Tumor mutation burden and immunological, genomic, and clinicopathological factors as biomarkers for checkpoint inhibitor treatment of patients with non-small-cell lung cancer

被引:0
作者
Yuki Ozaki
Satoshi Muto
Hironori Takagi
Masayuki Watanabe
Takuya Inoue
Mitsuro Fukuhara
Takumi Yamaura
Naoyuki Okabe
Yuki Matsumura
Takeo Hasegawa
Jun Ohsugi
Mika Hoshino
Yutaka Shio
Daisuke Tanaka
Hideaki Nanamiya
Jun-ichi Imai
Takao Isogai
Shinya Watanabe
Hiroyuki Suzuki
机构
[1] Fukushima Medical University,Department of Chest Surgery, School of Medicine
[2] Fukushima Medical University,Translational Research Center
来源
Cancer Immunology, Immunotherapy | 2020年 / 69卷
关键词
Tumor mutation burden; Immune checkpoint inhibitor; Immunological; Biomarker; Non-small-cell lung cancer;
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摘要
Cancer treatment using immune checkpoint inhibitors is widely used, although biomarkers predictive of response are not well established. However, both the expressions of programmed cell death ligand 1 (PD-L1) and the tumor mutation burden (TMB) hold promise as such biomarkers for immune checkpoint inhibitors; however, its characteristics and clinical and immunological impacts have not been fully analyzed. We, therefore, evaluated the clinical and immunological parameters related to TMB to identify potential new biomarkers. We enrolled 92 patients with non-small-cell lung cancer who underwent surgery at Fukushima Medical University Hospital from 2013 to 2016. TMB of individual tumors was calculated by whole-exome sequencing analysis. Major cancer-related gene mutations were evaluated using panel sequencing. Expression of PD-L1 and abundance of tumor-infiltrating lymphocytes were evaluated by immunohistochemistry using surgical samples. The median TMB value was 60. TMB was significantly higher in men, current or former smokers, and in patients with squamous cell carcinoma, tumor size ≥ 2.8 cm, wild-type EGFR, TP53 gene mutation-positive status, and cyclin-dependent kinase-inhibitor gene 2A mutation-positive status. According to multivariate analysis, TMB was significantly associated with EGFR gene mutation-negative status (p = 0.0111) and TP53 gene mutation-positive status (p = 0.0425). If TMB is identified as a robust biomarker for immune checkpoint inhibitor administration, analysis of TP53 and EGFR mutations may provide a relatively rapid and easy proxy for predicting TMB.
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页码:127 / 134
页数:7
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