基于转录组数据识别代谢综合征与结直肠癌的共同基因特征和分子机制

Identification of shared genetic features and molecular mechanisms of metabolic syndrome and colorectal cancer based on transcriptomic data

摘要:

目的 识别代谢综合征（metabolic syndrome，MetS）与结直肠癌（colorectal cancer，CRC）共同的基因特征和生物学通路，并筛选与MetS相关的CRC预后生物标志物。方法 对MetS、CRC和相应的对照样本进行差异分析，以识别表达差异的基因作为与疾病相关的基因。根据这些基因的表达特征进行功能富集分析，以识别受调控的生物学功能。利用单因素Cox回归鉴定与CRC预后相关的MetS基因，并使用LASSO和多因素Cox回归分析构建CRC的预后预测模型。基于汇总数据的孟德尔随机化分析（Summary-data-based Mendelian Randomization，SMR）进一步确认MetS基因与CRC预后的因果关系。结果 325个基因在MetS和CRC中表达上调，281个基因表达下调。研究还发现，Apelin信号和胞吐等通路在2种疾病中被抑制，而核酸修复通路则被激活。其中，有60个与MetS和CRC共享的基因与CRC的预后相关。18个基因被用于构建预测模型，在TCGA数据库的CRC队列中，模型在1~5年的曲线下面积（area under the curve，AUC）值均大于0.75，表现出良好的预测性能。通过SMR分析进一步确定，P4HA1和LARS2与CRC预后具有因果关系。结论 MetS和CRC具有共同的基因特征和通路，炎症可能为2种疾病相关的基础，共享基因对CRC的预后有影响。

Abstract:

Objective To identify shared genetic features and biological pathways between metabolic syndrome（MetS） and colorectal cancer（CRC），and to screen for prognostic biomarkers associated with MetS in CRC.Methods First，differential analysis was performed on MetS，CRC，and their corresponding control samples to identify genes with differential expression，which were used as disease-related genes. Subsequently，functional enrichment analysis was performed based on the expression characteristics of these genes to identify the regulated biological functions. Then，single-factor Cox regression was used to identify MetS genes associated with CRC prognosis，and LASSO and multivariate Cox regression analysis were used to construct a model for prediction of CRC prognosis. Finally，the causal relationship between MetS genes and CRC prognosis was further confirmed through Summary-data-based Mendelian Randomization.Results A total of 325 genes were upregulated and 281 genes were downregulated in both MetS and CRC. Apelin signaling and endocytosis pathways were inhibited and the nucleotide excision repair pathway was activated in both diseases. Among them，60 genes shared between MetS and CRC were associated with CRC prognosis. Eighteen genes were employed to construct a prediction model. In the CRC cohort of the TCGA database，the model demonstrated robust prediction performance with the area under the curve exceeding 0.75 for the 1-5 year period. Summary-data-based Mendelian Randomization analysis confirmed the causal relationship of P4HA1 and LARS2 with CRC prognosis.Conclusion MetS and CRC share genetic features and pathways，with inflammation as a possible link between these two diseases. Shared genes can influence the prognosis of CRC.