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免疫相关细胞死亡与应激的预后模型揭示了驱动结直肠癌巨噬细胞表型演变的机制。

Prognostic models of immune-related cell death and stress unveil mechanisms driving macrophage phenotypic evolution in colorectal cancer.

作者信息

Liu Hao, Zhang Chuhan, Peng Sanfei, Yin Yuhan, Xu Yishi, Wu Sihan, Wang Liping, Fu Yang

机构信息

Department of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.

Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.

出版信息

J Transl Med. 2025 Jan 28;23(1):127. doi: 10.1186/s12967-025-06143-9.

Abstract

BACKGROUND

Tumor microenvironment (TME), particularly immune cell infiltration, programmed cell death (PCD) and stress, has increasingly become a focal point in colorectal cancer (CRC) treatment. Uncovering the intricate crosstalk between these factors can enhance our understanding of CRC, guide therapeutic strategies, and improve patient prognosis.

METHODS

We constructed an immune-related cell death and stress (ICDS) prognostic model utilizing machine learning methodologies. Furthermore, we performed enrichment analyses and deconvolution algorithms to elucidate the complex interactions between immune cell infiltration and the processes of PCD and stress within a substantial array of transcriptomic data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus data base (GEO) related to CRC. Single-cell sequencing and biochemical experiments were used to validate the interaction between the model genes and programmed cell death in tumor cells.

RESULTS

The ICDS prognostic model exhibited robust predictive performance in seven independent cohorts, revealing an inverse correlation between model scores and patient prognosis. Meanwhile, the ICDS index was positively correlated with clinical stage. Model analysis indicated that patient subgroups with low ICDS index exhibited heightened immune activation features and elevated activity in PCD and stress pathways. Single-cell analysis further revealed that macrophages were the central drivers of immune characteristics underlying prognostic differences within the ICDS prognostic model. Pseudotime analysis and cellular experiments indicated that the model gene GAL3ST4 promotes the transition of macrophages toward an M2 pro-tumor phenotype. Furthermore, cell communication analysis and experimental validation revealed that the cuproptosis in tumor cells suppress GAL3ST4 expression, thereby inhibiting M2-like macrophage polarization.

CONCLUSION

In summary, we constructed the ICDS prognostic model and uncovered the mechanism by which tumor cells downregulate GAL3ST4 expression via cuproptosis to inhibit M2-like macrophage polarization, providing new targets and biomarkers for CRC treatment and prognosis evaluation.

摘要

背景

肿瘤微环境(TME),尤其是免疫细胞浸润、程序性细胞死亡(PCD)和应激,已日益成为结直肠癌(CRC)治疗的焦点。揭示这些因素之间复杂的相互作用可以增进我们对CRC的理解,指导治疗策略,并改善患者预后。

方法

我们利用机器学习方法构建了一个免疫相关细胞死亡与应激(ICDS)预后模型。此外,我们进行了富集分析和反卷积算法,以阐明来自癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)的大量与CRC相关的转录组数据中免疫细胞浸润与PCD和应激过程之间的复杂相互作用。使用单细胞测序和生化实验来验证模型基因与肿瘤细胞中程序性细胞死亡之间的相互作用。

结果

ICDS预后模型在七个独立队列中表现出强大的预测性能,揭示了模型评分与患者预后之间的负相关。同时,ICDS指数与临床分期呈正相关。模型分析表明,ICDS指数低的患者亚组表现出增强的免疫激活特征以及PCD和应激途径的活性升高。单细胞分析进一步表明,巨噬细胞是ICDS预后模型中预后差异潜在免疫特征的核心驱动因素。伪时间分析和细胞实验表明,模型基因GAL3ST4促进巨噬细胞向M2促肿瘤表型的转变。此外,细胞通讯分析和实验验证表明,肿瘤细胞中的铜死亡抑制GAL3ST4表达,从而抑制M2样巨噬细胞极化。

结论

总之,我们构建了ICDS预后模型,并揭示了肿瘤细胞通过铜死亡下调GAL3ST4表达以抑制M2样巨噬细胞极化的机制,为CRC治疗和预后评估提供了新的靶点和生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edde/11776142/4764bd8b56d2/12967_2025_6143_Fig1_HTML.jpg

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