Peng Shen , Yinsheng Shi , Pengcheng Xu , Linbin Rao , Zhengfei Wang , Junjie Jiang , Meiling Weng
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Based on the median riskscore, we clustered the patients into high-risk (HR) and low-risk (LR) groups. We carried out Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of differentially expressed genes (DEGs) in HR and LR groups. The single sample gene set enrichment analysis (ssGSEA) was employed to analyze the immune infiltration of the HR and LR groups. The CellMiner database was utilized to predict drugs and perform molecular docking on drugs and target proteins.</p></div><div><h3>Results</h3><p>We identified 8 genes with prognostic significance to construct a prognostic model. Results of GO and KEGG demonstrated that DEGs were mainly enriched in biological functions such as fatty acid metabolic processes and pathways such as the cAMP signaling pathway. Results of ssGSEA uncovered that immune cells such as DCs and Macrophages in the HR group, as well as immune functions such as Check-point and Parainflammation, were considerably higher than those in the LR group. Drug sensitivity prediction and results of molecular docking revealed that Rigosertib targeted the prognostic genes MAP3K1. HYPOTHEMYCIN and AMG900 effectively targeted JUN.</p></div><div><h3>Conclusion</h3><p>Our project suggested that the prognostic model with apoptotic features can effectively predict prognosis in CCA patients, proffering prognostic biomarkers and potential therapeutic targets for CCA patients.</p></div>","PeriodicalId":10424,"journal":{"name":"Clinics and research in hepatology and gastroenterology","volume":"48 8","pages":"Article 102430"},"PeriodicalIF":2.6000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The construction of a prognostic model by apoptosis-related genes to predict survival, immune landscape, and medication in cholangiocarcinoma\",\"authors\":\"Peng Shen , Yinsheng Shi , Pengcheng Xu , Linbin Rao , Zhengfei Wang , Junjie Jiang , Meiling Weng\",\"doi\":\"10.1016/j.clinre.2024.102430\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Cholangiocarcinoma (CCA) is a highly aggressive and invasive malignant tumor of the bile duct, with a poor prognosis and a high mortality rate. 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引用次数: 0
摘要
背景：胆管癌（CCA）是一种侵袭性极强的胆管恶性肿瘤，预后差，死亡率高。目前，尚缺乏有效的靶向治疗方法和可靠的预后生物标志物：方法：我们从癌症基因组图谱（The Cancer Genome Atlas，TCGA）和基因表达总库（Gene Expression Omnibus，GEO）数据库中下载了CCA的RNA-seq和临床数据作为训练集和测试集。凋亡相关基因来自分子特征数据库（Molecular Signatures Database，MsigDB）。我们使用单变量/多变量 Cox 回归和 Lasso 回归分析来构建风险分数预后模型。根据中位风险评分，我们将患者分为高风险（HR）组和低风险（LR）组。我们对 HR 组和 LR 组的差异表达基因（DEGs）进行了基因本体（GO）和京都基因组百科全书（KEGG）富集分析。利用单样本基因组富集分析（ssGSEA）分析了HR组和LR组的免疫浸润情况。利用CellMiner数据库预测药物，并对药物和靶蛋白进行分子对接：结果：我们发现了8个具有预后意义的基因，并构建了一个预后模型。GO和KEGG结果显示，DEGs主要富集在脂肪酸代谢过程等生物学功能和cAMP信号通路等通路中。ssGSEA的结果显示，HR组的免疫细胞（如DCs和巨噬细胞）以及免疫功能（如检查点和副炎症）明显高于LR组。药物敏感性预测和分子对接结果显示，Rigosertib靶向了预后基因MAP3K1.HYPOTHEMYCIN和AMG900有效地靶向了JUN：我们的项目表明，具有凋亡特征的预后模型可以有效预测CCA患者的预后，为CCA患者提供预后生物标志物和潜在的治疗靶点。
The construction of a prognostic model by apoptosis-related genes to predict survival, immune landscape, and medication in cholangiocarcinoma
Background
Cholangiocarcinoma (CCA) is a highly aggressive and invasive malignant tumor of the bile duct, with a poor prognosis and a high mortality rate. Currently, there is a lack of effective targeted treatment methods and reliable biomarkers for prognosis.
Methods
We downloaded RNA-seq and clinical data of CCA from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases as training and test sets. The apoptosis-related genes were obtained from the Molecular Signatures Database (MsigDB) database. We used univariate/multivariate Cox regression and Lasso regression analyses to construct a riskscore prognostic model. Based on the median riskscore, we clustered the patients into high-risk (HR) and low-risk (LR) groups. We carried out Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of differentially expressed genes (DEGs) in HR and LR groups. The single sample gene set enrichment analysis (ssGSEA) was employed to analyze the immune infiltration of the HR and LR groups. The CellMiner database was utilized to predict drugs and perform molecular docking on drugs and target proteins.
Results
We identified 8 genes with prognostic significance to construct a prognostic model. Results of GO and KEGG demonstrated that DEGs were mainly enriched in biological functions such as fatty acid metabolic processes and pathways such as the cAMP signaling pathway. Results of ssGSEA uncovered that immune cells such as DCs and Macrophages in the HR group, as well as immune functions such as Check-point and Parainflammation, were considerably higher than those in the LR group. Drug sensitivity prediction and results of molecular docking revealed that Rigosertib targeted the prognostic genes MAP3K1. HYPOTHEMYCIN and AMG900 effectively targeted JUN.
Conclusion
Our project suggested that the prognostic model with apoptotic features can effectively predict prognosis in CCA patients, proffering prognostic biomarkers and potential therapeutic targets for CCA patients.
期刊介绍：
Clinics and Research in Hepatology and Gastroenterology publishes high-quality original research papers in the field of hepatology and gastroenterology. The editors put the accent on rapid communication of new research and clinical developments and so called "hot topic" issues. Following a clear Editorial line, besides original articles and case reports, each issue features editorials, commentaries and reviews. The journal encourages research and discussion between all those involved in the specialty on an international level. All articles are peer reviewed by international experts, the articles in press are online and indexed in the international databases (Current Contents, Pubmed, Scopus, Science Direct).
Clinics and Research in Hepatology and Gastroenterology is a subscription journal (with optional open access), which allows you to publish your research without any cost to you (unless you proactively chose the open access option). Your article will be available to all researchers around the globe whose institution has a subscription to the journal.
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