Raw data of qRT-PCR.

Colon cancer, as a highly prevalent malignant tumor globally, poses a significant threat to human health. In recent years, ferroptosis and cuproptosis, as two novel forms of cell death, have attracted widespread attention for their potential roles in the development and treatment of colon cancer. However, the investigation into the subtypes and their impact on the survival of colon cancer patients remains understudied. In this study, utilizing data from TCGA and GEO databases, we examined the expression differences of ferroptosis and cuproptosis-related genes in colon cancer and identified two subtypes. Through functional analysis and bioinformatics methods, we elucidated pathway differences and biological characteristics between these two subtypes. By leveraging differential genes between the two subtypes, we constructed a prognostic model using univariate Cox regression and multivariate Cox regression analysis as well as LASSO regression analysis. Further survival analysis and receiver operating characteristic curve analysis demonstrated the model’s high accuracy. To enhance its clinical utility, we evaluated the clinical significance of the model and constructed a nomogram, significantly improving the predictive ability of the model and providing a new tool for prognostic assessment of colon cancer patients. Subsequently, through immune-related analysis, we revealed differences in immune cell infiltration and immune function between high- and low-risk groups. Further analysis of the relationship between the model and immune cells and functions revealed potential therapeutic targets. Drug sensitivity analysis revealed associations between the expression of model-related genes and drug sensitivity, suggesting their involvement in tumor resistance through certain mechanisms. AZD8055_1059, Bortezomib_1191, Dihydrorotenone_1827, and MG-132_1862 were more sensitive in the high-risk group. Finally, we analyzed differential expression of model-related genes between tumor tissues and normal tissues, validated through real-time quantitative PCR and immunohistochemistry. In summary, our study provides a relatively accurate prognostic tool for colon cancer patients, offering guidance for treatment selection and indicating the potential of immunotherapy in colon cancer.结直肠癌（Colon cancer）作为全球高发的恶性肿瘤，对人类健康构成严重威胁。近年来，铁死亡（ferroptosis）与铜死亡（cuproptosis）这两种新型细胞死亡形式，因其在结直肠癌发生发展与治疗中的潜在作用而受到广泛关注。然而，目前针对结直肠癌中铁死亡与铜死亡相关亚型及其对患者生存的影响研究仍较为匮乏。本研究依托癌症基因组图谱（TCGA, The Cancer Genome Atlas）与基因表达综合数据库（GEO, Gene Expression Omnibus）的数据集，分析了结直肠癌中铁死亡与铜死亡相关基因的表达差异，并鉴定出两种亚型。通过功能分析与生物信息学方法，本研究阐明了这两种亚型之间的通路差异与生物学特征。基于两种亚型间的差异表达基因，本研究通过单因素Cox回归、多因素Cox回归以及LASSO回归分析构建了预后模型。进一步的生存分析与受试者工作特征曲线（ROC, Receiver Operating Characteristic）分析证实，该模型具有较高的预测准确性。为提升模型的临床实用性，本研究评估了该模型的临床意义并构建了列线图（nomogram），显著提升了模型的预测能力，为结直肠癌患者的预后评估提供了全新工具。随后，通过免疫相关分析，本研究揭示了高风险组与低风险组之间免疫细胞浸润与免疫功能的差异。进一步分析模型与免疫细胞、免疫功能的关联，发掘出潜在的治疗靶点。药物敏感性分析显示，模型相关基因的表达与药物敏感性存在关联，提示其可能通过特定机制参与肿瘤耐药。其中，AZD8055_1059、硼替佐米（Bortezomib_1191）、二氢鱼藤酮（Dihydrorotenone_1827）与MG-132_1862在高风险组中展现出更高的药物敏感性。最后，本研究分析了模型相关基因在肿瘤组织与正常组织中的差异表达，并通过实时定量聚合酶链反应（qPCR, real-time quantitative PCR）与免疫组织化学（IHC, immunohistochemistry）进行了验证。综上，本研究为结直肠癌患者提供了一款较为精准的预后工具，可为治疗方案选择提供指导，并提示了结直肠癌免疫治疗的潜在应用价值。