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基于脂质代谢相关基因的新型 8 基因标志物在结肠腺癌中的计算机开发和临床验证。

In silico development and clinical validation of novel 8 gene signature based on lipid metabolism related genes in colon adenocarcinoma.

机构信息

Department of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, China.

出版信息

Pharmacol Res. 2021 Jul;169:105644. doi: 10.1016/j.phrs.2021.105644. Epub 2021 Apr 30.

DOI:10.1016/j.phrs.2021.105644

PMID:33940186

Abstract

BACKGROUND

Changes in lipid metabolism pathways play a major role in colon carcinogenesis and development. Hence, we conducted a systematic analysis of lipid metabolism-related genes to explore new markers that predict the prognosis of colon adenocarcinoma (COAD).

METHODS

The non-negative Matrix Factorization (NMF) algorithm was applied to identify the molecular subtypes based on lipid metabolism-related genes. A weighted correlation network analysis (WCGNA) was used to identify co-expressed genes, and Lasso multivariate Cox analysis was performed to build a risk prognosis model. A timer database was used to analyze the immune infiltration of the gene signature and the GSCALite database was used for genome-wide analysis of the gene signature.

RESULTS

TCGA-COAD samples were divided into 3 subtypes based on lipid metabolism-related genes. 2739 genes were identified by WGCNA analysis. Finally, an 8-gene signature (RTN2, FYN, HEYL, FAM69A, FBXL5, HMGN2, LGALS4, STOX1) was constructed that demonstrated good robustness in different datasets, as well as an independent risk factor for colon cancer patients' prognosis. In addition, our model's predictive efficacy overall was higher than that of the other published models, and the 8 genes' expression analysis indicated that RTN2, HEYL, and STOX1 were all expressed highly significantly in COAD, while FAM69A, FBXL5, LGALS4, FYN and HMGN2 were expressed significantly poorly in cancer tissues, which was confirmed in immunohistochemistry. The 8 genes were expressed significantly differently in COAD immune subtypes and correlated with clinical variables. Genome-wide analysis revealed that the STOX1 mutation frequency was the highest, and genome methylation influenced HEYL, FAM69A, and STOX1 gene expression significantly; further, the expression of HEYL and FBXL5 was correlated positively with Copy number variation (CNV) and was regulated significantly by CNV in most cancers. FBXL5 was correlated significantly with austocystin d and bafilomycin and played an important role in anti-tumor and immunotherapy. The HEYL, FYN, FAM69A, and RTN2 genes' expression was associated with the EMT pathway's activation, while LGALS4 and STOX1 were associated significantly with the EMT pathway's inhibition.

CONCLUSION

This study constructed an 8-gene signature as a novel marker to predict colon cancer patients' survival.

摘要

背景

脂质代谢途径的改变在结肠癌的发生和发展中起着重要作用。因此，我们对脂质代谢相关基因进行了系统分析，以探索新的生物标志物来预测结肠腺癌（COAD）的预后。

方法

采用非负矩阵分解（NMF）算法基于脂质代谢相关基因识别分子亚型。使用加权相关网络分析（WGCNA）识别共表达基因，并用 Lasso 多变量 Cox 分析构建风险预后模型。使用计时器数据库分析基因特征的免疫浸润，使用 GSCALite 数据库进行基因特征的全基因组分析。

结果

根据脂质代谢相关基因，TCGA-COAD 样本被分为 3 个亚型。通过 WGCNA 分析鉴定出 2739 个基因。最后，构建了一个由 8 个基因（RTN2、FYN、HEYL、FAM69A、FBXL5、HMGN2、LGALS4、STOX1）组成的基因特征，该特征在不同数据集的稳健性良好，并且是结肠癌患者预后的独立危险因素。此外，我们的模型的预测效果总体上高于其他已发表的模型，8 个基因的表达分析表明 RTN2、HEYL 和 STOX1 在 COAD 中均高度表达，而 FAM69A、FBXL5、LGALS4、FYN 和 HMGN2 在癌组织中表达显著降低，免疫组化也证实了这一点。8 个基因在 COAD 免疫亚型中的表达存在显著差异，并与临床变量相关。全基因组分析显示 STOX1 突变频率最高，基因甲基化显著影响 HEYL、FAM69A 和 STOX1 基因表达；进一步的研究表明，HEYL 和 FBXL5 的表达与拷贝数变异（CNV）显著相关，在大多数癌症中，CNV 对其表达有显著的调控作用。FBXL5 与 austocystin d 和 bafilomycin 显著相关，在抗肿瘤和免疫治疗中发挥重要作用。HEYL、FYN、FAM69A 和 RTN2 基因的表达与 EMT 通路的激活有关，而 LGALS4 和 STOX1 与 EMT 通路的抑制有关。