Li Qiaxuan, Yao Lintong, Lin Zenan, Li Fasheng, Xie Daipeng, Li Congsen, Zhan Weijie, Lin Weihuan, Huang Luyu, Wu Shaowei, Zhou Haiyu
Department of Thoracic Surgery, Guangdong Provincial People's Hospital & Guangdong Academy of Medical Sciences, School of Medicine, South China University of Technology, Southern Medical University, Guangzhou, China.
College of Medicine, Shantou University, Shantou, China.
Front Oncol. 2021 Oct 20;11:706616. doi: 10.3389/fonc.2021.706616. eCollection 2021.
Long non-coding RNAs (lncRNAs) participate in the regulation of immune response and carcinogenesis, shaping tumor immune microenvironment, which could be utilized in the construction of prognostic signatures for non-small cell lung cancer (NSCLC) as supplements.
Data of patients with stage I-III NSCLC was downloaded from online databases. The least absolute shrinkage and selection operator was used to construct a lncRNA-based prognostic model. Differences in tumor immune microenvironments and pathways were explored for high-risk and low-risk groups, stratified by the model. We explored the potential association between the model and immunotherapy by the tumor immune dysfunction and exclusion algorithm.
Our study extracted 15 immune-related lncRNAs to construct a prognostic model. Survival analysis suggested better survival probability in low-risk group in training and validation cohorts. The combination of tumor, node, and metastasis staging systems with immune-related lncRNA signatures presented higher prognostic efficacy than tumor, node, and metastasis staging systems. Single sample gene set enrichment analysis showed higher infiltration abundance in the low-risk group, including B cells (p<0.001), activated CD8+ T cells (p<0.01), CD4+ T cells (p<0.001), activated dendritic cells (p<0.01), and CD56+ Natural killer cells (p<0.01). Low-risk patients had significantly higher immune scores and estimated scores from the ESTIMATE algorithm. The predicted proportion of responders to immunotherapy was higher in the low-risk group. Critical pathways in the model were enriched in immune response and cytoskeleton.
Our immune-related lncRNA model could describe the immune contexture of tumor microenvironments and facilitate clinical therapeutic strategies by improving the prognostic efficacy of traditional tumor staging systems.
长链非编码RNA（lncRNAs）参与免疫反应和致癌作用的调控，塑造肿瘤免疫微环境，可作为补充用于构建非小细胞肺癌（NSCLC）的预后特征。
从在线数据库下载I-III期NSCLC患者的数据。使用最小绝对收缩和选择算子构建基于lncRNA的预后模型。通过该模型对高危和低危组的肿瘤免疫微环境和通路差异进行探索。我们通过肿瘤免疫功能障碍和排除算法探索该模型与免疫治疗之间的潜在关联。
我们的研究提取了15个免疫相关lncRNAs构建预后模型。生存分析表明，在训练和验证队列中，低危组的生存概率更高。肿瘤、淋巴结和转移分期系统与免疫相关lncRNA特征的组合比肿瘤、淋巴结和转移分期系统具有更高的预后效能。单样本基因集富集分析显示，低危组的浸润丰度更高，包括B细胞（p<0.001）、活化的CD8+T细胞（p<0.01）、CD4+T细胞（p<0.001）、活化的树突状细胞（p<0.01）和CD56+自然杀伤细胞（p<0.01）。低危患者的免疫评分和ESTIMATE算法估计评分显著更高。低危组对免疫治疗反应者的预测比例更高。模型中的关键通路在免疫反应和细胞骨架中富集。
我们的免疫相关lncRNA模型可以描述肿瘤微环境的免疫格局，并通过提高传统肿瘤分期系统的预后效能来促进临床治疗策略。
