Identification of lung adenocarcinoma biomarkers based on bioinformatic analysis and human samples

Abstract

Lung adenocarcinoma is one of the most common malignant tumors worldwide. Although efforts have been made to clarify its pathology, the underlying molecular mechanisms of lung adenocarcinoma are still not clear. The microarray datasets GSE75037, GSE63459 and GSE32863 were downloaded from the Gene Expression Omnibus (GEO) database to identify biomarkers for effective lung adenocarcinoma diagnosis and therapy. The differentially expressed genes (DEGs) were identified by GEO2R, and function enrichment analyses were conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). The STRING database and Cytoscape software were used to construct and analyze the protein‑protein interaction network (PPI). We identified 376 DEGs, consisting of 83 upregulated genes and 293 downregulated genes. Functional and pathway enrichment showed that the DEGs were mainly focused on regulation of cell proliferation, the transforming growth factor β receptor signaling pathway, cell adhesion, biological adhesion, and responses to hormone stimulus. Sixteen hub genes were identified and biological process analysis showed that these 16 hub genes were mainly involved in the M phase, cell cycle phases, the mitotic cell cycle, and nuclear division. We further confirmed the two genes with the highest node degree, DNA topoisomerase IIα (TOP2A) and aurora kinase A (AURKA), in lung adenocarcinoma cell lines and human samples. Both these genes were upregulated and associated with larger tumor size. Upregulation of AURKA in particular, was associated with lymphatic metastasis. In summary, identification of the DEGs and hub genes in our research enables us to elaborate the molecular mechanisms underlying the genesis and progression of lung adenocarcinoma and identify potential targets for the diagnosis and treatment of lung adenocarcinoma.

Keywords: lung adenocarcinoma; TOP2A; AURKA; biomarker; bioinformatics; human samples.

Figure 1.

Venn diagram, protein-protein interaction network and the most significant components of DEGs. (A) DEGs were selected with P-value <0.05 and a fold change >2 among the mRNA expression profiling sets GSE75037, GSE63459 and GSE32863. These three datasets manifested an overlap of 376 genes. (B) The protein-protein interaction network of DEGs was constructed using Cytoscape software. (C) The most significant components of the DEGs were obtained from protein-protein interaction network with 16 nodes. DEGs, differentially expressed genes.

Figure 2.

Interaction network of the hub genes and the biological process analysis. (A) cBioPortal platform were used to analyze the hub genes and the co-expression genes. The hub genes are marked with a bold outline. Co-expression genes are marked with a thin outline. (B) The plugin of Cytoscape, BiNGO, was adopted to conduct the analysis of biological process. P-value of the ontologies are represented by different color shade. The yellow node indicates higher functional enrichment than white. The numbers of the genes involved in the ontologies are represented by the different size of the node. P<0.05 was considered statistically significant. Interaction network of the hub genes and the biological process analysis. (C) The hub gene alteration rates in lung adenocarcinoma were screened from cBioPortal platform; the red-colored bars represent the upregulation of the gene. (D) The UCSC (University of California Santa Cruz) cancer platform was used to construct the hub gene hierarchical clustering. The primary tumor, recurrent tumor and normal tissue are represented in different colors.

Figure 2.

Interaction network of the hub genes and the biological process analysis. (A) cBioPortal platform were used to analyze the hub genes and the co-expression genes. The hub genes are marked with a bold outline. Co-expression genes are marked with a thin outline. (B) The plugin of Cytoscape, BiNGO, was adopted to conduct the analysis of biological process. P-value of the ontologies are represented by different color shade. The yellow node indicates higher functional enrichment than white. The numbers of the genes involved in the ontologies are represented by the different size of the node. P<0.05 was considered statistically significant. Interaction network of the hub genes and the biological process analysis. (C) The hub gene alteration rates in lung adenocarcinoma were screened from cBioPortal platform; the red-colored bars represent the upregulation of the gene. (D) The UCSC (University of California Santa Cruz) cancer platform was used to construct the hub gene hierarchical clustering. The primary tumor, recurrent tumor and normal tissue are represented in different colors.

Figure 3.

The relationship between alteration of the hub genes and overall survival (A) and disease free survival (B) were explored in the cBioPortal platform. P<0.05 was considered statistically significant. To note, the full names of all the gene symbols used in the figures are listed in Table III.

Figure 3.

The relationship between alteration of the hub genes and overall survival (A) and disease free survival (B) were explored in the cBioPortal platform. P<0.05 was considered statistically significant. To note, the full names of all the gene symbols used in the figures are listed in Table III.

Figure 4.

Expression profiles of (A) TOP2A and (B) AURKA in 20 malignant tumor types are represented using the Oncomine database. The number represent the cases meeting the threshold for TOP2A and AURKA. Heat maps of (C) TOP2A and (D) AURKA gene expression in lung carcinoma samples vs. adjacent lung tissues in the Oncomine database. (C) 1. Lung carcinoma vs. normal lung, Beer et al (2002) (22). 2. Lung carcinoma vs. normal lung, Hou et al (2010) (23). 3. Lung carcinoma vs. normal lung, Landi et al (2008) (24). 4. Lung carcinoma vs. normal lung, Selamat et al (2012) (7). 5. Lung carcinoma vs. normal lung, Su et al (2007) (25). 6. Lung carcinoma vs. normal lung, Yamagata et al (2003) (26). (D) 1. Lung carcinoma vs. normal lung, Bhattacharjee et al (2001) (27). 2. Lung carcinoma vs. normal lung, Garber et al (2001) (28). 3. Lung carcinoma vs. normal lung, Hou et al (2010) (23). 4. Lung carcinoma vs. normal lung, Landi et al (2008) (24). 5. Lung carcinoma vs. normal lung, Selamat et al (2012) (7). 6. Lung carcinoma vs. normal lung, Su et al (2007) (25). The P-value for a gene is its P-value for the median-ranked analysis. The fold change represents the relative expression of the tumor tissue compared with the normal tissue. AURKA, aurora kinase A; TOP2A, DNA topoisomerase II α.

Figure 5.

RT-qPCR to confirm the upregulation of TOP2A and AURKA in lung adenocarcinoma and HBE cell lines and human samples. (A) TOP2A expression in lung adenocarcinoma cell lines A549, HCC827 and H1975 and a human bronchial epithelial (HBE) cell line. (B) AURKA expression in the lung adenocarcinoma cell lines. (C) TOP2A expression in lung adenocarcinoma tissue and non-cancerous lung tissue samples. (D) AURKA expression in lung adenocarcinoma tissue and non-cancerous lung tissue samples. AURKA, aurora kinase A; TOP2A, DNA topoisomerase II α. *P<0.05.