联合生物标志物预测接受免疫检查点抑制剂治疗的晚期非小细胞肺癌患者临床结局的价值。

Predictive Value of Combining Biomarkers for Clinical Outcomes in Advanced Non-Small Cell Lung Cancer Patients Receiving Immune Checkpoint Inhibitors.

机构信息

Department of Medicine, Duke University School of Medicine, Durham, NC.

Department of Biostatistics and Bioinformatics, Duke University, Durham, NC.

出版信息

Clin Lung Cancer. 2021 Nov;22(6):500-509. doi: 10.1016/j.cllc.2021.03.017. Epub 2021 Mar 27.

DOI:10.1016/j.cllc.2021.03.017

PMID:33972172

Abstract

INTRODUCTION

A high tumor mutational burden (TMB) (≥10 mut/Mb) has been associated with improved clinical benefit in non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICI) and is a tumor agnostic indication for pembrolizumab across tumor types. We explored whether combining TMB with programmed cell death ligand 1 (PD-L1) and pretreatment neutrophil-lymphocyte ratio (NLR) was associated with improved outcomes in ICI-treated NSCLC.

METHODS

We retrospectively analyzed patients treated with ICI with Foundation One genomic testing, including TMB. Optimal cutoff for prediction of response by TMB was determined by receiver operating characteristic analysis, and area under the curve (AUC) was calculated for all 3 biomarkers and combinations. Cox model was used to assess prognostic factors of overall survival (OS) and time to progression (TTP). Survival cutoffs calculated with Kaplan-Meier survival curves were TMB ≥10 mut/Mb, PD-L1 ≥50%, NLR <5, and combined biomarkers.

RESULTS

Data from 88 patients treated were analyzed. The optimal TMB cutoff was 9.24 mut/Mb (AUC, 0.62), improving to 0.74 combining all 3 biomarkers. Adjusted Cox model showed that TMB ≥10 mut/Mb was an independent factor of OS (hazard ratio [HR], 0.31; 95% confidence interval; 0.14-0.69; P = .004) and TTP (HR, 0.46; 95% CI, 0.27-0.77; P = .003). The combination of high TMB with positive PD-L1 and low NLR was significantly associated with OS (P = .038) but not TTP.

CONCLUSIONS

TMB has modest predictive and prognostic power for clinical outcomes after ICI treatment. The combination of TMB, PD-L1, and NLR status improves this power.

摘要

简介

高肿瘤突变负担（TMB）（≥10 mut/Mb）与非小细胞肺癌（NSCLC）患者接受免疫检查点抑制剂（ICI）治疗的临床获益改善相关，并且是跨肿瘤类型使用 pembrolizumab 的肿瘤不可知的适应证。我们探讨了 TMB 与程序性细胞死亡配体 1（PD-L1）和治疗前中性粒细胞-淋巴细胞比值（NLR）联合是否与 ICI 治疗的 NSCLC 患者的改善结局相关。

方法

我们回顾性分析了接受 ICI 治疗且进行了 Foundation One 基因组检测的患者，包括 TMB。通过接受者操作特征分析确定 TMB 预测反应的最佳截断值，并计算所有 3 种生物标志物及其组合的曲线下面积（AUC）。Cox 模型用于评估总生存期（OS）和无进展生存期（TTP）的预后因素。通过 Kaplan-Meier 生存曲线计算的生存截断值为 TMB≥10 mut/Mb、PD-L1≥50%、NLR<5 以及联合生物标志物。

结果

对 88 例接受治疗的患者的数据进行了分析。最佳 TMB 截断值为 9.24 mut/Mb（AUC，0.62），结合所有 3 种生物标志物后改善至 0.74。调整后的 Cox 模型显示，TMB≥10 mut/Mb 是 OS（风险比[HR]，0.31；95%置信区间；0.14-0.69；P=0.004）和 TTP（HR，0.46；95%CI，0.27-0.77；P=0.003）的独立因素。高 TMB 与阳性 PD-L1 和低 NLR 结合与 OS 显著相关（P=0.038），但与 TTP 无关。