Department of General Surgery, The First Affiliated Hospital of Jinan University, Guangzhou 510632, China.
International School, Jinan University, Guangzhou, Guangdong 510632, China.
Dis Markers. 2021 Nov 24;2021:4846683. doi: 10.1155/2021/4846683. eCollection 2021.
Colorectal cancer (CRC) is the third most common malignancies worldwide. Ferroptosis is a programmed, iron-dependent cell death observed in cancer cells. However, the prognostic potential and immunotherapy biomarker potential of ferroptosis-related genes (FRGs) in CRC patients remains to be clarified.
At first, we comprehensively analysed the different expression and prognosis of related FRGs in CRC patients based on TCGA cohort. The relationship between functional enrichment of these genes and immune microenvironment in CRC was investigated using the TCGA database. Prognostic model was constructed to determine the association between FRGs and the prognosis of CRC. Relative verification was done based on the GEO database. Meanwhile, the ceRNA network of FRGs in the model was also performed to explore the regulatory mechanisms.
Eight differentially expressed FRGs were associated with the prognosis of CRC patients. Patients from the TCGA database were classified into the A, B, and C FRG clusters with different features. And FRG scores were constructed to quantify the FRG pattern of individual patients with colorectal cancer. The CRC patients with higher FRG score showed worse survival outcomes, higher immune dysfunction, and lower response to immunotherapy. The prognostic model showed a high accuracy for predicting the OS of CRC. Finally, a ceRNA network was analysed to show the concrete regulation mechanisms of critical FRGs in CRC.
The FRG risk score prognostic model based on 8 FRGs exhibit superior predictive performance, providing a novel prognostic model with a high accuracy for CRC patients. Moreover, FRG score can be the potential biomarker of the response of immunotherapy for CRC.
结直肠癌(CRC)是全球第三大常见恶性肿瘤。铁死亡是一种在癌细胞中观察到的程序性、铁依赖性细胞死亡。然而,铁死亡相关基因(FRGs)在 CRC 患者中的预后潜力和免疫治疗生物标志物潜力仍有待阐明。
首先,我们基于 TCGA 队列全面分析了 CRC 患者中相关 FRGs 的不同表达和预后。使用 TCGA 数据库研究这些基因的功能富集与 CRC 免疫微环境之间的关系。构建预后模型以确定 FRGs 与 CRC 预后之间的关联。基于 GEO 数据库进行相对验证。同时,对模型中的 FRGs 的 ceRNA 网络进行了分析,以探讨调控机制。
8 个差异表达的 FRGs 与 CRC 患者的预后相关。来自 TCGA 数据库的患者被分为 A、B 和 C FRG 聚类,具有不同的特征。并且构建了 FRG 评分来量化个体 CRC 患者的 FRG 模式。具有较高 FRG 评分的 CRC 患者的生存结局更差,免疫功能障碍更高,对免疫治疗的反应更低。该预后模型对 CRC 的 OS 具有较高的预测准确性。最后,分析了 ceRNA 网络,以显示 CRC 中关键 FRGs 的具体调控机制。
基于 8 个 FRGs 的 FRG 风险评分预后模型表现出优异的预测性能,为 CRC 患者提供了一种准确性较高的新预后模型。此外,FRG 评分可能是 CRC 免疫治疗反应的潜在生物标志物。