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乳腺癌中ASCL1的综合分析以及抑制ASCL1通过CREB1/GPX4轴激活铁死亡增加紫杉醇敏感性。

An integrative analysis of ASCL1 in breast cancer and inhibition of ASCL1 increases paclitaxel sensitivity by activating ferroptosis via the CREB1/GPX4 axis.

作者信息

Yang Xiaolu, Li Yilun, Peng Yaqi, Chang Yuan, He Binglu, Zhang Tianqi, Zhang Shiyu, Geng Cuizhi, Liu Yunjiang, Li Xiaolong, Hao Jun, Ma Li

机构信息

Department of Breast Disease Center, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China.

Department of Pathology, Hebei Medical University, Shijiazhuang, China.

出版信息

Front Immunol. 2025 Feb 3;16:1546794. doi: 10.3389/fimmu.2025.1546794. eCollection 2025.

DOI:10.3389/fimmu.2025.1546794
PMID:39963143
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11830715/
Abstract

OBJECTIVE

Our previous study found that Achaete-scute complex homolog 1 (ASCL1) is involved in classifying BC subtypes with different prognostic and pathological characteristics. However, the biological role of ASCL1 in BC still remains largely unexplored. This study aims to elucidate the function of ASCL1 in BC using bioinformatics analyses, as well as and experimental approaches.

METHODS

Data from the TCGA, GEO, and Human Protein Atlas databases were utilized to evaluate ASCL1 expression in BC and its association with patient prognosis. Genetic alterations in ASCL1 were assessed through the COSMIC and cBioPortal databases, while the TIMER2.0 database provided insights into the relationship between ASCL1 expression and key gene mutations in BC. The GDSC database was used to examine correlations between ASCL1 levels and sensitivity to standard chemotherapeutic agents. Associations between ASCL1 expression and cytokines, immunomodulatory factors, MHC molecules, and receptors were analyzed using Pearson and Spearman correlation methods. The TIP database was employed to investigate the connection between ASCL1 expression and immunoreactivity scores, and six computational approaches were applied to evaluate immune cell infiltration. Functional assays were conducted on BC cell lines MCF-7 and MDA-MB-231, and nude mouse models were used for studies.

RESULTS

ASCL1 was found to be upregulated in BC and correlated with unfavorable prognosis and mutations in key oncogenes. Its expression was linked to immunomodulatory factors, immune cell infiltration, and immunoreactivity scores in the tumor microenvironment. Additionally, ASCL1 influenced tumor immune dynamics and chemosensitivity in BC. Overexpression of ASCL1 enhanced BC cell proliferation, migration and invasion, while its knockdown had the opposite effect. Notably, inhibition of ASCL1 increased BC cell sensitivity to paclitaxel both and . In addition, inhibition of ASCL1 activated ferroptosis in BC, including altered mitochondrial morphology, increased MDA and ROS levels, decreased GSH levels and reduced GSH/GSSG ratio. Mechanistically, inhibition of ASCL1 decreases the phosphorylation of CREB1, thus reducing the expression of GPX4. In summary, inhibition of ASCL1 increases paclitaxel sensitivity by activating ferroptosis via the CREB1/GPX4 axis.

CONCLUSIONS

ASCL1 exerts oncogenic effects in BC and represents a potential therapeutic target for intervention.

摘要

目的

我们之前的研究发现,achaete - scute复合体同源物1(ASCL1)参与对具有不同预后和病理特征的乳腺癌亚型进行分类。然而,ASCL1在乳腺癌中的生物学作用在很大程度上仍未被探索。本研究旨在通过生物信息学分析以及实验方法来阐明ASCL1在乳腺癌中的功能。

方法

利用来自TCGA、GEO和人类蛋白质图谱数据库的数据来评估ASCL1在乳腺癌中的表达及其与患者预后的关联。通过COSMIC和cBioPortal数据库评估ASCL1的基因改变,而TIMER2.0数据库则提供了关于ASCL1表达与乳腺癌关键基因突变之间关系的见解。GDSC数据库用于检查ASCL1水平与对标准化疗药物敏感性之间的相关性。使用Pearson和Spearman相关方法分析ASCL1表达与细胞因子、免疫调节因子、MHC分子和受体之间的关联。TIP数据库用于研究ASCL1表达与免疫反应性评分之间的联系,并应用六种计算方法评估免疫细胞浸润。对乳腺癌细胞系MCF - 7和MDA - MB - 231进行功能测定,并使用裸鼠模型进行研究。

结果

发现ASCL1在乳腺癌中上调,且与不良预后和关键癌基因突变相关。其表达与免疫调节因子、免疫细胞浸润以及肿瘤微环境中的免疫反应性评分有关。此外,ASCL1影响乳腺癌的肿瘤免疫动态和化疗敏感性。ASCL1的过表达增强了乳腺癌细胞的增殖、迁移和侵袭,而其敲低则产生相反的效果。值得注意的是,抑制ASCL1在体内和体外均增加了乳腺癌细胞对紫杉醇的敏感性。此外,抑制ASCL1激活了乳腺癌中的铁死亡,包括线粒体形态改变、MDA和ROS水平升高、GSH水平降低以及GSH/GSSG比值降低。机制上,抑制ASCL1降低了CREB1的磷酸化,从而降低了GPX4的表达。总之,抑制ASCL1通过CREB1/GPX4轴激活铁死亡来增加紫杉醇敏感性。

结论

ASCL1在乳腺癌中发挥致癌作用,是一个潜在的干预治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/06622b0e9d45/fimmu-16-1546794-g009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/e473dcfaad99/fimmu-16-1546794-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/818e789828b4/fimmu-16-1546794-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/4772f47e34b8/fimmu-16-1546794-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/703dba1b5a3f/fimmu-16-1546794-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/06622b0e9d45/fimmu-16-1546794-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/beddd45c528c/fimmu-16-1546794-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/d825da525593/fimmu-16-1546794-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/12cdbf8225fd/fimmu-16-1546794-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/0eba61089c0f/fimmu-16-1546794-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/e473dcfaad99/fimmu-16-1546794-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/818e789828b4/fimmu-16-1546794-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/4772f47e34b8/fimmu-16-1546794-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/703dba1b5a3f/fimmu-16-1546794-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4218/11830715/06622b0e9d45/fimmu-16-1546794-g009.jpg

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