Transcriptomic data exploration of consensus genes and molecular mechanisms between chronic obstructive pulmonary disease and lung adenocarcinoma

Abstract

Most current research has focused on chronic obstructive pulmonary disease (COPD) and lung adenocarcinoma (LUAD) alone; however, it is important to understand the complex mechanism of COPD progression to LUAD. This study is the first to explore the unique and jointly molecular mechanisms in the pathogenesis of COPD and LUAD across several datasets based on a variety of analysis methods. We used weighted correlation network analysis to search hub genes in two datasets from public databases: GSE10072 and GSE76925. We explored the unique and jointly molecular mechanistic signatures of the two diseases in pathogenesis through enrichment analysis, immune infiltration analysis, and therapeutic targets analysis. Finally, the results were confirmed using real-time quantitative reverse transcription PCR. Fifteen hub genes were identified: GPI, EZH2, EFNA4, CFB, ENO1, SH3PXD2B, SELL, CORIN, MAD2L1, CENPF, TOP2A, ASPM, IGFBP2, CDKN2A, and ELF3. For the first time, SELL, CORIN, GPI, and EFNA4 were found to play a role in the etiology of COPD and LUAD. The LUAD genes identified were primarily involved in the cell cycle and DNA replication processes; COPD genes we found were related to ubiquitin-mediated proteolysis, ribosome, and T/B-cell receptor signaling pathways. The tumor microenvironment of LUAD pathogenesis was influenced by CD4 + T cells, type 1 regulatory T cells, and T helper 1 cells. T follicular helper cells, natural killer T cells, and B cells all impact the immunological inflammation in COPD. The results of drug targets analysis suggest that cisplatin and tretinoin, as well as bortezomib and metformin may be potential targeted therapy for patients with COPD combined LUAD. These signatures may be provided a new direction for developing early interventions and treatments to improve the prognosis of COPD and LUAD.

Figure 1

A flowchart showing all the steps involved in our analysis.

Figure 2

(A), the PCA plots showed a clear separation in two datasets. Blue spots represent the control group, and red spots represent the healthy people group. (B), volcano graph shows the differential gene expression, upregulated (blue box), downregulated (red box), and unchanged (gray boxes) transcripts. (C), KEGG pathway analysis for the target genes of the Important modules. COPD: chronic obstructive pulmonary disease; LUAD: lung adenocarcinoma; KEGG: Kyoto Encyclopedia of Genes and Genomes.

Figure 3

(A), the clustering dendrogram of genes. Disease-specific candidate genes with the same functions are denoted by the same color. Gray color denotes genes with unknown function. (B), Scatter plot between genes and diseases in important modules. (C), Heatmap of module–trait relationships between module genes and clinical traits. In the consensus module, If the two diseases presented similarly in the same clinical trait, the same color was applied to both modules; if the presentation of the diseases was different, then the module was colored gray. COPD: chronic obstructive pulmonary disease; LUAD: lung adenocarcinoma.

Figure 4

(A), the abundance of differentially expressed immune cells in COPD. (B), the abundance of differentially expressed immune cells in LUAD. Green represents the control group, and red represents COPD patients. COPD: chronic obstructive pulmonary disease; LUAD: lung adenocarcinoma; HC: control group.

Figure 5

Candidate disease-specific drug-target networks. Label targets and drugs are colored black and turquoise, respectively. The size of the drug letters reveals the degree of the drug. (A), Candidate drug-target network of COPD blue module; (B), Candidate drug-target network of COPD-LUAD turquoise module; (C), Candidate drug-target network of LUAD blue module; (D), Candidate drug-target network of the LUAD turquoise module. COPD: chronic obstructive pulmonary disease; LUAD: lung adenocarcinoma.

Figure 6

(A), RT–qPCR was used to detect the expression of different genes in LUAD and normal cells. (B), RT–qPCR was used to detect the expression of different genes in COPD and normal cells. “*” p < 0.05, “**” p < 0.01, “***” p < 0.001. COPD: chronic obstructive pulmonary disease; LUAD: lung adenocarcinoma; RT-qPCR: Real-time quantitative reverse transcription PCR.