School of Public Health, Gansu University of Chinese Medicine, Lanzhou, Gansu, China.
Department of Biomedical Sciences, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Kepala Batas, Penang, Malaysia.
Front Immunol. 2024 Nov 1;15:1483498. doi: 10.3389/fimmu.2024.1483498. eCollection 2024.
Cell death mechanisms are integral to the pathogenesis of breast cancer (BC), with ATP-induced cell death (AICD) attracting increasing attention due to its distinctive specificity and potential therapeutic applications.
This study employed genomic methodologies to investigate the correlation between drug sensitivity and types of AICD in BC. Initially, data from TCGA were utilized to construct a prognostic model and classification system for AICD. Subsequently, a series of bioinformatics analyses assessed the prognostic and clinical significance of this model within the context of BC.
Analysis revealed a cohort of 18 genes associated with AICD, exhibiting prognostic relevance. Survival analyses indicated that overall survival rates were significantly lower in high-risk populations compared to their low-risk counterparts. Furthermore, prognostic indicators linked to AICD demonstrated high accuracy in predicting survival outcomes in BC. Immunological assessments indicated heightened expression of anti-tumor infiltrating immune cells and immune checkpoint molecules in low-risk populations, correlating with various anti-tumor immune functions. Ultimately, a comprehensive prognostic model related to AICD was developed through univariate analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis. As Adenosine triphosphate (ATP) concentration increased, the viability of BC cells exhibited a general decline at each time point. Notably, ATP diminished the mitochondrial membrane potential in BC cells while enhancing it in normal breast epithelial cells. Additionally, ATP inhibited the migration of BC cells and promoted their apoptosis. ATP also stimulated reactive oxygen species (ROS) production in MCF-10A cells, with implications for the immune response in BC cells. Compared to the control group, expression levels of , , and were significantly reduced in the ATP intervention group, whereas expression was elevated. , , and share genetic variants with BC, while does not exhibit genetic causal variation with the disease.
A valuable prognostic model associated with AICD has been established, capable of accurately predicting BC prognosis. The induction of cell death by ATP appears to play a protective role in BC progression. These findings carry significant implications for the implementation of personalized and tailored treatment strategies for BC patients.
细胞死亡机制是乳腺癌（BC）发病机制的重要组成部分，由于其独特的特异性和潜在的治疗应用，ATP 诱导的细胞死亡（AICD）引起了越来越多的关注。
本研究采用基因组学方法研究了 BC 中药物敏感性与 AICD 类型之间的相关性。首先，利用 TCGA 数据构建了 AICD 的预后模型和分类系统。随后，一系列生物信息学分析评估了该模型在 BC 中的预后和临床意义。
分析发现了一组与 AICD 相关的 18 个基因，具有预后相关性。生存分析表明，高危人群的总生存率明显低于低危人群。此外，与 AICD 相关的预后指标在预测 BC 患者的生存结果方面具有较高的准确性。免疫评估表明，低危人群中抗肿瘤浸润免疫细胞和免疫检查点分子的表达水平较高，与各种抗肿瘤免疫功能相关。最终，通过单因素分析、最小绝对收缩和选择算子（LASSO）和多因素 Cox 回归分析建立了一个与 AICD 相关的综合预后模型。随着 ATP 浓度的增加，BC 细胞的活力在每个时间点都普遍下降。值得注意的是，ATP 降低了 BC 细胞的线粒体膜电位，而增强了正常乳腺上皮细胞的线粒体膜电位。此外，ATP 抑制了 BC 细胞的迁移并促进了它们的凋亡。ATP 还刺激 MCF-10A 细胞中活性氧（ROS）的产生，这对 BC 细胞中的免疫反应有影响。与对照组相比，ATP 干预组中 、 、和 的表达水平明显降低，而 的表达水平升高。 、 、和 与 BC 具有遗传变异，而 与该疾病没有遗传因果变异。
建立了一个与 AICD 相关的有价值的预后模型，能够准确预测 BC 的预后。ATP 诱导的细胞死亡似乎在 BC 进展中起保护作用。这些发现对实施针对 BC 患者的个性化和定制化治疗策略具有重要意义。
