Understanding the synergistic and antagonistic effects of tumor microenvironment (TME) and tumor mutation pattern on lung adenocarcinoma (LUAD) is urgently needed. Herein, we applied ESTIMATE and CIBERSORT methods to calculate the ratio of immune and stromal components and TIICs proportion of LUAD samples from TCGA database. Immune-related genes were analyzed by Lasso regression analysis and used for ceRNA network construction. A 14-lncRNA immune-related signature was developed, among which C5orf64 was found to be positively correlated with abundances of M2 macrophages, monocytes, eosinophils and neutrophils, but negatively correlated with Tregs and plasma cells. PD-1, PD-L1 and CTLA-4 were demonstrated to be high expressed in high-level C5orf64 groups. However, C5orf64 had a negative correlation with TP53 mutation frequency. A novel model was built based on age, tumor stage and immune-related lncRNA signature. To conclude, lncRNA C5orf64 had potential to be an indicator for TME modulation and tumor mutation pattern remodeling in LUAD.

迫切需要了解肿瘤微环境（TME）和肿瘤突变模式对肺腺癌（LUAD）的协同和拮抗作用。在此，我们应用 ESTIMATE 和 CIBERSORT 方法计算来自 TCGA 数据库的 LUAD 样本的免疫和基质成分的比例以及 TIICs 比例。通过 Lasso 回归分析分析免疫相关基因并用于 ceRNA 网络构建。开发了一个 14-lncRNA 免疫相关特征，其中发现 C5orf64 与 M2 巨噬细胞、单核细胞、嗜酸性粒细胞和中性粒细胞的丰度呈正相关，但与 Tregs 和浆细胞呈负相关。PD-1、PD-L1 和 CTLA-4 被证明在高水平 C5orf64 组中高表达。然而，C5orf64 与 TP53 突变频率呈负相关。基于年龄、肿瘤阶段和免疫相关的 lncRNA 特征建立了一个新的模型。总之，lncRNA C5orf64 有可能成为 LUAD 中 TME 调节和肿瘤突变模式重塑的指标。