GluA1相互作用蛋白GNAI2和SRSF10对肝细胞癌预后的影响及诊断模型的建立

Effect of GluA1 interacting proteins GNAI2 and SRSF10 on prognosis of Hepatocellular carcinoma and establishment of diagnostic model

摘要:

目的 探讨AMPA型谷氨酸受体亚基1（glutamate A1，GluA1）相互作用蛋白GNAI2、SRSF10对HCC药物相关靶点、预后指标及诊断模型的作用和影响。方法 蛋白质组学方法获得GluA1相互作用蛋白。Xena数据库（https：//xenabrowser.net/）中获取肝细胞癌（liver hepatocellular carcinoma，LIHC）转录组数据以及对应的临床数据，保留在75%样本中表达的基因和其中原发肿瘤和癌旁组织样本用于后续分析。R语言的limma包标准流程对样本进行差异分析。对GluA1相互作用蛋白及差异基因取交集，并进行表达量分析、单因素COX分析和生存曲线分析。PDBePISA数据库验证候选蛋白集与GluA1在分子结构上的对接。string数据库分析候选蛋白集与肝癌相关药物的作用靶点。多因素COX分析患者的预后指标，logistic回归模型构建肝癌诊断模型。结果 获得6个候选蛋白，即KIF1A、GNAI2、RPL3、ARPC1A、EIF3H和SRSF10与GluA1具有很强的亲和力。其中GNAI2和SRSF10是肝细胞癌药物Regorafenib的二级作用靶点，其在单因素以及多因素COX分析中对患者的生存均存在影响（P<0.05），GNAI2（P=0.000 339），SRSF10（P=0.040 4），并且GNAI2、SRSF10在疾病组中比正常组中高。Z值分别为GNAI2：3.584、SRSF10：2.049。HR分别为GNAI2：2.38，SRSF10：1.18，均为不利预后因素，有希望作为独立于其他因素的预后指标。在肝癌患者的诊断模型中，HR系数分别为GNAI2：11.8455，SRSF10：-0.2037，且该模型在训练集上的曲线下面积为0.971，性能优异。结论 GluA1相互作用蛋白GNAI2和SRSF10是肝细胞癌治疗药物Regorafenib的二级作用靶点，意味着其可能会成为独立于其他因素的预后指标，且具备一定的诊断意义。

Abstract:

Objective To investigate the effect of AMPA glutamate receptor subunit 1（glutamate A1，GluA1） interacting proteins GNAI2 and SRSF10 on drug-related targets，prognostic indicators，and diagnostic models of hepatocellular carcinoma（HCC）.Methods GluA1 interacting proteins were obtained by proteomic methods. Transcriptome data and the corresponding clinical data of liver hepatocellular carcinoma were obtained from the Xena database（https：//xenabrowser.net/）. Genes expressed in 75% of the samples and primary tumor and para-carcinoma tissue samples were retained for subsequent analysis. The limma package standard process in R language was used to perform variation analysis on the samples. The intersection of GluA1 interacting proteins and differentially expressed genes was obtained for expression analysis，univariate COX analysis，and survival curve analysis. The PDBePISA database was used to verify the molecular docking of the candidate protein set with GluA1. The string database was used to analyze the targets of HCC-related drugs in the candidate protein set. Prognostic indicators of patients were analyzed by the multivariate COX analysis. The logistic regression model was used to construct a diagnostic model for HCC.Results Six candidate proteins，namely KIF1A，GNAI2，RPL3，ARPC1A，EIF3H，and SRSF10，were obtained with strong affinity to GluA1. GNAI2 and SRSF10 were secondary targets of Regorafenib in HCC，and the univariate and multivariate COX analyses showed that they had significant effects on patient survival（P=0.000 339，0.0404）. GNAI2 and SRSF10 were higher in level in the disease group than in the normal group（Z=3.584，2.049； hazard ratio（HR）=2.38，1.18），and are adverse prognostic factors. In the diagnostic model of HCC，the HR coefficients were 11.8455 and -0.2037，respectively，and the area under the curve of this model on the training set was 0.971，indicating excellent performances.Conclusion GluA1 interacting proteins GNAI2 and SRSF10 are secondary targets of Regorafenib in HCC，which may become prognostic indicators independent of other factors and have certain diagnostic significance.