PO.CL01.05 · 临床研究
基因组HLA I类等位基因失衡削弱晚期非小细胞肺癌的持久免疫治疗应答
Genomic HLA class I allelic imbalance undermines enduring immunotherapy response in advanced non small cell lung cancer
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摘要 Abstract
中文摘要
人类白细胞抗原I类（HLA-I）分子对新抗原呈递和T细胞识别至关重要，然而HLA-I基因内等位基因失衡（HLA-AI）在免疫检查点抑制剂（ICI）治疗中的临床意义仍未明确。在此，我们基于III期CHOICE-01试验中292例具有配对肿瘤和血液样本的完全杂合患者，建立了与常规临床测序兼容的单倍型特异性、基于覆盖度（cHLA-AI）和血浆来源（bHLA-AI）的模型。伴有HLA-AI的肿瘤突变负荷（TMB）低的肿瘤未从一线免疫化疗中获益，而所有其他患者获得显著的生存获益（mOS 16.53对29.57个月，HR = 2.29，95% CI 1.59-3.30，p < 0.001，交互作用P = 0.019；mPFS 5.59对9.92个月，HR = 2.02，95% CI 1.43-2.90，p < 0.001，交互作用P = 0.016）。这些发现在RATIONALE-304和RATIONALE-307试验及独立真实世界队列中得到验证，并扩展至cfDNA（bHLA-AI），其中组织-血浆整合评估勾勒出四种治疗轨迹。将cHLA-AI与病理学、PD-L1和TMB结合显著改善了2年OS预测（DeLong检验P = 0.003）。多组学分析将cHLA-AI与活跃的DNA损伤应答信号、高TMB、升高的瘤内异质性（ITH-high）、明显的染色体不稳定性（CIN-high）、免疫冷微环境以及治疗中TCR扩增失败相联系，而纵向采样揭示其在免疫压力下晚期、分支性的出现。泛癌分析（N = 5,989）显示其与TMB和增殖活性（Ki-67指数）的一致关联。总之，这些结果确立cHLA-AI为连接基因组不稳定性、免疫逃逸和治疗结局的关键生物标志物，为非小细胞肺癌及其他癌种的分层免疫治疗提供了框架。
查看英文原文 English abstract
Human leukocyte antigen class I (HLA-I) molecules are essential for neoantigen presentation and T cell recognition, yet the clinical significance of allelic imbalance within HLA-I genes (HLA-AI) in immune checkpoint inhibitor (ICI) therapy remains undefined. Here, we established haplotype-specific, coverage-based (cHLA-AI) and plasma-derived (bHLA-AI) models compatible with routine clinical sequencing, based on 292 fully heterozygous patients with paired tumor and blood samples from the phase III CHOICE-01 trial. Tumor mutational burden (TMB)-low tumors with HLA-AI derived no benefit from first-line immunochemotherapy, whereas all other patients achieved significant survival gains (mOS 16.53 vs. 29.57 months, HR = 2.29, 95% CI 1.59-3.30, p < 0.001,interaction P = 0.019; mPFS 5.59 vs. 9.92 months, HR = 2.02, 95% CI 1.43-2.90, p < 0.001, interaction P = 0.016). These findings were validated in the RATIONALE-304 and RATIONALE-307 trials and independent real-world cohorts, and extended to cfDNA (bHLA-AI), where integrated tissue-plasma assessment delineated four therapeutic trajectories. Incorporating cHLA-AI with pathology, PD-L1 and TMB significantly improved 2-year OS prediction (DeLong's P = 0.003). Multi-omic profiling linked cHLA-AI to active DNA damage response signaling, high TMB, elevated intratumor heterogeneity (ITH-high), pronounced chromosomal instability (CIN-high), immune-cold microenvironments, and failure of on-treatment TCR expansion, while longitudinal sampling revealed its late, branching emergence under immune pressure. Pan-cancer profiling (N = 5,989) demonstrated consistent associations with TMB and proliferative activity (Ki-67 index). Collectively, these results establish cHLA-AI as a pivotal biomarker bridging genomic instability, immune evasion, and therapeutic outcome, providing a framework for stratified immunotherapy in non-small cell lung cancer and beyond.
利益披露 Disclosure
Y. Dong#, None..
S. Wang#, None..
W. Li*, None..
Z. Wang*, None..
J. Wang*, None.