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基于MAPK信号通路相关基因的风险评分模型预测食管鳞状细胞癌的生存及其免疫微环境与用药研究
作者:曹莎莎1  李铭2  王晓敏3  李宇桐1  刘晓会4  张耀文3 
单位:1. 安阳市肿瘤医院 中心实验室, 河南 安阳 455000;
2. 安阳市肿瘤医院 影像科, 河南 安阳 455000;
3. 安阳市肿瘤医院 放疗科, 河南 安阳 455000;
4. 安阳市肿瘤医院 内科, 河南 安阳 455000
关键词:食管鳞癌 丝裂原活化蛋白激酶信号通路 预后 癌症基因组图谱数据库 免疫 
分类号:R735.1
出版年·卷·期(页码):2024·43·第三期(311-322)
摘要:

目的:基于丝裂原活化蛋白激酶(MAPK)信号通路相关基因(MRGs)构建预后模型,提高食管鳞状细胞癌(ESCC)患者的预后效果。方法:从癌症基因组图谱(TCGA)获取ESCC患者的相关信息,从京都基因与基因组百科全书(KEGG)数据库获取MRGs。基于MRGs中与ESCC患者生存相关基因对患者进行聚类分析,对所得差异基因进行回归分析筛选预后基因构建预后模型。对该模型划分的高低风险组进行基因本体论(GO)、KEGG分析和单样本基因富集分析(ssGSEA)。利用CellMiner数据库寻找可能与模型基因相关的药物。结果:回归分析筛选出了13个基因构建了预后模型,该模型在TCGA和基因表达综合数据库(GEO)中显示出良好预测能力。GO和KEGG分析结果显示,高低风险组白细胞介导的免疫和细胞黏附分子等生物学功能和通路具有显著差异。行ssGSEA发现,高风险组患者的免疫细胞浸润和大多数免疫功能显著强于低风险组。结论:开发了一个具有良好预测能力的预后模型,可能对ESCC的预后和治疗具有指导意义。

Objective: To construct a prognostic model based on mitogen-activated protein kinase(MAPK) signaling pathway related genes(MRGs) to help improve the prognosis of esophageal squamous cell carcinoma(ESCC) patients. Methods: Transcriptional data and clinical information of ESCC patients were obtained from the the Cancer Genome Atlas(TCGA), and MRGs were obtained from the Kyoto Encyclopedia of Genes and Genomes(KEGG) database. Cluster analysis was performed on patients based on ESCC genes related to survival in MRGs. Based on the differential genes of these two clusters, Cox regression analysis was conducted to screen prognosis genes and construct a risk model. Gene ontology(GO),KEGG analysis and single sample Gene Set Enrichment Analysis(ssGSEA) were performed between high- and low-risk groups based on the prognostic model. The CellMiner database was utilized to search for drugs that may be related to model genes. Results: 13 genes were screened to construct a prognosis model via regression analysis. The prognosis model showed stable and accurate predictive ability in the TCGA and Gene Expression Omnibus(GEO). The GO and KEGG analysis results showed significant differences in biological functions and pathways such as leukocyte mediated immunity and cell adhesion molecules between the high- and low- risk groups based on this model. ssGSEA found that patients in the high-risk group had significantly higher levels of immune cell infiltration and most immune functions than those in the low-risk group. Conclusion: We have developed a prognostic model with good and reliable predictive ability, which may have guiding significance for the prognosis and treatment research of ESCC.

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