Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, 651 Ilalo St, Honolulu, HI, 96813, USA.
Molecular Biosciences and Bioengineering Program, College of Tropical Agriculture and Human Resources, University of Hawaii at Manoa, Honolulu, Hawaii, USA.
Mol Cancer. 2024 Nov 6;23(1):247. doi: 10.1186/s12943-024-02160-2.
Immune checkpoint inhibitors (ICIs) have revolutionized the treatment landscape for non-small cell lung cancer (NSCLC). The variability in patient responses necessitates a blood-based, multi-cohort gene signature to predict ICI response in NSCLC.
We performed transcriptomic profiling of peripheral blood mononuclear cell (PBMC) and buffy coat (BC) samples from three independent cohorts of NSCLC patients treated with ICIs: a retrospective cohort (PMBCR, n = 59), a retrospective validation cohort (BC, n = 44), and a prospective validation cohort (PBMCP, n = 42). We identified a 5-gene signature (UQCRB, NDUFA3, CDKN2D, FMNL1-DT, and APOL3) predictive of ICI response and validated its clinical utility in the prospective PBMCP cohort. Response was evaluated using RECIST criteria, and patients were followed up for progression-free survival (PFS) and overall survival (OS).
In the prospective PBMCP cohort, the 5-gene signature demonstrated high accuracy in stratifying patients into responders and non-responders (AUC = 0.89, 95% CI: 0.80-0.99). Predicted responders exhibited significantly longer PFS compared to predicted non-responders (median: 13.8 months vs. 4.2 months, HR = 0.21, 95% CI: 0.07-0.58, p = 0.005).
Our study confirms a 5-gene signature as a key biomarker for ICI response in NSCLC, enhancing treatment precision.
免疫检查点抑制剂（ICIs）彻底改变了非小细胞肺癌（NSCLC）的治疗格局。患者反应的可变性需要一种基于血液的多队列基因特征来预测 NSCLC 对 ICI 的反应。
我们对接受 ICI 治疗的三个独立 NSCLC 患者队列的外周血单核细胞（PMBC）和血涂片（BC）样本进行了转录组分析：回顾性队列（PMBCR，n=59）、回顾性验证队列（BC，n=44）和前瞻性验证队列（PBMCP，n=42）。我们确定了一个预测 ICI 反应的 5 基因特征（UQCRB、NDUFA3、CDKN2D、FMNL1-DT 和 APOL3），并在前瞻性 PBMCP 队列中验证了其临床实用性。通过 RECIST 标准评估反应，对患者进行无进展生存期（PFS）和总生存期（OS）随访。
在前瞻性 PBMCP 队列中，5 基因特征在将患者分层为应答者和非应答者方面具有很高的准确性（AUC=0.89，95%CI：0.80-0.99）。预测的应答者的 PFS 明显长于预测的非应答者（中位数：13.8 个月 vs. 4.2 个月，HR=0.21，95%CI：0.07-0.58，p=0.005）。
我们的研究证实了 5 基因特征是 NSCLC 对 ICI 反应的关键生物标志物，增强了治疗精度。
