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

肿瘤突变负担和免疫学、基因组学和临床病理学因素作为非小细胞肺癌患者检查点抑制剂治疗的生物标志物

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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

Abstract

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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