Jiang Lili, Li Shuang, Zhou Ping, Huang Yan, Chen Min, Yang Chan
Department of Pathology, West China Hospital, Sichuan University, Chengdu, China.
Department of Pathology, The First People's Hospital of Yunnan Province, Yunnan, Kunming, China.
Front Immunol. 2025 Sep 12;16:1579840. doi: 10.3389/fimmu.2025.1579840. eCollection 2025.
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 (<0.01, <0.01) group and NACT-IO (<0.001, <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 (<0.01, <0.001) and GC-TLSs (<0.01, <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 (<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, = 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, = 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 '.
三级淋巴结构（TLSs）是肿瘤微环境中的抗肿瘤免疫枢纽。生发中心（GC）（成熟的标志物）和TLS的空间分布可能决定免疫治疗的反应性。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。
纳入NACT-IO组（72例患者）、NACT组（50例患者）、UT组（50例患者，未接受新辅助治疗）。采用多重免疫荧光（mIF）分析新辅助治疗前后配对样本（同一病例）的微环境差异。进一步分析治疗对术后样本中TLS（肿瘤床内/外）成熟度和空间分布模式的影响，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（<0.01，<0.01）和NACT-IO组（<0.001，<0.001）肿瘤床内总TLS（t-TLSs）和GC阳性TLS（GC-TLSs）的密度显著高于肿瘤床外。与UT组相比，NACT和NACT-IO显著增加了肿瘤床内t-TLSs（<0.01，<0.001）和GC-TLSs（<0.01，<0.01）的密度。此外，GC-TLS与治疗周期之间存在倒U形相关性：接受2个或更少（≤2）周期的NACT和NACT-IO后，GC-TLSs的密度达到峰值，接受超过2个（>2）周期的NACT和NACT-IO后显著下降（<0.05）。多变量Cox回归模型证实，肿瘤床热点区域内低GC-TLS负荷（≤2/20×HPF）（HR = 3.99，95%CI = 1.10 - 14.5， = 0.036）在NACT-IO亚组的≤2周期中优于传统的病理缓解预后因素（HR = 3.44，95%CI = 1.03 - 11.47， = 0.044），并成为预测无病生存（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（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短疗程可最大化GC-TLS的预后价值，为优化治疗“时间窗”提供关键证据。
