Quantitative peripheral live single T-cell dynamic polyfunctionality profiling predicts lung cancer checkpoint immunotherapy treatment response and clinical outcomes.

IF 4 2区 医学 Q2 ONCOLOGY Translational lung cancer research Pub Date : 2024-12-31 Epub Date: 2024-12-17 DOI:10.21037/tlcr-24-260
Zuan-Fu Lim, Xiaoliang Wu, Lin Zhu, Heidar Albandar, Maria Hafez, Chenchen Zhao, Mohammed Almubarak, Matthew Smolkin, Hong Zheng, Sijin Wen, Patrick C Ma
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Abstract

Background: Predictive biomarkers for immune checkpoint inhibitors (ICIs), e.g., programmed death ligand-1 (PD-L1) tumor proportional score (TPS), remain limited in clinical applications. Predictive biomarkers that require invasive tumor biopsy procedures are practically challenging especially when longitudinal follow-up is required. Clinical utility of tissue-based PD-L1 TPS also becomes diluted when ICI is combined with chemotherapies. Peripheral single T-cell dynamic polyfunctionality profiling offers the opportunity to reveal rare T-cell subpopulations that are polyfunctional and responsible for the underlying ICI treatment molecular response that bulk biological assays cannot achieve. Here, we evaluated a novel live single-cell functional liquid biopsy cytokine profiling platform, IsoLight, as a potential predictive biomarker to track ICI treatment response and clinical outcomes in non-small cell lung cancer (NSCLC).

Methods: Peripheral blood mononuclear cell samples of 10 healthy donors and 10 NSCLC patients undergoing ICI-based therapies were collected longitudinally pre-/post-ICI treatment after ≥2 cycles under institutional review board (IRB)-approved protocols. Cancer blood samples were collected from unresectable advanced stage (III-IV) NSCLC patients. Clinical course and treatment response and survival outcomes were extracted from electronic health records, with treatment response assessed by treating oncologists based on RECIST. CD4+ and CD8+ T-cells were enriched magnetically and analyzed on the IsoLight platform. Single T-cells were captured in microchambers on IsoCode chips for proteomic immune cytokines profiling. Functional polyfunctionality data from 55,775 single cells were analyzed with IsoSpeak software, 2D- and 3D-t-distributed stochastic neighbor embedding (t-SNE) analysis, kappa coefficient, and Kaplan-Meier survival plots. P values ≤0.05 is considered statistically significant.

Results: Pre-treatment baseline polyfunctionality profiles could not differentiate NSCLC patients from healthy subjects, and could not differentiate ICI responders from non-responders. We found a statistically significant difference between responders and non-responders in CD8+ T-cells' changes in overall polyfunctionality (ΔPolyFx) (P=0.01) and polyfunctional strength index (ΔPSI) (P=0.006) in our dynamic pre-/post-treatment single cell measurements, both performing better than PD-L1 TPS alone (P=0.08). In the 3D-t-SNE analysis, subpopulations of post-treatment CD8+ T-cells in ICI responders displayed distinct immune cytokine profiles from those in pre-treatment cells. CD8+ T-cells ΔPolyFx and ΔPSI scores performed better than PD-L1 TPS in ICI response correlation. Moreover, combined PD-L1 strong TPS and ΔPSI >15 scores strongly correlated with early ICI response with a robust kappa coefficient of 1.0 (P=0.003), which was previously statistically established to indicate a perfect agreement between the prediction and actual response status. Interestingly, high CD4+ T-cells ΔPSI >5 was found to correlate with a strong trend of improved progression-free survival (3.9-fold) (10.8 vs. 2.8 months; P=0.07) and overall survival (3-fold) (34.5 vs. 11.5 months; P=0.09) in ICI-treated patients.

Conclusions: Our study nominates single peripheral T-cell polyfunctionality dynamics analysis to be a promising liquid biopsy platform to determine potential ICI predictive biomarker in NSCLC. It warrants further studies in larger prospective cohorts to validate the clinical utilities and to further optimize cancer immunotherapy.

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定量外周活单个t细胞动态多功能分析预测肺癌检查点免疫治疗反应和临床结果。
背景:免疫检查点抑制剂(ICIs)的预测性生物标志物,如程序性死亡配体-1 (PD-L1)肿瘤比例评分(TPS),在临床应用中仍然有限。需要侵入性肿瘤活检程序的预测性生物标志物实际上具有挑战性,特别是当需要纵向随访时。当ICI与化疗联合使用时,基于组织的PD-L1 TPS的临床应用也会被稀释。外周单个t细胞动态多功能分析提供了揭示罕见的t细胞亚群的机会,这些亚群具有多功能,并负责潜在的ICI治疗分子反应,这是大量生物分析无法实现的。在这里,我们评估了一种新的单细胞功能性液体活检细胞因子分析平台IsoLight,作为一种潜在的预测性生物标志物,用于跟踪非小细胞肺癌(NSCLC)的ICI治疗反应和临床结果。方法:在机构审查委员会(IRB)批准的方案下,在ici治疗前后≥2个周期纵向收集10名健康供体和10名接受ici治疗的NSCLC患者的外周血单个核细胞样本。肿瘤血液样本采集自晚期(III-IV)非小细胞肺癌患者。从电子健康记录中提取临床病程、治疗反应和生存结果,由治疗肿瘤学家基于RECIST评估治疗反应。对CD4+和CD8+ t细胞进行磁富集,并在IsoLight平台上分析。在IsoCode芯片的微室中捕获单个t细胞,用于蛋白质组免疫细胞因子分析。使用IsoSpeak软件、2D和3d -t分布随机邻居嵌入(t-SNE)分析、kappa系数和Kaplan-Meier生存图对55,775个单细胞的功能多功能性数据进行分析。P值≤0.05认为有统计学意义。结果:治疗前基线多功能谱不能区分非小细胞肺癌患者和健康受试者,也不能区分ICI应答者和无应答者。我们发现反应者和无反应者在CD8+ t细胞的总体多功能性变化(ΔPolyFx) (P=0.01)和多功能性强度指数(ΔPSI) (P=0.006)的动态治疗前/治疗后单细胞测量中有统计学显著差异,两者的表现都优于单独使用PD-L1 TPS (P=0.08)。在3D-t-SNE分析中,ICI应答者治疗后CD8+ t细胞亚群显示出与治疗前细胞不同的免疫细胞因子谱。CD8+ t细胞ΔPolyFx和ΔPSI评分在ICI反应相关性上优于PD-L1 TPS。此外,联合PD-L1强TPS和ΔPSI bbb15评分与早期ICI反应强相关,稳健kappa系数为1.0 (P=0.003),这表明预测与实际反应状态完全一致。有趣的是,高CD4+ t细胞ΔPSI >5被发现与改善无进展生存的强烈趋势相关(3.9倍)(10.8 vs. 2.8个月;P=0.07)和总生存期(3倍)(34.5 vs 11.5个月;P=0.09)。结论:我们的研究表明,单外周t细胞多功能动力学分析是一种有前景的液体活检平台,可以确定非小细胞肺癌中潜在的ICI预测生物标志物。这需要在更大的前瞻性队列中进行进一步的研究,以验证临床效用并进一步优化癌症免疫治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.20
自引率
2.50%
发文量
137
期刊介绍: Translational Lung Cancer Research(TLCR, Transl Lung Cancer Res, Print ISSN 2218-6751; Online ISSN 2226-4477) is an international, peer-reviewed, open-access journal, which was founded in March 2012. TLCR is indexed by PubMed/PubMed Central and the Chemical Abstracts Service (CAS) Databases. It is published quarterly the first year, and published bimonthly since February 2013. It provides practical up-to-date information on prevention, early detection, diagnosis, and treatment of lung cancer. Specific areas of its interest include, but not limited to, multimodality therapy, markers, imaging, tumor biology, pathology, chemoprevention, and technical advances related to lung cancer.
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