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开发和验证基于G2M签名的预后模型,用于分层化结肠癌预后

Xin Song¹, Yan Dou¹, Xiaoyong Shen²

¹National Demonstration Center for Experimental Basic Medicine Education, School of Basic Medical Sciences, Tianjin Medical University, Qixiangtai Road No.22, Heping District, Tianjin, 300070, China.

Discover oncology

|August 10, 2025

概括

这项研究开发了一种使用G2M基因用于结肠癌的新预后模型,确定了9个关键基因. 该模型准确预测患者的生存率和风险,帮助临床决策.

科学领域:

在瘤学瘤学.
基因组学就是基因组学.
生物信息学是一种生物信息学.

背景情况:

结肠癌预后需要改进预测模型.
G2M细胞周期阶段对于癌症的进展至关重要.

研究的目的:

开发一个整合G2M相关基因用于结肠癌预后的预测模型.
确定关键的G2M基因及其在结肠癌临床进展中的作用.

主要方法:

使用了TCGA-COAD和GEO数据集 (GSE39582,GSE17536,GSE17537) 的数据集.
使用LASSO应用考克斯回归来识别预后基因.
开发了一种预后诺莫格拉姆,整合了风险评分和临床参数.

主要成果:

鉴定了九个枢纽G2M基因 (BRIP1,CDCA2,HMGCR,HOXC10,PSMA5,PSMD6,SIX4,SLC12A2,SPA17)).这些基因的基因组分为三种.
G2M预后模型将患者分为高风险和低风险组,具有不同的生存结果.
风险分层与免疫细胞透和细胞外矩阵事件相关.
开发了Nomogram来预测1年,3年和5年的生存率.

结论:

基于G2M相关基因的创新预后模型被开发用于结肠癌.
与G2M相关的基因在结肠癌的临床进展中发挥着关键作用.

关键词:

大肠癌是什么意思大肠癌是什么意思在 G2M 中,G2M 是地理地质组织 (GEO) 是指地理地质组织.预测预测预测预测在TCGA中,它是TCGA.

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