Wang Yonghong, Liu Ke, He Wanbin, Dan Jie, Zhu Mingjie, Chen Lei, Zhou Wenjie, Li Ming, Li Jiangpeng
Department of Gastrointestinal Surgery, The People's Hospital of Leshan, Leshan, China.
Front Oncol. 2024 Jul 11;14:1396726. doi: 10.3389/fonc.2024.1396726. eCollection 2024.
Prognostic assessment for colorectal cancer (CRC) displays substantial heterogeneity, as reliance solely on traditional TNM staging falls short of achieving precise individualized predictions. The integration of diverse biological information sources holds the potential to enhance prognostic accuracy.
To establish a comprehensive multi-tiered precision prognostic evaluation system for CRC by amalgamating gene expression profiles, clinical characteristics, and tumor microsatellite instability (MSI) status in CRC patients.
We integrated genomic data, clinical information, and survival follow-up data from 483 CRC patients obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. MSI-related gene modules were identified using differential expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA). Three prognostic models were constructed: MSI-Related Gene Prognostic Model (Model I), Clinical Prognostic Model (Model II), and Integrated Multi-Layered Prognostic Model (Model III) by combining clinical features. Model performance was assessed and compared using Receiver Operating Characteristic (ROC) curves, Kaplan-Meier analysis, and other methods.
Six MSI-related genes were selected for constructing Model I ( = 0.724); Model II used two clinical features ( = 0.684). Compared to individual models, the integrated Model III exhibited superior performance ( = 0.825) and demonstrated good stability in an independent dataset ( = 0.767).
This study successfully developed and validated a comprehensive multi-tiered precision prognostic assessment model for CRC, providing an effective tool for personalized medical management of CRC.
结直肠癌(CRC)的预后评估存在很大异质性,因为仅依靠传统的TNM分期不足以实现精确的个体化预测。整合多种生物信息源有可能提高预后准确性。
通过整合CRC患者的基因表达谱、临床特征和肿瘤微卫星不稳定性(MSI)状态,建立一个全面的多层精准预后评估系统。
我们整合了来自癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)的483例CRC患者的基因组数据、临床信息和生存随访数据。使用差异表达分析和加权基因共表达网络分析(WGCNA)确定MSI相关基因模块。构建了三个预后模型:MSI相关基因预后模型(模型I)、临床预后模型(模型II)和通过结合临床特征的综合多层预后模型(模型III)。使用受试者工作特征(ROC)曲线、Kaplan-Meier分析和其他方法评估和比较模型性能。
选择六个MSI相关基因构建模型I( = 0.724);模型II使用两个临床特征( = 0.684)。与单个模型相比,综合模型III表现出更好的性能( = 0.825),并在独立数据集中表现出良好的稳定性( = 0.767)。
本研究成功开发并验证了一个全面的多层精准CRC预后评估模型,为CRC的个性化医疗管理提供了有效工具。