Department of Cardiothoracic Surgery, Xiangya Third Hospital, Central South University, Changsha, 410013, Hunan, China.
Sci Rep. 2022 Aug 30;12(1):14729. doi: 10.1038/s41598-022-19105-8.
Previous literatures have suggested the importance of inflammatory response during lung adenocarcinoma (LUAD) development. This study aimed at exploring the inflammation-related genes and developing a prognostic signature for predicting the prognosis of LUAD. Survival‑associated inflammation-related genes were identified by univariate Cox regression analysis in the dataset of The Cancer Genome Atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) penalized Cox regression model was used to derive a risk signature which is significantly negatively correlated with OS and divide samples into high-, medium- and low-risk group. Univariate and multivariate Cox analyses suggested that the level of risk group was an independent prognostic factor of the overall survival (OS). Time-dependent receiver operating characteristic (ROC) curve indicated the AUC of 1-, 3- and 5-years of the risk signature was 0.715, 0.719, 0.699 respectively. A prognostic nomogram was constructed by integrating risk group and clinical features. The independent dataset GSE30219 of Gene Expression Omnibus (GEO) was used for verification. We further explored the differences among risk groups in Gene set enrichment analysis (GSEA), tumor mutation and tumor microenvironment. Furthermore, Single Sample Gene Set Enrichment Analysis (ssGSEA) and the results of Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) suggested the status of immune cell infiltration was highly associated with risk groups. We demonstrated the prediction effect of CTLA-4 and PD-1/PD-L1 inhibitors in the low-risk group was better than that in the high-risk group using two methods of immune score include immunophenoscore from The Cancer Immunome Atlas (TCIA) and TIDE score from Tumor Immune Dysfunction and Exclusion (TIDE). In addition, partial targeted drugs and chemotherapy drugs for lung cancer had higher drug sensitivity in the high-risk group. Our findings provide a foundation for future research targeting inflammation-related genes to predictive prognosis and some reference significance for the selection of immunotherapy and drug regimen for lung adenocarcinoma.
先前的文献表明，在肺腺癌（LUAD）发展过程中炎症反应的重要性。本研究旨在探索与炎症相关的基因，并开发一种用于预测 LUAD 预后的预后特征。通过对癌症基因组图谱（TCGA）数据集进行单因素 Cox 回归分析，确定了与生存相关的炎症相关基因。最小绝对收缩和选择算子（LASSO）惩罚 Cox 回归模型用于推导出一个风险特征，该特征与 OS 显著负相关，并将样本分为高、中、低风险组。单因素和多因素 Cox 分析表明，风险组水平是总生存期（OS）的独立预后因素。时间依赖性接收器操作特征（ROC）曲线表明，风险签名的 1 年、3 年和 5 年 AUC 分别为 0.715、0.719、0.699。通过整合风险组和临床特征构建了预后列线图。Gene Expression Omnibus（GEO）的独立数据集 GSE30219 用于验证。我们进一步在基因集富集分析（GSEA）、肿瘤突变和肿瘤微环境中探索了风险组之间的差异。此外，单样本基因集富集分析（ssGSEA）和细胞鉴定的结果通过估计相对 RNA 转录物的子集（CIBERSORT）表明免疫细胞浸润状态与风险组高度相关。我们使用两种免疫评分方法，即癌症免疫图谱（TCIA）中的免疫表型评分和肿瘤免疫功能障碍和排除（TIDE）中的 TIDE 评分，证明了低风险组中 CTLA-4 和 PD-1/PD-L1 抑制剂的预测效果优于高风险组。此外，部分针对肺癌的靶向药物和化疗药物在高危组中具有更高的药物敏感性。我们的研究结果为未来针对炎症相关基因预测预后的研究提供了基础，并为肺腺癌的免疫治疗和药物方案选择提供了一些参考意义。
