Wang Yongling, Yuan Zan, Lao Yi, He Jiangtao, Mo Shufen, Chen Kangbiao, Ye Yanyan, Huang Lu
The First Department of Medical Oncology, Central Hospital of Guangdong Provincial Nongken, Zhanjiang Cancer Hospital, Zhanjiang, China.
Guangdong Medical University, Zhanjiang, China.
PLoS One. 2025 Jul 18;20(7):e0328560. doi: 10.1371/journal.pone.0328560. eCollection 2025.
The exact mechanisms driving colorectal cancer (CRC) are yet to be fully elucidated. This study aims to confirm the reliability of a prognostic model for colon adenocarcinoma (COAD) by analyzing the varied expression levels of Glycolysis & Pyroptosis-Related Differentially Expressed Genes (G&PRDEGs) in COAD using bioinformatics tools.
We retrieved gene expression data and clinical details for COAD patients from the Cancer Genome Atlas (TCGA) database. These data were analyzed to categorize the samples into pyroptosis-positive and pyroptosis-negative groups based on their expression of G&PRDEGs. A prognostic model for COAD was then developed using LASSO Cox regression analysis, focusing on these differentially expressed genes (DEGs). Kaplan-Meier curves were plotted to assess the differences in survival between the two groups. Furthermore, we conducted multivariate Cox regression analyses to evaluate the influence of clinical parameters and model-derived risk scores. Analyses of pathway enrichment were performed using R software, alongside single-sample gene-set enrichment analysis (ssGSEA) to explore the role of immune cells and functions associated with G&PRDEGs.
A predictive model was developed using 53 G&PRDEGs that were expressed differentially. An examination of survival rates revealed that the high-risk groups exhibited a noticeably diminished overall survival (OS) in comparison to the low-risk groups in the TCGA database (P < 0.001). An examination of the receiver operating characteristic (ROC) curve indicated that the risk score effectively predicted outcomes at 1, 3, and 5 years, with a space beneath the curve greater than 0.7. The risk score significantly affected the survival of COAD sufferers in the TCGA database, on the basis of the multivariate Cox regression analysis. The high-risk groups had a hazard ratio (HR) of 3.988 (95% CI 2.865 ~ 5.551, P < 0.001) in contrast to the low-risk groups. Examinations of enrichment identified an increase in the expression of DEGs in the high-risk groups, in contrast to the low-risk cohort, on the basis of the TCGA database. SsGSEA revealed elevated levels of immune cell soakage in the high-risk groups in contrast to the low-risk groups.
The COAD prognosis model, developed using G&PRDEGs, exhibits predictive capability for the prognosis of COAD sufferers and offers utility in prognostic analysis for COAD sufferers.
驱动结直肠癌（CRC）的确切机制尚未完全阐明。本研究旨在通过使用生物信息学工具分析结肠腺癌（COAD）中糖酵解与焦亡相关差异表达基因（G&PRDEGs）的不同表达水平，来确认一种COAD预后模型的可靠性。
我们从癌症基因组图谱（TCGA）数据库中检索了COAD患者的基因表达数据和临床细节。基于这些数据中G&PRDEGs的表达情况，将样本分为焦亡阳性组和焦亡阴性组。然后使用LASSO Cox回归分析，针对这些差异表达基因（DEGs）建立了COAD的预后模型。绘制Kaplan-Meier曲线以评估两组之间的生存差异。此外，我们进行了多变量Cox回归分析，以评估临床参数和模型衍生风险评分的影响。使用R软件进行通路富集分析，同时进行单样本基因集富集分析（ssGSEA），以探索与G&PRDEGs相关的免疫细胞和功能的作用。
利用53个差异表达的G&PRDEGs建立了一个预测模型。生存率检查显示，与TCGA数据库中的低风险组相比，高风险组的总生存期（OS）明显缩短（P < 0.001）。对受试者工作特征（ROC）曲线的检查表明，风险评分在1年、3年和5年时能有效预测结果，曲线下面积大于0.7。基于多变量Cox回归分析，风险评分显著影响了TCGA数据库中COAD患者的生存。与低风险组相比，高风险组的风险比（HR）为3.988（95% CI 2.865 ~ 5.551，P < 0.001）。基于TCGA数据库的富集检查发现，与低风险队列相比，高风险组中DEGs的表达增加。ssGSEA显示，与低风险组相比，高风险组中免疫细胞浸润水平升高。
使用G&PRDEGs建立的COAD预后模型对COAD患者的预后具有预测能力，并在COAD患者的预后分析中具有实用价值。
