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基于机器学习框架鉴定结直肠癌中一种新型铁死亡诱导的免疫原性细胞死亡相关特征。

Identification of a novel ferroptosis-induced immunogenic cell death related signature based on a machine learning framework in colorectal cancer.

作者信息

Zhu Feng, Liu Xin, Li Huiyuan, Li Jianfeng, Liu Hongzhang, Wang Yusheng

机构信息

General Surgery Department, Jincheng People's Hospital, 1666 BaiShui East Street, Jincheng, 048026, Shanxi, China.

General Surgery Department, Jincheng Hospital Affiliated to Changzhi Medical College, 1666 BaiShui East Street, Jincheng, 048026, Shanxi, China.

出版信息

Discov Oncol. 2025 Jul 9;16(1):1289. doi: 10.1007/s12672-025-03147-1.

Abstract

BACKGROUND

Ferroptosis and immunogenic cell death play vital roles in colorectal cancer (CRC). The interplay between ferroptosis and immunogenic cell death (F-ICD) represents a promising frontier in cancer therapy. However, few studies have explored the combined regulatory effects of F-ICD in CRC.

METHODS

In current study, we identified F-ICD related genes based on analysis of single-cell transcriptomics level and developed F-ICD related signature using 101 machine learning algorithms and WGCNA analysis. Differential analysis between normal and tumor samples was performed using DESeq2 (|logFC|>1, p. adj < 0.05). The RSF algorithm was chosen for further analysis due to its strong predictive performance, making it a robust tool for our study. An external validation was performed to access the expression level of seven key F-ICD related genes.

RESULTS

By quantifying the expression levels of 44 genes related to F-ICD, we found that F-ICD activity was significantly elevated in NK cells, T cells, and some B cells. The module showed a significant correlation with the F-ICD score (r = 0.66). The predictive model had highly accurate AUCs in three datasets (0.99, 0.61, and 0.58 for the 3-years training sets), revealing the importance of F-ICD in different pathological stages and prognoses in CRC. Further results indicated that F-ICD was associated with pathways such as oxidative phosphorylation and NF-κB signaling. Patients with high F-ICD had significantly different mutation profiles and poorer prognoses.

CONCLUSION

This study developed a novel signature integrating ferroptosis and immunogenic cell death, creating a valuable model for predicting prognosis and the tumor immune environment in CRC. Furthermore, seven key genes emerged as promising targets for further investigation and therapeutic intervention, highlighting their potential role in ferroptosis and immunogenic cell death.

摘要

背景

铁死亡和免疫原性细胞死亡在结直肠癌(CRC)中起着至关重要的作用。铁死亡与免疫原性细胞死亡之间的相互作用(F-ICD)是癌症治疗中一个有前景的前沿领域。然而,很少有研究探讨F-ICD在CRC中的联合调节作用。

方法

在本研究中,我们基于单细胞转录组学水平分析鉴定了F-ICD相关基因,并使用101种机器学习算法和WGCNA分析开发了F-ICD相关特征。使用DESeq2(|logFC|>1,p.adj < 0.05)对正常样本和肿瘤样本进行差异分析。由于其强大的预测性能,选择RSF算法进行进一步分析,使其成为我们研究的一个强大工具。进行外部验证以评估七个关键F-ICD相关基因的表达水平。

结果

通过量化44个与F-ICD相关基因的表达水平,我们发现F-ICD活性在自然杀伤细胞、T细胞和一些B细胞中显著升高。该模块与F-ICD评分显示出显著相关性(r = 0.66)。预测模型在三个数据集中具有高度准确的AUC(3年训练集分别为0.99、0.61和0.58),揭示了F-ICD在CRC不同病理阶段和预后中的重要性。进一步结果表明,F-ICD与氧化磷酸化和NF-κB信号传导等通路相关。F-ICD高的患者具有显著不同的突变谱和较差的预后。

结论

本研究开发了一种整合铁死亡和免疫原性细胞死亡的新型特征,为预测CRC的预后和肿瘤免疫环境创建了一个有价值的模型。此外,七个关键基因成为进一步研究和治疗干预中有前景的靶点,突出了它们在铁死亡和免疫原性细胞死亡中的潜在作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e18/12240883/ab028bd6023f/12672_2025_3147_Fig1_HTML.jpg

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