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. 2022 Sep 13:13:997842.
doi: 10.3389/fphar.2022.997842. eCollection 2022.

Identification and verification of hub genes associated with the progression of non-small cell lung cancer by integrated analysis

Xie Mengyan  1 , Ding Kun  2   3   4 , Jing Xinming  1 , Wei Yutian  5 , Shu Yongqian  1   4
Affiliations

Identification and verification of hub genes associated with the progression of non-small cell lung cancer by integrated analysis

Xie Mengyan et al. Front Pharmacol. .

Abstract

Objectives: Lung cancer is one of the most common cancers worldwide and it is the leading cause of cancer-related mortality. Despite the treatment of patients with non-small cell lung carcinoma (NSCLC) have improved, the molecular mechanisms of NSCLC are still to be further explored. Materials and Methods: Microarray datasets from the Gene Expression Omnibus (GEO) database were selected to identify the candidate genes associated with tumorigenesis and progression of non-small cell lung carcinoma. The differentially expressed genes (DEGs) were identified by GEO2R. Protein-protein interaction network (PPI) were used to screen out hub genes. The expression levels of hub genes were verified by GEPIA, Oncomine and The Human Protein Atlas (HPA) databases. Survival analysis and receiver operating characteristic (ROC) curve analysis were performed to value the importance of hub genes in NSCLC diagnosis and prognosis. ENCODE and cBioPortal were used to explore the upstream regulatory mechanisms of hub genes. Analysis on CancerSEA Tool, CCK8 assay and colony formation assay revealed the functions of hub genes in NSCLC. Results: A total of 426 DEGs were identified, including 93 up-regulated genes and 333 down-regulated genes. And nine hub genes (CDC6, KIAA0101, CDC20, BUB1B, CCNA2, NCAPG, KIF11, BUB1 and CDK1) were found to increase with the tumorigenesis, progression and cisplatin resistance of NSCLC, especially EGFR- or KRAS-mutation driven NSCLC. Hub genes were valuable biomarkers for NSCLC, and the overexpression of hub genes led to poor survival of NSCLC patients. Function analysis showed that hub genes played roles in cell cycle and proliferation, and knockdown of hub genes significantly inhibited A549 and SPCA1 cell growth. Further exploration demonstrated that copy number alterations (CNAs) and transcription activation may account for the up-regulation of hub genes. Conclusion: Hub genes identified in this study provided better understanding of molecular mechanisms within tumorigenesis and progression of NSCLC, and provided potential targets for NSCLC treatment as well.

Keywords: NSCLC; bioinformatics; biomarker; hub genes; integrated analysis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
A schematic representation of the research methods. Diagram showing the four main modules in this study, including DEGs analysis, DEGs screening, hub genes validation and functional validation.
FIGURE 2
FIGURE 2
Identification of overlapping DEGs and PPI construction of DEGs. (A-C) Volcano plots showing DEGs in NSCLC tissues compared to normal tissues in GSE19804/GSE43458/GSE18842 (|Log2FC| ≥ 2 and p < 0.05). (D and E) Venn diagrams showing the number of overlapping DEGs in the three GEO datasets (D. up-regulated genes E. down-regulated genes). (F) Heatmap of the top representative DEGs (|Log2FC| ≥ 2.5 and p < 0.05). (G) PPI network of DEGs constructed by the String and Cytoscape software. (H) The most significant module of PPI network based on the score of each node. (Red represents up-regulated, blue represents down-regulated).
FIGURE 3
FIGURE 3
mRNA and protein expression changes of hub genes in NSCLC. (A) Boxplots (Red box: tumor tissue; Grey box: normal tissue) showing the expression levels of hub genes based on the TCGA database. The red and grey boxes represent NSCLC and normal tissues, respectively. |Log2FC| cutoff = 1, p value cutoff = 0.05. (B) Rank of hub genes changes in subtypes of NSCLC according to Oncomine database (Red represents up-regulated). |Log2FC| cutoff = 1, p value cutoff = 0.001. (C) Immunohistochemical staining of hub genes in NSCLC tumor cells included in HPA database. (D) The expression of hub genes with the progression of LUAD in GSE84447 dataset: 0- normal lungs (n = 2), one- nonmetastatic primary tumors (n = 10), two- metastatic primary tumors (n = 9),3- macrometastases (n = 9). (E) The expression of hub genes with the progression of LUAD in GSE52248 dataset. Each point represents the average value of the group (each group: n = 6). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.
FIGURE 4
FIGURE 4
The roles of hub genes in LUSC and in EGFR- or KRAS-mutation driven NSCLC. (A) The expression levels of hub genes in different stages of LUSC tumorigenesis (122 samples from 77 patients). (B) The protein expression levels of hub genes in LUSC in CPTAC database. (C) The expression levels of hub genes (BUB1, BUB1B, CDK1, CCNA2 and CDC20) in lung adenocarcinomas identified patients with dismal prognosis. GSE13213: Primary lung cancer: n = 58; PM metastasis: n = 24; LN metastasis: n = 6; Liver metastasis: n = 3; Brain metastasis: n = 9. (D) Heatmap of hub gene expression in KRAS-mutant and KRAS-wild type lung cancer compared to normal lung tissues (GSE31210). Normal lung: n = 20, KRAS MUT: n = 20, KRAS WT: n = 68. (E) Kaplan-Meier analysis of hub genes in LUAD with KRAS mutation from TCGA. (F) Hub gene expression in EGFR-TKI-sensitive and TKI-resistant lung cancer tissues in GSE161584 dataset. (G) Heatmap of hub gene expression in DDP-resistant A549 cells and control cells (GSE108214). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.
FIGURE 5
FIGURE 5
Survival analysis and ROC curve analysis of hub genes in NSCLC. (A) Kaplan-Meier survival curves of OS based on the hub genes (CDC6, KIAA0101, CDC20, BUB1B, CCNA2, NCAPG, KIF11, BUB1, CDK1) expression using the online bioinformatics tool Kaplan-Meier Plotter. (B–F) Individual ROC curve of hub genes according to the chip data of GSE19804, GSE43458 and GSE18842. (G) Combined ROC curve of hub genes according to the chip data of GSE19804, GSE43458 and GSE18842.
FIGURE 6
FIGURE 6
Co-occurrence of hub gene alterations in NSCLC and ChIP-seq of histone and transcription factors in A549 cells. (A) Five pairs of hub genes tending to have concurrent CNAs in NSCLC. (B) The characteristic peaks (fold change over control) of H3K4me3 and H3K27ac at the promoter region of BUB1B, CDC6, CDC20, CDK1, NCAPG and KIF11. (C) The characteristic peaks (fold change over control) of MYC at the promoter region of BUB1B, CDK1 and CCNA2.
FIGURE 7
FIGURE 7
The biological functions of hub genes in NSCLC. (A) The correlation between cell cycle, cell proliferation and hub gene expression at single cell level in NSCLC via CancerSEA database. (B) Correlation between Ki-67, PCNA and hub gene expression based on TCGA-LUAD analysis, n = 526. Statistical significance was tested using Pearson’s correlation coefficient. Correlation scores were analyzed by the Pearson correlation test. (C) Assessment of the proliferation of A549 cells transfected with siRNAs#1 targeting hub genes by CCK8 assay (Left). The inhibition rate of each siRNA#1 on cell proliferation in CCK8 assay (Right). (D) Assessment of the proliferation of SPCA1 cells transfected with siRNAs#1 targeting hub genes by CCK8 assay (Left). The inhibition rate of each siRNA#1 on cell proliferation in CCK8 assay (Right). (E,F) Assessment of the colony formation ability of A549 cells transfected with siRNAs#1 targeting hub genes by colony formation assay. The inhibition rate of each siRNA#1 on colony formation. (G,H) Assessment of the colony formation ability of SPCA1 cells transfected with siRNAs#1 targeting hub genes by colony formation assay. The inhibition rate of each siRNA#1 on colony formation. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.
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