Background: Lung cancer is one of the most common types of cancer, and it has a poor prognosis. It is urgent to identify prognostic biomarkers to guide therapy.

Methods: The immune gene expression profiles for patients with lung adenocarcinomas (LUADs) were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). The relationships between the expression of 45 immune checkpoint genes (ICGs) and prognosis were analyzed. Additionally, the correlations between the expression of 45 biomarkers and immunotherapy biomarkers, including tumor mutation burden (TMB), mismatch repair defects, neoantigens, and others, were identified. Ultimately, prognostic ICGs were combined to determine immune subgroups, and the prognostic differences between these subgroups were identified in LUAD.

Results: A total of 11 and nine ICGs closely related to prognosis were obtained from the GEO and TCGA databases, respectively. CD200R1 expression had a significant negative correlation with TMB and neoantigens. CD200R1 showed a significant positive correlation with CD8A, CD68, and GZMB, indicating that it may cause the disordered expression of adaptive immune resistance pathway genes. Multivariable Cox regression was used to construct a signature composed of four prognostic ICGs (IDO1, CD274, CTLA4, and CD200R1): Risk Score = −0.002^*IDO1+0.031^*CD274−0.069^*CTLA4−0.517^*CD200R1. The median Risk Score was used to classify the samples for the high- and low-risk groups. We observed significant differences between groups in the training, testing, and external validation cohorts.

Conclusion: Our research provides a method of integrating ICG expression profiles and clinical prognosis information to predict lung cancer prognosis, which will provide a unique reference for gene immunotherapy for LUAD.

背景：肺癌是最常见的癌症之一，预后较差。迫切需要确定预后生物标志物来指导治疗。

方法：从癌症基因组图谱 (TCGA) 和基因表达综合 (GEO) 中获得肺腺癌 (LUAD) 患者的免疫基因表达谱。分析45个免疫检查点基因（ICG）的表达与预后之间的关系。此外，还确定了 45 种生物标志物和免疫治疗生物标志物表达之间的相关性，包括肿瘤突变负荷 (TMB)、错配修复缺陷、新抗原等。最终，结合预后 ICG 来确定免疫亚组，并在 LUAD 中确定这些亚组之间的预后差异。

结果：从GEO和TCGA数据库中分别获得了11个和9个与预后密切相关的ICG。 CD200R1表达与TMB、新抗原呈显着负相关。 CD200R1与CD8A、CD68、GZMB呈显着正相关，提示其可能导致适应性免疫抵抗途径基因表达紊乱。使用多变量 Cox 回归构建由四个预后 ICG（IDO1、CD274、CTLA4 和 CD200R1）组成的特征：风险评分 = −0.002 ^* IDO1+0.031 ^* CD274−0.069 ^* CTLA4−0.517 ^* CD200R1。中位风险评分用于将样本分类为高风险组和低风险组。我们观察到训练、测试和外部验证队列中各组之间存在显着差异。

结论：我们的研究提供了一种整合ICG表达谱和临床预后信息来预测肺癌预后的方法，为LUAD的基因免疫治疗提供独特的参考。