Clinical-genomic nomogram for predicting sensitivity to second-line immunotherapy for advanced non-small cell lung cancer.

IF 4 2区医学 Q2 ONCOLOGY

Translational lung cancer research Pub Date : 2025-02-28 Epub Date: 2025-02-27 DOI:10.21037/tlcr-2024-1249

Ying Hua, Ai Wang, Chao Xie, Apostolos C Agrafiotis, Pinlang Zhang, Baosheng Li

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引用次数: 0

Abstract

Background: The introduction of immune checkpoint inhibitors (ICIs) has significantly improved the outcomes of patients with advanced non-small cell lung cancer (NSCLC). However, ICIs only benefit a subset of patients. The study aimed to identify genomic biomarkers and construct models to predict the response to second-line ICI therapy.

Methods: We retrospectively collected clinical data and genetic testing results from patients with NSCLC treated with second-line ICI at a single medical center between August 2018 and June 2021. We reanalyzed the raw sequence data of clinical genetic testing and defined the common detection region among the different testing panels. Immunotherapy sensitivity was evaluated using the immune-based Response Evaluation Criteria in Solid Tumors.

Results: We included 102 patients as a training cohort and 46 as a test cohort. In the training cohort, we examined the relationship between ICI response and the mutation status of 343 genes. Mutations in the EGFR gene were significantly more common in the resistant group than in the sensitive group (41.0% vs. 20.6%; P=0.04), while mutations in the EP300 gene were associated with greater sensitivity to ICIs (39.7% vs. 15.4%; P=0.01). A nomogram was built based on clinical variables, genomic data, and programmed death-ligand 1 (PD-L1) expression. The total nomogram points were significantly higher in the sensitive group than in the resistance group in both cohorts, and the areas under the receiver operating characteristic curve were 0.780 in the training cohort and 0.720 in the test cohort. The higher nomogram points also indicated better progression-free survival.

Conclusions: Based on real-world clinical settings, the clinical genomic nomogram, which involved limited input variables that were economical and easy to obtain, demonstrated a good ability to predict the response to second-line ICI treatment in advanced NSCLC.

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预测晚期非小细胞肺癌二线免疫治疗敏感性的临床基因组图。

背景：免疫检查点抑制剂（ICIs）的引入显著改善了晚期非小细胞肺癌（NSCLC）患者的预后。然而，ICIs只能使一小部分患者受益。该研究旨在确定基因组生物标志物并构建模型来预测对二线ICI治疗的反应。方法：回顾性收集2018年8月至2021年6月在单一医疗中心接受二线ICI治疗的非小细胞肺癌患者的临床资料和基因检测结果。我们重新分析了临床基因检测的原始序列数据，并定义了不同检测组之间的共同检测区域。采用实体瘤免疫应答评价标准评价免疫治疗敏感性。结果：我们纳入了102名患者作为训练队列，46名患者作为测试队列。在训练队列中，我们检查了ICI反应与343个基因突变状态之间的关系。耐药组EGFR基因突变明显高于敏感组(41.0% vs. 20.6%；P=0.04)，而EP300基因突变与对ICIs的更高敏感性相关(39.7% vs. 15.4%；P = 0.01)。基于临床变量、基因组数据和程序性死亡配体1 （PD-L1）表达构建nomogram。两个队列中敏感组的总nomogram points均显著高于抵抗组，训练组和测试组的受试者工作特征曲线下面积分别为0.780和0.720。nomogram points越高也表明无进展生存期越好。结论：基于现实世界的临床环境，临床基因组图包含有限的输入变量，经济且易于获得，能够很好地预测晚期NSCLC对二线ICI治疗的反应。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Translational lung cancer research Medicine-Oncology

CiteScore

7.20

自引率

2.50%

发文量

137

期刊介绍： Translational Lung Cancer Research(TLCR, Transl Lung Cancer Res, Print ISSN 2218-6751; Online ISSN 2226-4477) is an international, peer-reviewed, open-access journal, which was founded in March 2012. TLCR is indexed by PubMed/PubMed Central and the Chemical Abstracts Service (CAS) Databases. It is published quarterly the first year, and published bimonthly since February 2013. It provides practical up-to-date information on prevention, early detection, diagnosis, and treatment of lung cancer. Specific areas of its interest include, but not limited to, multimodality therapy, markers, imaging, tumor biology, pathology, chemoprevention, and technical advances related to lung cancer.