[基于加权基因共表达网络分析的大肠腺癌免疫相关预后特征识别]。

Xiang He, Shouwei Wan, Qiang He, Jixue Hou
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引用次数: 0

摘要

目的探讨免疫相关分子标志物对结肠癌(COAD)预后的影响。方法基于TCGA数据库对免疫相关基因(IREGs)进行分析。采用加权基因共表达网络分析(WGCNA)和Cox回归分析建立风险模型。根据中位风险评分将COAD患者分为高危组和低危组。比较两组患者预后差异。利用GEO对模型的功能进行了验证。结果共获得IREGs 1015条。建立的模型由3个基因组成:RAR相关孤儿受体C (RORC)、富含亮氨酸的重复fli -i相互作用蛋白2 (LRRFIP2)和凝集素半乳糖苷结合可溶性凝集素4 (LGALS4)。GEO数据库中高危组预后明显差于低危组,并通过GEO数据库进行验证。单因素和多因素Cox回归分析显示,风险模型可作为COAD患者预后的独立因素。结论基于IREGs的风险模型可以预测COAD患者的预后。
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[Identification of immune-related prognostic signature for colon adenocarcinoma based on weighted gene co-expression network analysis].

Objective To identify immune-related molecular markers in an attempt to predict prognosis of colon adenocarcinoma (COAD). Methods Immune related genes (IREGs) was analyzed based on the TCGA database. Weighted gene co-expression network analysis (WGCNA) and Cox regression analysis were used to establish risk models. According to the median risk score, COAD patients were divided into high risk and low risk groups. The prognostic difference were compared between the two groups. The function of the model was validated using GEO. Results A total of 1015 IREGs was obtained. The established model consisted of three genes: RAR related orphan receptor C (RORC), leucine-rich repeat Fli-I-interacting protein 2 (LRRFIP2) and lectin galactoside-binding soluble galectin 4 (LGALS4). The high-risk group had significantly poorer prognosis than low-risk group in the GEO database, and it was validated using a GEO database. Further analysis via univariate and multivariate Cox regression analyses revealed that risk model could function as independent prognostic factor for COAD patients. Conclusion The risk model based on IREGs can predict the prognosis of patients with COAD.

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