阿替唑单抗
医学
STK11段
肿瘤科
内科学
突变
人口
基因突变
生存分析
癌症研究
作者
Haiyong Wang,Haiyong Wang,Jun Guo,Xiao Han,Chenglong Zhao,Huijuan Li,Zhehai Wang
出处
期刊:Lung Cancer
[Elsevier BV]
日期:2021-01-01
卷期号:151: 76-83
被引量:5
标识
DOI:10.1016/j.lungcan.2020.11.006
摘要
Abstract
Background
Non-small cell lung cancer (NSCLC) patients with high expression of PDL1 are more likely to benefit from atezolizumab. There are no relevant research focusing on the relationship between the PDL1 expression and clinical variables and gene mutation types among NSCLC patients. Methods
NSCLC patients with confirmed PDL1 expression and gene mutation information from OAK study were included in our study. Logistic regression proportional model was applied to analyze the risk factors on PDL1 high expression. The biomarker evaluable population (BEP) was screened to analyze the gene mutation informaion among these patients. High frequency gene mutations were screened based on different PDL1 expressions. Moreover, the log rank test was applied to analyze the overall survival (OS) difference based on different gene mutation types. Results
A total of 838 patients with NSCLC were included in our study. White patients are more likely to have PDL1 ≥ 1% (P = 0.004). ERBB4, EP300, PREX2, SLIT2, EPHB1 and IGF2R mutations were high frequency mutations in patients with high PDL1 expression, and the patients with EGFR, SMARCA4, EPHA5, FAT1, STK11, TET2 mutations were more likely to be seen in negative PDL1 expression group. Worse survival could be found in patients with KEAP1 (P < 0.001), TP53 (P = 0.004) and EPHA5 (P = 0.013) mutations who received atezolizumab compared with those who had none of these gene mutations. Importantly, for PDL1 high patients without KEAP1, EPHA5, TP53 mutations receiving atezolizumab, they all showed relatively longer median survival with 22.47, 22.18 and 23.33 months, respectively (all, P < 0.01). Conclusions
Different high frequency gene mutations could be found between the patients with high and negative PDL1. PDL1 expression combined with specific gene mutation may better predict the survival for patients receiving atezolizumab.
科研通智能强力驱动
Strongly Powered by AbleSci AI