Systemic inflammation biomarkers can identify high tumor mutation burden in lung adenocarcinoma

作者：Jiabin Fang, Qing Li, Nengluan Xu, Xiaojie Yang, Qiongyao Zhang, Yusheng Chen, Hongru Li · 发表于：BMC Cancer · 年份：2025 · DOI：10.1186/s12885-025-14894-3 · 被引用次数：5 · 研究领域：Inflammatory Biomarkers in Disease Prognosis、Cancer Immunotherapy and Biomarkers、Lung Cancer Research Studies

BACKGROUND: Tumor mutational burden (TMB) is a recognized biomarker for predicting immunotherapy efficacy in non-small cell lung cancer (NSCLC). Its assessment requires whole-exome sequencing (WES), but the high cost and stringent sample requirements of WES limit its clinical application. This study aims to assess the predictive value of accessible systemic inflammation markers for identifying high TMB lung cancer populations. METHODS: WES was performed on tumor samples and paired peripheral blood from 72 lung adenocarcinoma patients. Genomic analysis identified mutation patterns across different TMB groups. Systemic inflammatory markers, including the neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), lymphocyte-to-monocyte ratio (LMR), and platelet to lymphocyte ratio (PLR), were collected. Generalized linear models and restricted cubic spline (RCS) plots were used to explore the predictive value of these markers for TMB. The Xgboost model assessed the importance of each variable for TMB prediction. RESULTS: Among the 72 lung adenocarcinoma patients, missense mutations were the most common, with single nucleotide variants being the predominant mutation type. The most frequently mutated genes were EGFR (35%), TP53 (33%), and TTN (24%). Compared to the low TMB group, the high TMB group showed a higher proportion of C > A single nucleotide variants, along with significantly increased frequencies of TP53 (56% vs. 11%, p < 0.001) and TTN (42% vs...