Construction of an Mutation and Immune-Related Prognostic Prediction Model in Lung Adenocarcinoma.

BACKGROUND

mutation in LUAD affects immune cell infiltration in tumor tissue, and is associated with tumor prognosis.

OBJECTIVE

This study aimed to construct a mutation and immune-related LUAD prognostic model.

MATERIALS AND METHODS

The mutation frequency of in LUAD was queried via cBioPortal in TCGA and PanCancer Atlas databases. The degree of immune infiltration was analyzed by CIBERSORT analysis. DEGs in mut and wt samples were analyzed. Metascape, GO and KEGG methods were adopted for functional and signaling pathway enrichment analysis of DEGs. Genes related to immune were overlapped with DEGs to acquire immune-related DEGs, whose Cox regression and LASSO analyses were employed to construct prognostic model. Univariate and multivariate Cox regression analyses verified the independence of riskscore and clinical features. A nomogram was established to predict the OS of patients. Additionally, TIMER was introduced to analyze relationship between infiltration abundance of 6 immune cells and expression of feature genes in LUAD.

RESULTS

The mutation frequency of in LUAD was 16%, and the degrees of immune cell infiltration were different between the wild-type and mutant . DEGs of mutated and unmutated LUAD samples were mainly enriched in immune-related biological functions and signaling pathways. Finally, 6 feature genes were obtained, and a prognostic model was established. Riskscore was an independent immuno-related prognostic factor for LUAD. The nomogram diagram was reliable.

CONCLUSION

Collectively, genes related to mutation and immunity were mined from the public database, and a 6-gene prognostic prediction signature was generated.