Survival prediction model for non-small cell lung cancer based on somatic mutations.

Background: The 5-year survival rate of non-small cell lung cancer (NSCLC) is only 15%. Screening some combined gene mutations could predict the survival of NSCLC patients and also provide new ideas for the diagnosis and treatment of NSCLC. The present study aimed to identify signature mutations for survival prediction of NSCLC.

Methods: Clinical and gene mutation information for 949 NSCLC patients was downloaded from TCGA. High frequency mutation and common mutation genes were analyzed based on 1000 cancer related genes. The LASSO-COX model was used to screen gene mutation points and analyze their survival, and then a survival prediction model was established. Fifty NSCLC patients were collected and 1000 targeted genes were enriched by targeted next generation sequencing. The results were used to verify the combination of common mutation genes and the function of the survival model, and then to clarify their clinical significance.

Results: Ten variables were screened out after LASSO-COX analysis, including age, tumor stage, EGFR c.[2,573 T>G], PIK3CA c.[1624G>A], TP53 c.[375G>T], TP53 c.[527G>T], TP53 c.[733G>T], TP53 c.[734G>T], TP53 c.[743G>T], NFE2L2 c.[100C>G]. Except for TP53 c.[743G>T] and NFE2L2 c.[100C>G], the residual six hot spot mutations of EGFR, PIK3CA and TP53 could be regarded as a signature mutations for forecasting the survival time of NSCLC.

Conclusions: The combination of six hot spot mutations of EGFR, PIK3CA and TP53 is expected to be used for predicting the survival time of NSCLC.