Background: Lung cancer is the most common malignancy world-wide. There are a variety of immune infiltrating cells in tumor microenvironment, which is an important component of tumor immunity and has clinical significance for the prognosis of patients. CD45RO is a surface marker of memory T cells. The expression of CD45RO⁺ tumor infiltrating lymphocytes (TILs) is associated with the prognosis of many tumors. The purpose of this study was to evaluate the relationship between the density of CD45RO⁺ TILs in tumor and stromal area and the clinical characteristics of patients with non-small cell lung cancer (NSCLC) and its impact on the prognosis of patients. We aimed to explore the clinical value of CD45RO⁺ TILs and programmed cell death ligand 1 (PD-L1) as prognostic markers.
Methods: Multiple fluorescent immunohistochemical staining was used to stain the tissue microarray chips of 167 patients with NSCLC, marking CD45RO, cytokeratin (CK) and PD-L1. Using artificial intelligence image recognition technology and tumor cell-specific CK staining, divide the tumor and stromal area in the tissue, evaluate the density of CD45RO⁺ TILs in the tumor and stromal area, and the expression level of PD-L1 in tumor cells. The non-parametric test was used to analyze the relationship between CD45RO⁺ TILs and the clinical characteristics of patients, and the Kaplan-Meier method and Cox risk ratio model were used to analyze the relationship between CD45RO⁺ TILs independently or in combination with PD-L1 and tumor prognosis.
Results: The density of CD45RO⁺ TILs was significantly associated with patient age, smoking, tumor stage, and pathological type. Single-factor survival analysis showed that NSCLC (P=0.007) stromal region and lung adenocarcinoma (LUAD) (P<0.001) with CD45RO⁺ TILs high density had better OS. Multivariate survival analysis showed that the high density of CD45RO⁺ TILs in the stromal region of NSCLC (HR=0.559, 95%CI: 0.377-0.829, P=0.004) and lung adenocarcinoma (HR=0.352, 95%CI: 0.193-0.641, P=0.001) were independent prognostic factors for overall survival time (OS). Combined with PD-L1 score of tumor cells in tumor tissues and infiltration score of CD45RO⁺ TILs in all tumor tissues, the patients were divided into 4 groups: patients with PD-L1⁺/CD45RO⁺ had the longest disease-free survival (DFS) time, and patients with PD-L1⁺/CD45RO- had the shortest DFS time. Multivariate Cox regression analysis showed that PD-L1⁺/CD45RO- was an independent prognostic factor for DFS and had a higher risk of poor prognosis compared to the other three groups (HR=2.221, 95%CI: 1.258-3.919, P=0.006).
Conclusions: In tumor tissues, the density of CD45RO⁺ TILs, as well as the combination of CD45RO⁺ TILs and PD-L1 in tumor areas, significantly correlated with clinicopathological features and prognosis of NSCLC, which can be used as a new prognosis marker.
【中文题目：CD45RO⁺记忆T细胞作为非小细胞肺癌患者 预后标志物的研究】 【中文摘要：背景与目的 肺癌是世界范围内最常见的恶性肿瘤之一。肿瘤微环境中多种多样的免疫浸润细胞，是肿瘤免疫的重要组成，对患者预后具有临床意义。CD45RO⁺肿瘤浸润淋巴细胞（tumor infiltrating lymphocytes, TILs），即记忆T细胞，其表达与多种肿瘤预后相关。本研究旨在探讨非小细胞肺癌（non-small cell lung cancer, NSCLC）中评估肿瘤和基质区CD45RO⁺ TILs密度与患者临床特征和预后的关系，及其联合程序性死亡受体配体1（programmed cell death-ligand 1, PD-L1）作为预后标志物的临床价值。方法 对167例NSCLC患者的组织微阵列进行多重荧光免疫组织化学染色，标记CD45RO、细胞角蛋白（cytokeratin, CK）和PD-L1。利用人工智能图像识别技术和肿瘤细胞特异性CK染色，划分组织中的肿瘤区和基质区，评估肿瘤区和基质区CD45RO⁺ TILs的密度以及肿瘤细胞的PD-L1表达水平。采用非参检验分析CD45RO⁺ TILs与患者临床特征的关系，使用Kaplan-Meier方法和Cox风险比例模型分析CD45RO⁺ TILs独立或与PD-L1联合与肿瘤预后的关系。结果 CD45RO⁺ TILs的密度与患者年龄、吸烟、肿瘤分期和病理类型显著相关。在NSCLC和肺腺癌（lung adenocarcinoma, LUAD）患者中，基质区高密度CD45RO⁺ TILs具有更长的总生存期（overall survival, OS）（NSCLC: P=0.007; LUAD: P<0.001），并且是OS的独立预后因素（NSCLC: HR=0.559, 95%CI: 0.377-0.829, P=0.004; LUAD: HR=0.352, 95%CI: 0.193-0.641, P=0.001）。联合肿瘤细胞的PD-L1评分以及所有区域CD45RO⁺ TILs的浸润评分将患者分为四组：其中PD-L1⁺/CD45RO⁺患者无病生存期（disease-free survival, DFS）最长，PD-L1⁺/CD45RO-的患者DFS时间最短，并可作为DFS预后的独立因素（HR=2.221, 95%CI: 1.258-3.919, P=0.006）。结论 肿瘤组织中CD45RO⁺ TILs密度以及CD45RO⁺ TILs联合肿瘤区PD-L1，与NSCLC的临床病理特征及预后显著相关，可作为新的生存预后标志物。】 【中文关键词：肺肿瘤；CD45RO；程序性死亡受体-配体1；预后】.
Keywords: CD45RO; Lung neoplasms; Prognosis; Programmed cell death ligand 1.