never-smokers: a different disease. IASLC Thoracic Oncology, pp. 23.e3–29.e3, Elsevier
    1. Torre L.A., Siegel R.L. and Jemal A. (2016) Lung cancer statistics. Lung Cancer and Personalized Medicine, pp. 1–19, Springer; 10.1007/978-3-319-24223-1_1 - DOI - PubMed
    1. Oser M.G., Niederst M.J., Sequist L.V. and Engelman J.A. (2015) Transformation from non-small-cell lung cancer to small-cell lung cancer: molecular drivers and cells of origin. Lancet Oncol. 16, e165–e172 10.1016/S1470-2045(14)71180-5 - DOI - PMC - PubMed
    1. Hirsch F.R., Suda K., Wiens J. and Bunn P.A. Jr (2016) New and emerging targeted treatments in advanced non-small-cell lung cancer. Lancet North Am. Ed. 388, 1012–1024 10.1016/S0140-6736(16)31473-8 - DOI - PubMed
    1. Liu Z., Liu B. and Li C. (2019) A case report of metastatic bilateral ovarian cancer due to non-small cell lung cancer with ALK gene rearrangement. Eur. J. Gynaecol. Oncol. 40, 151–153

Publication types