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新辅助化疗-免疫治疗局部晚期肺鳞状细胞癌后的生发中心-三级淋巴结构可预测疾病进展

英文原题:The germinal center-tertiary lymphoid structure after neoadjuvant chemo-immunotherapy for locally advanced lung squamous cell carcinoma can predict the disease progression.

查看英文原题

The germinal center-tertiary lymphoid structure after neoadjuvant chemo-immunotherapy for locally advanced lung squamous cell carcinoma can predict the disease progression.

PubMed 2025/09/12(内容时间) Front Immunol Q1 · IF 7(JCR 2025)

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研究思路按摘要原文分段

三级淋巴结构(TLSs)是肿瘤微环境中的抗肿瘤免疫中枢。生发中心(GC)(成熟的标志)和TLS的空间分布可能决定免疫治疗的应答性。然而,新辅助化疗(NACT)和联合免疫治疗(NACT-IO)对TLS动态重塑的调控机制尚未阐明。

NACT-IO组(72例)、NACT组(50例)、UT组(50例,未接受新辅助治疗)被纳入。采用多重免疫荧光(mIF)分析配对样本(同一病例)在新辅助治疗前后的微环境差异。进一步分析治疗对术后样本中TLS成熟度及空间分布模式(瘤床内/外)的影响,并建立基于热点区域的TLS定量方法以评估其预后价值。

空间异质性分析显示,NACT组(p<0.01,p<0.01)和NACT-IO组(p<0.001,p<0.001)瘤床内总TLS(t-TLSs)和GC阳性TLS(GC-TLSs)的密度均显著高于瘤床外。与UT组相比,NACT和NACT-IO显著增加了瘤床内t-TLSs(p<0.01,p<0.001)和GC-TLSs(p<0.01,p<0.01)的密度。此外,GC-TLS与治疗周期之间呈倒U型相关:在接受两个或以下(≤2)周期NACT和NACT-IO后,GC-TLSs密度达到峰值,而在接受超过两个(>2)周期NACT和NACT-IO后显著下降(p<0.05)。多因素Cox回归模型证实,在≤2周期NACT-IO亚组中,瘤床热点内低GC-TLS负荷(≤2/20×HPF)(HR=3.99,95%CI=1.10-14.5,p=0.036)优于传统预后因素病理缓解(HR=3.44,95%CI=1.03-11.47,p=0.044),并成为预测无病生存期(DFS)的最强独立因素。

本研究首次揭示,NACT和NACT-IO通过TLS的多维度(丰度、空间分布和成熟度)动态重塑增强抗肿瘤疗效,并提出≤2周期的NACT-IO短程方案可最大化GC-TLS的预后价值,为优化治疗“时间窗”提供了关键证据。

展开英文摘要原文

The tertiary lymphoid structures (TLSs) are the anti-tumor immune hubs in the tumor microenvironment. The germinal center (GC) (a marker of maturation) and spatial distribution of TLS may determine the responsiveness of immunotherapy. However, the regulatory mechanism of neoadjuvant chemotherapy (NACT) and combined immunotherapy (NACT-IO) on the dynamic remodeling of TLS has not been elucidated.

The NACT-IO group (72 patients), NACT group (50 patients), UT group (50 patients, un-neoadjuvant therapy) were included. Multiple immunofluorescence (mIF) was used to analyze the difference of microenvironment in paired samples (the same case) pre and post neoadjuvant therapy. To further analyze the effect of treatment on the maturity and spatial distribution pattern of TLS (within/outside tumor bed) in postoperative samples, and to establish a quantitative method of TLS based on hot spot area to evaluate its prognostic value.

Spatial heterogeneity analysis that the density of total TLSs (t-TLSs) and GC-positive TLSs (GC-TLSs) in the tumor bed of NACT ( p <0.01, p <0.01) group and NACT-IO ( p <0.001, p <0.001) group were significantly higher than that outside the tumor bed. Compared with the UT group, NACT and NACT-IO significantly increased the density of t-TLSs ( p <0.01, p <0.001) and GC-TLSs ( p <0.01, p <0.01) in the tumor bed. In addition, there was an inverted U-shaped correlation between GC-TLS and treatment cycle: the density of GC-TLSs reaches the peak value after receiving two or less (≤ 2) cycles of NACT and NACT-IO, and decreased significantly after receiving more than two (> 2) cycles of NACT and NACT-IO ( p <0.05). Multivariate Cox regression model confirmed that low GC-TLS burden (≤2/20×HPF) within tumor bed hotspots (HR = 3.99, 95%CI=1.10-14.5, p = 0.036) was superior to the traditional prognostic factor of pathological remission in ≤ 2-cycles of NACT-IO subgroup (HR = 3.44, 95%CI=1.03-11.47, p = 0.044), and became the strongest independent factor for predicting disease free survival (DFS).

This study reveals for the first time that NACT and NACT-IO enhance anti-tumor efficacy through multidimensional (abundance, spatial distribution and maturity) dynamic remodeling of TLS, and proposes the short course of ≤ 2 cycles of NACT-IO can maximize the prognostic value of GC-TLS, providing key evidence for optimizing the treatment ' time window '.

论文信息

作者
Jiang L、Li S、Zhou P、Huang Y、Chen M、Yang C
单位
Department of Pathology, West China Hospital, Sichuan University, Chengdu, China.China
期刊
Frontiers in immunology2025
原文标识
PubMed 41019066 · DOI 10.3389/fimmu.2025.1579840