Heterogeneity of lymphocyte subsets in predicting immune checkpoint inhibitor treatment response in advanced lung cancer: an analysis across different pathological types, therapeutic drugs, and age groups.

IF 4 2区 医学 Q2 ONCOLOGY
Translational lung cancer research Pub Date : 2024-06-30 Epub Date: 2024-06-14 DOI:10.21037/tlcr-24-109
Chuanwang Miao, Yuanji Chen, Hao Zhang, Wei Zhao, Cunliang Wang, Zeliang Ma, Shan Zhu, Xudong Hu
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Abstract

Background: Immune checkpoint inhibitor (ICI) has become pivotal in the treatment of advanced lung cancer, yet the absence of reliable biomarkers for assessing treatment response poses a significant challenge. This study aims to explore the predictive value of various lymphocyte subsets in different lung cancer subtypes, thus potentially identifying novel biomarkers to improve ICI treatment stratification and outcomes.

Methods: We conducted a retrospective analysis of 146 stage III or IV lung cancer patients undergoing ICI treatment. The study focused on exploring the relationship between various lymphocyte subsets and the efficacy of ICIs, aiming to determine their predictive value for post-treatment outcomes.

Results: Subgroup analysis revealed a positive correlation (P=0.01) between lower CD3+CD8+ T lymphocyte levels and treatment response in squamous cell carcinoma patients. However, no significance was observed in lung adenocarcinoma patients. Additionally, the predictive ability of lymphocyte subsets for different immunotherapy drugs varies. In individuals receiving anti-programmed cell death ligand 1 (PD-L1) treatment, a lower CD3+CD8+ T lymphocyte levels is significantly associated with a positive treatment outcome (P=0.002), while there is no difference for programmed death 1 (PD-1) drugs. Among patients under 60, higher expression of CD3+CD4+ T lymphocytes (P=0.03) combined with lower CD3+CD8+ T lymphocyte levels (P=0.006) showed a statistically significant association with improved treatment response. However, in patients aged over 60, no discernible correlation was ascertained between lymphocyte subsets and therapeutic response. Through prognostic analysis, two distinct lymphocyte subsets were identified, both exerting considerable impact on progression-free survival subsequent to ICIs treatment: CD3+CD4+ T lymphocytes [hazard ratio (HR) =0.50, P=0.006] and CD3+CD8+ T lymphocytes (HR =1.78, P=0.02).

Conclusions: Our findings underscore the significant heterogeneity in the predictive value of distinct lymphocyte subsets for lung cancer patients undergoing ICI treatment. These findings are particularly salient when considering various pathological types, immunotherapeutic agents, and patient age groups.

预测晚期肺癌免疫检查点抑制剂治疗反应的淋巴细胞亚群异质性:对不同病理类型、治疗药物和年龄组的分析。
背景:免疫检查点抑制剂(ICI)已成为治疗晚期肺癌的关键,但缺乏评估治疗反应的可靠生物标志物构成了重大挑战。本研究旨在探索各种淋巴细胞亚群在不同肺癌亚型中的预测价值,从而为改善ICI治疗分层和疗效确定新的生物标志物:我们对 146 名接受 ICI 治疗的 III 期或 IV 期肺癌患者进行了回顾性分析。研究重点是探索各种淋巴细胞亚群与 ICIs 疗效之间的关系,旨在确定它们对治疗后结果的预测价值:亚组分析显示,鳞状细胞癌患者较低的 CD3+CD8+ T 淋巴细胞水平与治疗反应呈正相关(P=0.01)。但在肺腺癌患者中未观察到显著性。此外,淋巴细胞亚群对不同免疫疗法药物的预测能力也各不相同。在接受抗程序性细胞死亡配体1(PD-L1)治疗的患者中,较低的CD3+CD8+ T淋巴细胞水平与阳性治疗结果显著相关(P=0.002),而程序性死亡1(PD-1)药物则没有差异。在 60 岁以下的患者中,CD3+CD4+ T 淋巴细胞的较高表达量(P=0.03)加上较低的 CD3+CD8+ T 淋巴细胞水平(P=0.006)与治疗反应的改善有统计学意义。然而,在 60 岁以上的患者中,淋巴细胞亚群与治疗反应之间没有明显的相关性。通过预后分析,确定了两种不同的淋巴细胞亚群,它们对 ICIs 治疗后的无进展生存期都有相当大的影响:CD3+CD4+T淋巴细胞[危险比(HR)=0.50,P=0.006]和CD3+CD8+T淋巴细胞(HR=1.78,P=0.02):我们的研究结果表明,不同淋巴细胞亚群对接受 ICI 治疗的肺癌患者的预测价值存在显著的异质性。当考虑到各种病理类型、免疫治疗药物和患者年龄组时,这些发现尤为突出。
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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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