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胃癌中黏着斑相关基因特征的开发与验证

Development and validation of focal adhesion-related genes signature in gastric cancer.

作者信息

Zhao Guanghui, Luo Tianqi, Liu Zexian, Li Jianjun

机构信息

Department of Endoscopy, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, China.

Department of Musculoskeletal Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, China.

出版信息

Front Genet. 2023 Mar 8;14:1122580. doi: 10.3389/fgene.2023.1122580. eCollection 2023.

DOI:10.3389/fgene.2023.1122580
PMID:36968601
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10030739/
Abstract

This study aims to build a focal adhesion-related genes-based prognostic signature (FAS) to accurately predict gastric cancer (GC) prognosis and identify key prognostic genes related to gastric cancer. Gene expression and clinical data of gastric cancer patients were sourced from Gene Expression Omnibus and The Cancer Genome Atlas. Subsequently, the GEO dataset was randomly distributed into training and test cohorts. The TCGA dataset was used to validate the external cohort. Lasso Cox regression was used to detect OS-related genes in the GEO cohort. A risk score model was established according to the screened genes. A nomogram, based on the clinical characteristics and risk score, was generated to predict the prognosis of gastric cancer patients. Using time-dependent receiver operating characteristic (ROC) and calibration performances, we evaluated the models' validity. The patients were grouped into a high- or low-risk group depending on the risk score. Low-risk patients exhibited higher OS than high-risk patients (entire cohort: < 0.001; training cohort: < 0.001, test cohort: < 0.001). Furthermore, we found a correlation between high-risk gastric cancer and extracellular matrix (ECM) receptor interaction, high infiltration of macrophages, CD44, and HLA-DOA. The generated model based on the genetic characteristics of the focal adhesion prognostic gene can aid in the prognosis of gastric cancer patients in the future.

摘要

本研究旨在构建一种基于粘着斑相关基因的预后特征（FAS），以准确预测胃癌（GC）的预后，并识别与胃癌相关的关键预后基因。胃癌患者的基因表达和临床数据来源于基因表达综合数据库（Gene Expression Omnibus）和癌症基因组图谱（The Cancer Genome Atlas）。随后，将基因表达综合数据库数据集随机分为训练组和测试组。癌症基因组图谱数据集用于验证外部队列。采用套索Cox回归在基因表达综合数据库队列中检测与总生存期（OS）相关的基因。根据筛选出的基因建立风险评分模型。基于临床特征和风险评分生成列线图，以预测胃癌患者的预后。使用时间依赖的受试者工作特征（ROC）曲线和校准性能评估模型的有效性。根据风险评分将患者分为高风险组或低风险组。低风险患者的总生存期高于高风险患者（整个队列：<0.001；训练队列：<0.001，测试队列：<0.001）。此外，我们发现高风险胃癌与细胞外基质（ECM）受体相互作用、巨噬细胞高浸润、CD44和HLA-DOA之间存在相关性。基于粘着斑预后基因遗传特征生成的模型未来可有助于胃癌患者的预后评估。

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