Bioinformatics Analysis of Differential Gene and MicroRNA Expression in Lung Adenocarcinoma: Genetic Effects on Patient Prognosis, as Indicated by the TCGA Database

Objective: To investigate the differential expression of genes and microRNAs (miRNAs) in patients with lung adenocarcinoma and the relationship between such changes and patient prognosis. Methods: We analyzed the expression levels of genes and miRNAs in lung adenocarcinoma tissues and adjacent normal tissues using The Cancer Genome Atlas database (TCGA). We analyzed the function of the differentially expressed genes and miRNAs in a co-expression network. Finally, we performed survival analysis of differential genes and miRNAs in the co-expression network using clinical data from the TCGA database. Results: We successfully identified 6064 differentially expressed genes: 5324 upregulated genes and 740 downregulated genes. And we identified 161 differentially expressed miRNAs: 126 upregulated miRNAs and 35 downregulated miRNAs. We identified several genes that were related to each other in the co-expression network. Further analysis revealed that the high expression levels of G6PC, APOB, F2, PAQR9, and PAQR9-AS1 genes were associated with poor prognosis. However, there was no significant correlation between the expression of hsa-mir-122 with regards to patient prognosis. Conclusions: Our data showed that hsa-mir-122 and a number of related genes may affect the prognosis of patients with lung adenocarcinoma by regulating the cytoskeleton, thus promoting tumor angiogenesis and the metastasis of tumor cells. The high expression levels of some differentially expressed genes was associated with the low survival rate in patients with lung adenocarcinoma. However, the levels of hsa-mir-122 were not correlated with patient prognosis.