Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, No. 180 Fenglin Rd, Xuhui District, Shanghai, 200032, China.
Department of Biostatistics, Public Health, Fudan University, Shanghai, 200000, China.
Cancer Immunol Immunother. 2020 Jul;69(7):1293-1305. doi: 10.1007/s00262-020-02546-3. Epub 2020 Mar 18.
To comprehensively elucidate the landscape of the tumor environment (TME) of lung adenocarcinoma (LUAD), which has a profound impact on prognosis and response to immunotherapy.
Using a large dataset of LUAD patients from The Cancer Genome Atlas, Gene Expression Omnibus database (GEO), and our institution (n = 1411), we estimated the infiltration pattern of 24 immune cell populations in each sample and systematically correlated the TME phenotypes with genomic traits and clinicopathologic characteristics.
The LUAD microenvironment was classified into two distinct TME clusters (A and B), and a random forest classifier model was constructed. TMEcluster A was characterized by sparse distribution of immune cell infiltration, relatively low levels of immunomodulators and slightly higher mutation load. By contrast, enrichment of both cytotoxic T cells and immunosuppressor cells was observed in TMEcluster B. Moreover, several immune-related cytokines or markers including IFN-γ, TNF-β, and several immune checkpoint molecules such as PD-L1 were also upregulated in TMEcluster B. Multivariable Cox analysis revealed that the TMEcluster was an independent prognostic factor (TMEcluster B vs. A, hazard ratio = 0.68, 95% confidence interval = 0.50-0.91, p = 0.010). These findings were all externally validated in the data from the GEO database and our institution.
Our findings describe a comprehensive landscape of LUAD immune infiltration pattern and integrate several previously proposed biomarkers associated with distinct immunophenotypes, thus shedding light on how tumors interact with immune microenvironment. Our results may guide a more precise immune therapeutic strategy for LUAD patients.
全面阐明肺癌腺癌（LUAD）肿瘤微环境（TME）的全貌，其对预后和免疫治疗反应有深远影响。
我们使用了来自癌症基因组图谱（TCGA）、基因表达综合数据库（GEO）和我们机构的大量 LUAD 患者数据集（n=1411），估计了每个样本中 24 种免疫细胞群的浸润模式，并系统地将 TME 表型与基因组特征和临床病理特征相关联。
LUAD 微环境被分为两个不同的 TME 簇（A 和 B），并构建了随机森林分类器模型。TMEcluster A 的特点是免疫细胞浸润稀疏分布，免疫调节剂水平相对较低，突变负荷略高。相比之下，TMEcluster B 中观察到细胞毒性 T 细胞和免疫抑制细胞的富集。此外，TMEcluster B 中还上调了几种免疫相关细胞因子或标志物，包括 IFN-γ、TNF-β 和几种免疫检查点分子，如 PD-L1。多变量 Cox 分析表明，TMEcluster 是一个独立的预后因素（TMEcluster B 与 A，风险比=0.68，95%置信区间=0.50-0.91，p=0.010）。这些发现均在 GEO 数据库和我们机构的数据中得到了外部验证。
我们的研究结果描述了 LUAD 免疫浸润模式的全面概况，并整合了几个与不同免疫表型相关的先前提出的生物标志物，从而揭示了肿瘤与免疫微环境相互作用的方式。我们的结果可能为 LUAD 患者的更精确免疫治疗策略提供指导。
