Hong Moonki, Lee Sang Wook, Cho Byoung Chul, Hong Min Hee, Lim Sun Min, Kwon Nak-Jung
Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea.
Palliative Care Center, Department of Internal Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea.
Ther Adv Med Oncol. 2024 May 20;16:17588359241254218. doi: 10.1177/17588359241254218. eCollection 2024.
Programmed death-ligand (PD-L1) expression serves as a predictive biomarker for immune checkpoint inhibitor (ICI) sensitivity in non-small cell lung cancer (NSCLC). Nevertheless, the development of biomarkers that reliably predict ICI response remains an ongoing endeavor due to imperfections in existing methodologies.
ICIs have led to a new paradigm in the treatment of NSCLC. The current companion PD-L1 diagnostics are insufficient in predicting ICI response. Therefore, we sought whether the Olink platform could be applied to predict response to ICIs in NSCLC.
We collected blood samples from patients with NSCLC before ICI treatment and retrospectively analyzed proteomes based on their response to ICI.
Overall, 76 NSCLC patients' samples were analyzed. Proteomic plasma analysis was performed using the Olink platform. Intraplate reproducibility, validation, and statistical analyses using elastic net regression and generalized linear models with clinical parameters were evaluated.
Intraplate coefficient of variation (CV) assays ranged from 3% to 6%, and the interplate CV was 14%. In addition, the Pearson correlation coefficient of the Olink Normalized Protein eXpression data was validated. No statistical differences were observed in the analyses of progressive disease and response to ICIs. Furthermore, no single proteome showed prognostic value in terms of progression-free survival.
In this study, the proximity extension assay-based approach of the Olink panel could not predict the patient's response to ICIs. Our proteomic analysis failed to achieve predictive value in both response or progression to ICIs and progression-free survival (PFS).
程序性死亡配体（PD-L1）表达作为非小细胞肺癌（NSCLC）中免疫检查点抑制剂（ICI）敏感性的预测生物标志物。然而，由于现有方法存在缺陷，可靠预测ICI反应的生物标志物的开发仍是一项持续的工作。
ICI已引领了NSCLC治疗的新范式。目前配套的PD-L1诊断方法在预测ICI反应方面并不充分。因此，我们探讨了Olink平台是否可用于预测NSCLC患者对ICI的反应。
我们收集了NSCLC患者在ICI治疗前的血样，并根据他们对ICI的反应对蛋白质组进行回顾性分析。
总共分析了76例NSCLC患者的样本。使用Olink平台进行血浆蛋白质组分析。评估了板内重复性、验证以及使用弹性网络回归和带有临床参数的广义线性模型进行的统计分析。
板内变异系数（CV）测定范围为3%至6%，板间CV为14%。此外，对Olink标准化蛋白质表达数据的Pearson相关系数进行了验证。在疾病进展和对ICI反应的分析中未观察到统计学差异。此外，就无进展生存期而言，没有单一蛋白质组显示出预后价值。
在本研究中，基于邻近延伸分析方法的Olink检测板无法预测患者对ICI的反应。我们的蛋白质组分析在对ICI的反应或进展以及无进展生存期（PFS）方面均未达到预测价值。
