Zhao Bing, Tang Xuegui
Department of Integrated Traditional and Western Medicine Anorectal, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Anorectal Department, Affiliated Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Front Genet. 2025 Aug 18;16:1604541. doi: 10.3389/fgene.2025.1604541. eCollection 2025.
Rectal adenocarcinoma (READ) is a common malignant tumor. This study aims to establish a risk model based on anoikis-related genes (ARGs) to predict prognosis and the tumor microenvironment in READ.
Transcriptomic data and clinical data downloaded from the TCGA and GEO databases were used for differential analysis and Cox regression analysis. An ARGs-based prognostic risk model was constructed for READ. The survival curves and ROC curves were plotted to determine the predictive ability of the model for READ patients. The model was externally validated in the GSE87211 dataset. A nomogram, immune analysis, drug sensitivity analysis, and functional enrichment analysis were also performed to comprehensively validate the model.
The risk model included 6 prognostic genes (ALDH1A1, BRCA1, GSN, KRT17, SCD, and SNCG). Kaplan-Meier curves for the TCGA training cohort (P < 0.0001), testing cohort (P = 0.018), and GSE87211 dataset (P = 0.036) showed better prognoses in the low-risk group. The AUC for 1-year, 3-year, and 5-year overall survival in the TCGA training cohort, testing cohort, and GSE87211 dataset were (0.962, 0.923, 0.956), (0.887, 0.838, 0.833), and (0.73, 0.817, 0.743), respectively. The nomogram showed that the risk score served as an independent predictor of overall survival. Drug sensitivity analysis revealed differences in the IC50 values of OSI-027, PLX-4720, UMI-77, and Sapitinib between the high-risk and low-risk groups. Immune microenvironment analysis suggested distinct differences in immune cells between the two risk groups. Enrichment analysis revealed that these prognostic ARGs were primarily enriched in pathways and biological processes related to tumorigenesis.
The risk model of ARGs can effectively predict READ prognosis and provide potential therapeutic targets.
直肠腺癌（READ）是一种常见的恶性肿瘤。本研究旨在建立一种基于失巢凋亡相关基因（ARGs）的风险模型，以预测READ的预后和肿瘤微环境。
从TCGA和GEO数据库下载的转录组数据和临床数据用于差异分析和Cox回归分析。构建了基于ARGs的READ预后风险模型。绘制生存曲线和ROC曲线以确定该模型对READ患者的预测能力。该模型在GSE87211数据集中进行了外部验证。还进行了列线图、免疫分析、药物敏感性分析和功能富集分析，以全面验证该模型。
风险模型包括6个预后基因（ALDH1A1、BRCA1、GSN、KRT17、SCD和SNCG）。TCGA训练队列（P < 0.0001）、测试队列（P = 0.018）和GSE87211数据集（P = 0.036）的Kaplan-Meier曲线显示，低风险组的预后更好。TCGA训练队列、测试队列和GSE87211数据集中1年、3年和5年总生存率的AUC分别为（0.962、0.923、0.956）、（0.887、0.838、0.833）和（0.73、0.817、0.743）。列线图显示风险评分是总生存的独立预测因子。药物敏感性分析显示，高风险组和低风险组之间OSI-027、PLX-4720、UMI-77和Sapitinib的IC50值存在差异。免疫微环境分析表明，两个风险组之间的免疫细胞存在明显差异。富集分析显示，这些预后ARGs主要富集在与肿瘤发生相关的通路和生物学过程中。
ARGs风险模型可以有效预测READ的预后，并提供潜在的治疗靶点。
