Heterogeneous pattern of gene expression driven by mutation is involved in the construction of a prognosis model of lung squamous cell carcinoma.

OBJECTIVE

To investigate the impact that mutation had on the gene heterogeneity expression and prognosis in patients with lung adenocarcinoma.

METHODS

In this study, the Cancer Genome Atlas (TCGA) dataset was used to analyze the mutations in lung adenocarcinoma. Lung adenocarcinoma data was collected from the TCGA database, clinical information of patients was analyzed, and bioinformatics statistical methods were applied for mutation analysis and prognosis survival analysis. The results were verified using the GEO dataset.

RESULTS

The incidence of mutations in lung adenocarcinoma was found to be 73%, and it was related to the prognosis of lung adenocarcinoma. Ten genes were screened with significant contributions to prognosis. A prognosis model was constructed and verified by LASSO COX analysis in the TCGA and GEO datasets based on these ten beneficial factors. The independent prognostic factor H2BC9 for mutation-driven gene heterogeneity expression was screened through multi-factor COX regression analysis.

CONCLUSION

Our data showed that the gene heterogeneity expression, which was driven by mutations, prolonged the survival of lung adenocarcinoma patients and provided valuable clues for the prognosis of gene mutations in lung adenocarcinoma.