Table_1_A Ferroptosis-Related Gene Signature Identified as a Novel Prognostic Biomarker for Colon Cancer.XLSX

BackgroundColon cancer (CC) is a common gastrointestinal malignant tumor with high heterogeneity in clinical behavior and response to treatment, making individualized survival prediction challenging. Ferroptosis is a newly discovered iron-dependent cell death that plays a critical role in cancer biology. Therefore, identifying a prognostic biomarker with ferroptosis-related genes provides a new strategy to guide precise clinical decision-making in CC patients.
MethodsAlteration in the expression profile of ferroptosis-related genes was initially screened in GSE39582 dataset involving 585 CC patients. Univariate Cox regression analysis and LASSO-penalized Cox regression analysis were combined to further identify a novel ferroptosis-related gene signature for overall survival prediction. The prognostic performance of the signature was validated in the GSE17536 dataset by Kaplan-Meier survival curve and time-dependent ROC curve analyses. Functional annotation of the signature was explored by integrating GO and KEGG enrichment analysis, GSEA analysis and ssGSEA analysis. Furthermore, an outcome risk nomogram was constructed considering both the gene signature and the clinicopathological features.
ResultsThe prognostic signature biomarker composed of 9 ferroptosis-related genes accurately discriminated high-risk and low-risk patients with CC in both the training and validation datasets. The signature was tightly linked to clinicopathological features and possessed powerful predictive ability for distinct clinical subgroups. Furthermore, the risk score was confirmed to be an independent prognostic factor for CC patients by multivariate Cox regression analysis (p < 0.05). Functional annotation analyses showed that the prognostic signature was closely correlated with pivotal cancer hallmarks, particularly cell cycle, transcriptional regulation, and immune-related functions. Moreover, a nomogram with the signature was also built to quantify outcome risk for each patient.
ConclusionThe novel ferroptosis-related gene signature biomarker can be utilized for predicting individualized prognosis, optimizing survival risk assessment and facilitating personalized management of CC patients.

背景：结直肠癌（Colon cancer, CC）是一类常见的消化道恶性肿瘤，其临床行为与治疗响应存在高度异质性，这使得个体化生存预测面临极大挑战。铁死亡（Ferroptosis）是新近发现的一种铁依赖性细胞死亡方式，在肿瘤生物学进程中发挥关键调控作用。因此，筛选基于铁死亡相关基因的预后生物标志物，可为结直肠癌患者的精准临床决策提供全新思路。
方法：首先在包含585例结直肠癌患者的GSE39582数据集中，初步筛选铁死亡相关基因的表达谱异常情况。随后联合单变量Cox回归分析与LASSO惩罚Cox回归分析，进一步构建用于总生存预测的新型铁死亡相关基因特征。通过Kaplan-Meier生存曲线及时间依赖性ROC曲线分析，在GSE17536数据集中验证该基因特征的预后效能。通过整合GO富集分析、KEGG富集分析、GSEA分析及ssGSEA分析，对该基因特征开展功能注释研究。此外，结合该基因特征与临床病理特征，构建了预后风险列线图（nomogram）。
结果：由9个铁死亡相关基因构成的预后特征生物标志物，在训练数据集与验证数据集中均可精准区分结直肠癌高风险与低风险患者。该特征与临床病理特征显著相关，且对不同临床亚组具备优异的预测能力。多变量Cox回归分析证实，风险评分可作为结直肠癌患者的独立预后因素（p < 0.05）。功能注释分析显示，该预后特征与核心肿瘤特征密切相关，尤其涉及细胞周期、转录调控及免疫相关功能。此外，基于该基因特征构建的列线图可实现对每位患者预后风险的量化评估。
结论：该新型铁死亡相关基因特征生物标志物可用于预测结直肠癌患者的个体化预后，优化生存风险评估流程，并助力结直肠癌患者的个性化临床管理。