Identification of anoikis-related genes to develop a risk model and predict the prognosis and tumor microenvironment in rectal adenocarcinoma.

IF 2.8 3区生物学 Q2 GENETICS & HEREDITY

Frontiers in Genetics Pub Date : 2025-08-18 eCollection Date: 2025-01-01 DOI:10.3389/fgene.2025.1604541

Bing Zhao, Xuegui Tang

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引用次数: 0

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusion: The risk model of ARGs can effectively predict READ prognosis and provide potential therapeutic targets.

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鉴定嗜酸相关基因，建立风险模型，预测直肠腺癌预后及肿瘤微环境。

背景：直肠腺癌（READ）是一种常见的恶性肿瘤。本研究旨在建立基于anoiisk -related genes （ARGs）的风险模型来预测READ患者的预后和肿瘤微环境。方法：使用从TCGA和GEO数据库下载的转录组学数据和临床数据进行差异分析和Cox回归分析。建立了基于args的READ预后风险模型。绘制生存曲线和ROC曲线，以确定模型对READ患者的预测能力。模型在GSE87211数据集中进行外部验证。通过nomogram、免疫分析、药物敏感性分析、功能富集分析等方法对模型进行了综合验证。结果：风险模型包括6个预后基因（ALDH1A1、BRCA1、GSN、KRT17、SCD、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曲线显示低危组预后较好。TCGA训练队列、测试队列和GSE87211数据集的1年、3年和5年总生存率AUC分别为（0.962,0.923,0.956）、（0.887,0.838,0.833）和（0.73,0.817,0.743）。nomogram显示，风险评分可以作为总体生存的独立预测因子。药物敏感性分析显示高危组与低危组之间OSI-027、PLX-4720、uni -77、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主要富集于与肿瘤发生相关的途径和生物学过程中。结论：ARGs风险模型可有效预测READ预后，提供潜在的治疗靶点。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Frontiers in Genetics Biochemistry, Genetics and Molecular Biology-Molecular Medicine

CiteScore

5.50

自引率

8.10%

发文量

3491

审稿时长

14 weeks

期刊介绍： Frontiers in Genetics publishes rigorously peer-reviewed research on genes and genomes relating to all the domains of life, from humans to plants to livestock and other model organisms. Led by an outstanding Editorial Board of the world’s leading experts, this multidisciplinary, open-access journal is at the forefront of communicating cutting-edge research to researchers, academics, clinicians, policy makers and the public. The study of inheritance and the impact of the genome on various biological processes is well documented. However, the majority of discoveries are still to come. A new era is seeing major developments in the function and variability of the genome, the use of genetic and genomic tools and the analysis of the genetic basis of various biological phenomena.