基线IL-6、IL-8、IFN-ω和perforin作为免疫检查点抑制剂治疗的转移性非小细胞肺癌的预后生物标志物
Baseline IL-6, IL-8, IFN-ω, and perforin as prognostic biomarkers in immune checkpoint inhibitor-treated metastatic non-small cell lung cancer.
作者
作者单位
- Division of Hematology/Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
- Division of Biostatistics and Informatics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
- Section of Oncology, Lieutenant Colonel Charles S. Kettles VA Medical Center, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
- Section of Oncology, Richard L. Roudebush VA Medical Center, VA Indiana Healthcare System, Indianapolis, IN, USA.
- Section of Oncology, Louis Stokes Cleveland VA Medical Center, VA Northeast Ohio Healthcare System, Cleveland, OH, USA.
摘要
中文
免疫检查点抑制剂（ICI）在非小细胞肺癌（NSCLC）中的预后血清生物标志物较少。我们评估了接受ICI治疗的转移性NSCLC患者中基线细胞因子作为预后标志物。对96名接受ICI的转移性NSCLC患者进行了基线血清细胞因子定量。针对无进展生存期（PFS）和总生存期（OS）分别建立了多变量模型，并调整了临床协变量。风险比（HR）以细胞因子浓度每翻倍表示。显著的细胞因子随后被纳入多变量Cox模型，并使用时间依赖性曲线下面积（AUC）评估模型区分度。进行了潜在类别分析（LCA）以识别与生存相关的细胞因子定义的患者表型。白细胞介素-6（IL-6）每翻一倍，死亡风险增加34% [HR=1.34；95%置信区间（CI）：1.13-1.60；P<0.001]，白细胞介素-8（IL-8）每翻一倍，死亡风险增加36%（HR=1.36；95% CI：1.16-1.59；P<0.001）。相反，干扰素-ω（IFN-ω）每翻一倍（HR=0.87；95% CI：0.80-0.95；P=0.001）和perforin每翻一倍（HR=0.50；95% CI：0.33-0.76；P<0.001）降低了死亡风险。包含IL-6、IL-8、IFN-ω和perforin的多变量细胞因子模型在PFS和OS上实现了时间依赖性AUC>0.70。LCA确定了两种细胞因子类别：一种富含IL-6/IL-8（预后差），另一种富含IFN-ω/perforin（预后良好）。在接受ICI治疗的转移性NSCLC中，较高的基线血清IL-6和IL-8浓度与较差的生存相关，而较高的基线血清IFN-ω和perforin与改善的生存相关，定义了具有预后意义的不同宿主免疫炎症表型。
English
Prognostic serum biomarkers of immune checkpoint inhibitor (ICI) efficacy in non-small cell lung cancer (NSCLC) are sparse. We evaluated baseline cytokines as markers of outcomes in ICI-treated metastatic NSCLC. Baseline serum cytokines were quantified in 96 patients with metastatic NSCLC receiving ICIs. Separate multivariable models were fit for progression-free survival (PFS) and overall survival (OS), adjusting for clinical covariates. Hazard ratios (HRs) were expressed per doubling in cytokine concentration. Significant cytokines were then incorporated into multivariable Cox models, and model discrimination was assessed using time-dependent area under the curve (AUC). Latent class analysis (LCA) was performed to identify cytokine-defined patient phenotypes associated with survival. Each doubling of interleukin-6 (IL-6) increased the hazard of death by 34% [HR =1.34; 95% confidence interval (CI): 1.13-1.60; P<0.001] and interleukin-8 (IL-8) by 36% (HR =1.36; 95% CI: 1.16-1.59; P<0.001). Conversely, each doubling of interferon-omega (IFN-ω) (HR =0.87; 95% CI: 0.80-0.95; P=0.001) and perforin (HR =0.50; 95% CI: 0.33-0.76; P<0.001) decreased mortality risk. Multivariable cytokine models incorporating IL-6, IL-8, IFN-ω, and perforin achieved time-dependent AUCs >0.70 for PFS and OS. LCA identified two cytokine classes: one enriched for IL-6/IL-8 (poor outcomes) and another enriched for IFN-ω/perforin (favorable outcomes). Higher baseline serum IL-6 and IL-8 concentrations were associated with inferior survival, whereas higher baseline serum IFN-ω and perforin were associated with improved survival in ICI-treated metastatic NSCLC, defining distinct host immune-inflammatory phenotypes with prognostic relevance.
分类与指标
- 研究类型
- 临床研究
- 病种
- 肺癌
- JCR 分区
- Q2
- 影响因子
- 3.4
- 新锐分区
- 3区