Relationship between the efficacy of immunotherapy and characteristics of specific tumor mutation genes in non-small cell lung cancer patients.

Background Immune checkpoint inhibitors (ICIs) have greatly improved the prognosis and overall management of non-small cell lung cancer (NSCLC) patients, but in the long term less than 20% of patients benefit from treatment with ICIs. Therefore, it is necessary to guide the choice of immunotherapy population through biomarkers in order to maximize the benefit for NSCLC patients. This article mainly explores the relationship between the efficacy of immunotherapy and specific tumor mutation gene characteristics in an NSCLC population. Methods This was a prospective analysis of patients with advanced NSCLC who visited the Department of Respiratory Medicine of Peking Union Medical College Hospital from March 2018 to June 2019 and were instructed to use PD-1 inhibitors. The follow-up deadline was 31 December 2019. The tumor pathological tissues were tested for tumor mutation genes, and the patients were evaluated for efficacy according to RECIST 1.1. The patients were divided into the durable benefit group (DCB) and the nonsustainable benefit group (NDB). DCB/NDB was used as the outcome variable. Various statistics methods were used to explore the independent predictors of long-term benefits associated with immunotherapy and to draw a progression-free survival curve for the relevant predictors. Results A total of 44 patients were examined for tumor mutation genes in pathological tissues; 20 in the DCB group and 24 in the NDB group. Specific gene mutations occurred in TP53 38.64%, KRAS 31.82%, EGFR 20.45%, BRCA 20.45%, ERBB (excluding EGFR) 18.18%, PTEN 15.91%, CDK4/6 13.64%, POLE 11.36%, MET 11.36%, PIK3CA 9.10%, FGFR 9.10%, BRAF 9.10%, JAK 9.10%, ALK 6.82%, POLD1 4.55%, BLM 4.55%. Chi-square test results showed that there were statistically significant differences between DCB and NDB groups with eight mutations such as KRAS. Logistic regression showed that the KRAS mutation was statistically significant (P < 0.001). Two accuracy indicators, Random Forest Classification of Mean Decrease Gini and Mean Decrease Accuracy, evaluated the importance of the impact of different gene mutations on the outcome. Under two different measures, the variables were all KRAS mutations. It is suggested that the mutation of the KRAS gene is an independent predictor of the long-term benefit of immunotherapy. Conclusions The mutation of KRAS gene in tumor tissues is an independent predictor of the long-term benefit of immunotherapy, and the predictive ability is better.