An integrative analysis based on multiple cell death patterns identifies an immunosuppressive subtype and establishes a prognostic signature in lower-grade glioma.

Annals of medicine Pub Date : 2024-12-01 Epub Date: 2024-10-10 DOI:10.1080/07853890.2024.2412831
Hao Lian, Jiajia Wang, Shan Yan, Kui Chen, Lilun Jin
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Abstract

Background: Cell death modulates the biological behaviors of tumors. However, the comprehensive role of the multiple forms of cell death in lower-grade glioma (LGG) is unknown.

Methods: We collected the transcriptional data of LGG patients from public repositories to comprehensively examine six cell death patterns (autophagy, apoptosis, cuproptosis, necroptosis, ferroptosis, and pyroptosis) in LGG samples and systematically correlated these patterns with patient survival, underlying biological processes, and drug sensitivity using serial bioinformatics analysis, clinical sample validation and in vitro assays.

Results: We identified and independently validated three reproducible cell death-based clusters associated with distinct clinical outcomes and tumor microenvironment characteristics. The Tumor Immune Dysfunction and Exclusion algorithm was applied for predicting how these three clusters would respond to immune checkpoint blockade (ICB) therapy; we found potential resistance of cluster B to ICB therapy. We also performed drug screening to identify cluster-specific drugs. Furthermore, a scoring system, designated as the CDPM score, was developed to estimate the cell death patterns of patients with LGG; this system could predict both LGG patients' prognosis and immunotherapy efficacy. By performing multiplex immunofluorescence staining, we validated the correlations of GNAL expression with the molecular and clinical features of LGG in an independent LGG cohort. Finally, in vitro assays showed that GNAL promoted apoptosis and inhibited the proliferation of LGG cells.

Conclusion: The new cell death-based subtype system indicates several features of LGG biology and reveals novel insights into the use of precision medicine for treating LGG. The CDPM score could be used to predict the immunotherapy response and prognosis of LGG patients; moreover, it could indicate a novel direction for improving LGG management.

基于多种细胞死亡模式的综合分析确定了一种免疫抑制亚型,并建立了低级别胶质瘤的预后特征。
背景:细胞死亡可调节肿瘤的生物学行为。然而,多种细胞死亡形式在低级别胶质瘤(LGG)中的综合作用尚不清楚:我们从公共资料库中收集了 LGG 患者的转录数据,全面研究了 LGG 样本中的六种细胞死亡模式(自噬、凋亡、杯突、坏死、铁突和热突),并利用系列生物信息学分析、临床样本验证和体外检测系统地将这些模式与患者生存、潜在的生物学过程和药物敏感性相关联:结果:我们发现并独立验证了三个可重复的细胞死亡集群,它们与不同的临床结果和肿瘤微环境特征相关。我们应用肿瘤免疫功能失调和排除算法预测了这三个群集对免疫检查点阻断疗法(ICB)的反应;我们发现群集B对ICB疗法有潜在耐药性。我们还进行了药物筛选,以确定群组特异性药物。此外,我们还开发了一套评分系统,称为CDPM评分,用于评估LGG患者的细胞死亡模式;这套系统可以预测LGG患者的预后和免疫疗法的疗效。通过进行多重免疫荧光染色,我们在一个独立的LGG队列中验证了GNAL表达与LGG分子和临床特征的相关性。最后,体外实验表明,GNAL能促进LGG细胞凋亡并抑制其增殖:结论:新的基于细胞死亡的亚型系统显示了LGG生物学的几个特征,并揭示了使用精准医学治疗LGG的新见解。CDPM评分可用于预测LGG患者的免疫治疗反应和预后;此外,它还为改善LGG管理指明了新的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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