Suppr超能文献

一种基于新型DNA损伤与DNA修复相关基因特征的结肠癌预后评估指标的鉴定与验证

Identification and Validation of a Novel DNA Damage and DNA Repair Related Genes Based Signature for Colon Cancer Prognosis.

作者信息

Wang Xue-Quan, Xu Shi-Wen, Wang Wei, Piao Song-Zhe, Mao Xin-Li, Zhou Xian-Bin, Wang Yi, Wu Wei-Dan, Ye Li-Ping, Li Shao-Wei

机构信息

Laboratory of Cellular and Molecular Radiation Oncology, Department of Radiation Oncology, Radiation Oncology Institute of Enze Medical Health Academy, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou, China.

Key Laboratory of Minimally Invasive Techniques & Rapid Rehabilitation of Digestive System Tumor of Zhejiang Province, Linhai, China.

出版信息

Front Genet. 2021 Feb 24;12:635863. doi: 10.3389/fgene.2021.635863. eCollection 2021.

Abstract

Colorectal cancer (CRC) with high incidence, has the third highest mortality of tumors. DNA damage and repair influence a variety of tumors. However, the role of these genes in colon cancer prognosis has been less systematically investigated. Here, we aim to establish a corresponding prognostic signature providing new therapeutic opportunities for CRC. After related genes were collected from GSEA, univariate Cox regression was performed to evaluate each gene's prognostic relevance through the TCGA-COAD dataset. Stepwise COX regression was used to establish a risk prediction model through the training sets randomly separated from the TCGA cohort and validated in the remaining testing sets and two GEO datasets (GSE17538 and GSE38832). A 12-DNA-damage-and-repair-related gene-based signature able to classify COAD patients into high and low-risk groups was developed. The predictive ability of the risk model or nomogram were evaluated by different bioinformatics- methods. Gene functional enrichment analysis was performed to analyze the co-expressed genes of the risk-based genes. A 12-gene based prognostic signature established within 160 significant survival-related genes from DNA damage and repair related gene sets performed well with an AUC of ROC 0.80 for 5 years in the TCGA-CODA dataset. The signature includes CCNB3, ISY1, CDC25C, SMC1B, MC1R, LSP1P4, RIN2, TPM1, ELL3, POLG, CD36, and NEK4. Kaplan-Meier survival curves showed that the prognosis of the risk status owns more significant differences than T, M, N, and stage prognostic parameters. A nomogram was constructed by LASSO regression analysis with T, M, N, age, and risk as prognostic parameters. ROC curve, C-index, Calibration analysis, and Decision Curve Analysis showed the risk module and nomogram performed best in years 1, 3, and 5. KEGG, GO, and GSEA enrichment analyses suggest the risk involved in a variety of important biological processes and well-known cancer-related pathways. These differences may be the key factors affecting the final prognosis. The established gene signature for CRC prognosis provides a new molecular tool for clinical evaluation of prognosis, individualized diagnosis, and treatment. Therapies based on targeted DNA damage and repair mechanisms may formulate more sensitive and potential chemotherapy regimens, thereby expanding treatment options and potentially improving the clinical outcome of CRC patients.

摘要

结直肠癌(CRC)发病率高,是肿瘤死亡率第三高的癌症。DNA损伤与修复影响多种肿瘤。然而,这些基因在结肠癌预后中的作用尚未得到系统研究。在此,我们旨在建立一种相应的预后特征,为CRC提供新的治疗机会。从基因集富集分析(GSEA)中收集相关基因后,通过TCGA-COAD数据集进行单因素Cox回归,以评估每个基因的预后相关性。通过从TCGA队列中随机分离出的训练集建立风险预测模型,并在其余测试集和两个基因表达综合数据库(GEO)数据集(GSE17538和GSE38832)中进行验证。开发了一种基于12个DNA损伤与修复相关基因的特征,能够将COAD患者分为高风险组和低风险组。通过不同的生物信息学方法评估风险模型或列线图的预测能力。进行基因功能富集分析,以分析基于风险的基因的共表达基因。在来自DNA损伤与修复相关基因集的160个与生存显著相关的基因中建立的基于12个基因的预后特征在TCGA-CODA数据集中5年的受试者工作特征曲线(ROC)下面积(AUC)为0.80,表现良好。该特征包括CCNB3、ISY1、CDC25C、SMC1B、MC1R、LSP1P4、RIN2、TPM1、ELL3、POLG、CD36和NEK4。Kaplan-Meier生存曲线显示,风险状态的预后差异比T、M、N和分期预后参数更显著。通过LASSO回归分析构建列线图,将T、M、N、年龄和风险作为预后参数。ROC曲线、C指数、校准分析和决策曲线分析表明,风险模型和列线图在第1、3和5年表现最佳。京都基因与基因组百科全书(KEGG)、基因本体论(GO)和基因集富集分析(GSEA)表明,该风险涉及多种重要的生物学过程和著名的癌症相关通路。这些差异可能是影响最终预后的关键因素。建立的CRC预后基因特征为临床预后评估、个体化诊断和治疗提供了一种新的分子工具。基于靶向DNA损伤与修复机制的疗法可能制定出更敏感和有潜力的化疗方案,从而扩大治疗选择并可能改善CRC患者的临床结局。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验