Purpose

Lung adenocarcinoma (LUAD) is the predominant subtype of lung cancer, with increasing evidence showing clinical benefits of immunotherapy. However, a lack of integrated profiles of complex LUAD immune microenvironments hampers the application of immunotherapy, resulting in limited eligible patient populations as well as drug resistance problems. Here, we aimed to systematically profile the immune signatures of LUADs and to assess the role of the immune microenvironment in patient outcome.

Methods

We systematically profiled the immune signatures of LUADs deposited in the TCGA and GEO databases using a total of 730 immune-related genes. Differential expression analysis was used to identify dysregulated genes. Univariate Cox analysis followed by robust likelihood-based survival analysis and multivariate Cox analysis were applied to construct an immune-related prognostic model.

Results

We found that differentially expressed immune genes were mainly enriched in immune cell proliferation, migration, activation and the NF-κB and TNF signaling pathways. The 10-immune gene predictive model that we constructed could differentiate LUAD patients with different overall survival times in several datasets, with areas under the curve (AUCs) of 0.67, 0.69, 0.72 and 0.74. LUAD patients with high- or low-risk scores exhibited distinct immune cell compositions, which may explain the prognostic significance of our model.

Conclusions

Our results add to the current knowledge of immune processes in LUADs and underscore the critical role of the immune microenvironment in LUAD patient outcome.

中文翻译：

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免疫特征的系统分析可确定肺腺癌的预后指标。

目的

肺腺癌（LUAD）是肺癌的主要亚型，越来越多的证据显示免疫疗法的临床益处。然而，缺乏复杂的LUAD免疫微环境的综合概况阻碍了免疫疗法的应用，导致合格的患者人群有限以及耐药性问题。在这里，我们旨在系统地分析LUADs的免疫特征，并评估免疫微环境在患者预后中的作用。

方法

我们系统地分析了使用总共730个免疫相关基因存储在TCGA和GEO数据库中的LUAD的免疫特征。差异表达分析用于鉴定失调的基因。应用单变量Cox分析，然后进行鲁棒的基于可能性的生存分析和多变量Cox分析，以构建免疫相关的预后模型。

结果

我们发现差异表达的免疫基因主要集中在免疫细胞的增殖，迁移，激活以及NF-κB和TNF信号通路中。我们构建的10个免疫基因预测模型可以在几个数据集中区分曲线下面积（AUC）为0.67、0.69、0.72和0.74的LUAD患者，这些患者的总生存时间不同。具有高风险或低风险评分的LUAD患者表现出不同的免疫细胞组成，这可能解释了我们模型的预后意义。

结论

我们的结果增加了LUADs免疫过程的最新知识，并强调了免疫微环境在LUAD患者预后中的关键作用。