Bioinformatic analysis of differentially expressed genes in lung cancer bone metastasis and their implications for disease progression in lung cancer patients

Background: Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related death worldwide. Moreover, it is highly susceptible to distant metastasis, which is the main cause of pain in advanced lung cancer, and frequently occurs in the bone. This study aimed to identify the differentially expressed genes (DEGs) related to metastatic bone disease in lung cancer using bioinformatics methods and to analyze the risk factors influencing the incidence of secondary bone metastasis in lung cancer. Methods: Gene expression profiles from the GSE175601 and GSE10799 datasets in the Gene Expression Omnibus (GEO) database were analyzed to screen for the DEGs associated with lung cancer bone metastasis. The STRING database was used to construct a protein-protein interaction (PPI) network, and the MCODE plugin was used to identify the key genes. The expression of these important genes in lung tumor tissues and their correlation with prognosis were validated in The Cancer Genome Atlas (TCGA) database. An examination of clinical data from patients diagnosed with stage IV lung adenocarcinoma treated at the Anhui No. 2 Provincial People's Hospital was conducted. Immunohistochemistry was used to examine the expression of key genes in lung cancer tumor tissues. A binary logistic regression analysis was conducted to examine the interactions in the expression of critical genes associated with bone metastasis in lung carcinoma patients. Results: In total, 59 DEGs were identified in the GSE175601 and GSE10799 datasets through Venn diagram construction. The PPI network analysis revealed two significant modules and eight candidate genes ( LAPTM5 , LCP2, , CD53, , ARHGAP25, , C1QA, , DES, , MYH11, , and VIM ). According to TCGA database analysis, in carcinogenic tissues of the lung, the expression of these eight critical genes is downregulated. Further, only the lung cancer patients who had high expressions of ARHGAP25 had an improved progress- free interval (PFI) (P<0.05), disease-specific survival (DSS), and overall survival (OS). Of the 49 with stage IV lung adenocarcinoma patients included in the study, 27 (55. 10%) developed bone metastasis. The immunohistochemical (IHC) results indicated that the expression score of ARHGAP25 was significantly lower in the group with bone metastasis (3.93 +/- 2.95) than the group without bone metastasis (6.64 +/- 3.62) (P=0.006). The proportion of patients with low ARHGAP25 expression was significantly higher in the group with bone metastasis (70.37%, 19/27) than the group without bone metastasis (31.82%, 7/22) (P=0.007). The binary logistic regression analysis identified serum alkaline phosphatase (ALP) and ARHGAP25 expression levels as independent risk factors for the occurrence of secondary bone metastatic disease in lung carcinoma patients. Conclusions: The key gene ARHGAP25 identified through bioinformatics for lung cancer bone metastasis was significantly downregulated. Its low expression constitutes an independent risk factor for secondary bone metastatic disease in patients with lung carcinoma.