免疫相关lncRNA预测结肠腺癌预后分析

Immune-Related lncRNA Predicts the Prognosis of Colon Adenocarcinoma

摘要: 目的：鉴定对结肠腺癌患者具有潜在预后价值的免疫相关长链非编码RNA。方法：从癌症基因组图谱(The Cancer Genome Atlas, TCGA)数据库中获得结肠腺癌样本的临床信息和全基因表达数据，根据分子特征数据库，找到免疫相关的差异基因。使用相关性分析，找到免疫相关的差异表达长链非编码RNA (lncRNA)，最后依据病人的生存状态，通过cox回归分析找出7个免疫和生存相关的差异表达lncRNA。依据这7个lncRNA在病人中的表达量，构建Cox风险模型，计算病人的风险值，通过中位数，将病人分为高低风险组。使用临床特征进行单因素和多因素独立预后分析，查看临床特征与预后之间的吻合概率。通过相关性分析检测在不同临床特征中7个lncRNA的表达情况。通过受试者工作特征曲线(receiver operator characteristic curve, ROC)检测预后因素的准确性。依据主成分分析(Principal Component Analysis, PCA)，观察各样品的基因表达模式。最后通过基因富集分析(Gene Set Enrichment Analysis, GSEA)和免疫相关性分析，观察基因分布情况。结果：本研究共收录437个队列研究，其中癌组织为398个，正常组织为39个。通过相关性分析找到20个免疫相关的差异表达lncRNA。确定了7个最具预后价值的免疫相关lncRNA (AC245100.7, AP001189.3, LINC01503, ZEB1-AS1, AC004585.1, SNHG16, AP006621.3)。构建Cox风险模型，发现高风险组的病人的死亡率显著增高，五年生存率显著降低。通过单因素和多因素独立预后分析，发现年龄，临床分期以及风险值可以作为独立预后因子。相关性分析表明ZEB1-AS1在N分期中表达与疾病分期高度一致。ROC曲线显示临床分期，N分期和风险值均有较好的临床预后。PCA分析发现基7个预后相关的lncRNA可以很好的将高低风险组区分开。通过GSEA富集分析，发现免疫反应和免疫进程的相关基因在高风险的病人体内明显富集。通过免疫相关性分析发现高风险组患者中B细胞、T细胞和巨噬细胞相关基因表达升高以及副炎症、I型干扰素和II型干扰素相关基因表达显著升高。结论：7个免疫相关的预后lncRNA对结肠腺癌具有预后价值。

Abstract: Objective: Identification of immune-related long-chain non-coding RNAs with potential prognostic value for colon adenocarcinoma patients. Methods: Obtain clinical information and full gene expression data of colon adenocarcinoma samples from the Cancer Genome Atlas (TCGA) database, and find immune-related differential genes according to the molecular feature database. Use correlation analysis to find immune-related differentially expressed long non-coding RNA (lncRNA). Finally, according to the patient’s survival status, seven immune-related and survival-related differentially expressed lncRNAs were found through cox regression analysis. Based on the expression levels of these 7 lncRNAs in patients, a Cox risk model was constructed, the patient’s risk value was calculated, and the patients were divided into high and low risk groups based on the median. Use clinical features to perform univariate and multivariate independent prognostic analysis to view the probability of agreement between clinical features and prognosis. Correlation analysis was used to detect the expression of 7 lncRNAs in different clinical features. The accuracy of prognostic factors is detected by receiver operator characteristic curve (ROC). According to principal component analysis (Principal Component Analysis, PCA), observe the gene expression pattern of each sample. Finally, through Gene Set Enrichment Analysis (GSEA) and immune correlation analysis, observe the distribution of genes. Results: This study included a total of 437 cohort studies, including 398 cancer tissues and 39 normal tissues. Through correlation analysis, 20 immune-related differentially expressed lncRNAs were found. Seven immune-related lncRNAs with the most prognostic value were identified (AC245100.7, AP001189.3, LINC01503, ZEB1-AS1, AC004585.1, SNHG16, AP006621.3). The Cox risk model was constructed and it was found that the mortality rate of patients in the high-risk group was significantly increased, and the five-year survival rate was significantly reduced. Through univariate and multivariate independent prognostic analysis, it is found that age, clinical stage and risk value can be used as independent prognostic factors. Correlation analysis showed that the expression of ZEB1-AS1 in the N stage was highly consistent with the disease stage. ROC curve shows clinical stage, N stage and risk value have good clinical prognosis. PCA analysis found that based on 7 prognostic-related lncRNAs, high-risk groups can be well distinguished from low-risk groups. Through GSEA enrichment analysis, it is found that genes related to immune response and immune process are significantly enriched in high-risk patients. Through immune correlation analysis, it was found that the expression of B cells, T cells, and macrophages related genes in the high-risk group was increased, and the expression of para- inflammation, type I interferon and type II interferon related genes were significantly increased. Conclusion: Seven immune-related prognostic lncRNAs have prognostic value for colon adenocarcinoma.