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MAZ介导的激素受体阳性乳腺癌的肿瘤进展和免疫逃逸:靶向肿瘤微环境和PCLAF +亚型特异性治疗

MAZ-mediated tumor progression and immune evasion in hormone receptor-positive breast cancer: Targeting tumor microenvironment and PCLAF+ subtype-specific therapy.

作者信息

Ni Gaofeng, Sun Yuwei, Jia Hongling, Xiahou Zhikai, Li Yumeng, Zhao Fu, Zang Hongyan

机构信息

Department of Breast Surgery, Yantaishan Hospital Affiliated to Binzhou Medical University, Yantai 264003, China.

The First Clinical Medical College of Shandong University of Traditional Chinese Medicine, Jinan 250014, China.

出版信息

Transl Oncol. 2025 Feb;52:102280. doi: 10.1016/j.tranon.2025.102280. Epub 2025 Jan 12.

Abstract

BACKGROUND

Breast cancer had been the most frequently diagnosed cancer among women, making up nearly one-third of all female cancers. Hormone receptor-positive breast cancer (HR+BC) was the most prevalent subtype of breast cancer and exhibited significant heterogeneity. Despite advancements in endocrine therapies, patients with advanced HR+BC often faced poor outcomes due to the development of resistance to treatment. Understanding the molecular mechanisms behind this resistance, including tumor heterogeneity and changes in the tumor microenvironment, was crucial for overcoming resistance, identifying new therapeutic targets, and developing more effective personalized treatments.

METHODS

The study utilized single-cell RNA sequencing (scRNA-seq) data sourced from the Gene Expression Omnibus database and The Cancer Genome Atlas to analyze HR+BC and identify key cellular characteristics. Cell type identification was achieved through Seurat's analytical tools, and subtype differentiation trajectories were inferred using Slingshot. Cellular communication dynamics between tumor cell subtypes and other cells were analyzed with the CellChat. The pySCENIC package was utilized to analyze transcription factors regulatory networks in the identified tumor cell subtypes. The results were verified by in vitro experiments. A risk scoring model was developed to assess patient outcomes.

RESULTS

This study employed scRNA-seq to conduct a comprehensive analysis of HR+BC tumor subtypes, identifying the C3 PCLAF+ tumor cells subtype, which demonstrated high proliferation and differentiation potential. C3 PCLAF+ tumor cells subtype was found to be closely associated with cancer-associated fibroblasts through the MK signaling pathway, facilitating tumor progression. Additionally, we discovered that MAZ was significantly expressed in C3 PCLAF+ tumor cells subtype, and in vitro experiments confirmed that MAZ knockdown inhibited tumor growth, accentuating its underlying ability as a therapeutic target. Furthermore, we developed a novel prognostic model based on the expression profile of key prognostic genes within the PCLAF+/MAZ regulatory network. This model linked high PCLAF+ tumor risk scores with poor survival outcomes and specific immune microenvironment characteristics.

CONCLUSION

This study utilized scRNA-seq to reveal the role of the C3 PCLAF+ tumor cells subtype in HR+BC, emphasizing its association with poor prognosis and resistance to endocrine therapies. MAZ, identified as a key regulator, contributed to tumor progression, while the tumor microenvironment had a pivotal identity in immune evasion. The findings underscored the importance of overcoming drug resistance, recognizing novel treatment targets, and crafting tailored diagnosis regimens.

摘要

背景

乳腺癌一直是女性中最常被诊断出的癌症,占所有女性癌症的近三分之一。激素受体阳性乳腺癌(HR+BC)是乳腺癌中最常见的亚型,具有显著的异质性。尽管内分泌治疗取得了进展,但晚期HR+BC患者由于对治疗产生耐药性,往往面临不良预后。了解这种耐药性背后的分子机制,包括肿瘤异质性和肿瘤微环境的变化,对于克服耐药性、确定新的治疗靶点以及开发更有效的个性化治疗至关重要。

方法

该研究利用来自基因表达综合数据库和癌症基因组图谱的单细胞RNA测序(scRNA-seq)数据来分析HR+BC并确定关键的细胞特征。通过Seurat的分析工具实现细胞类型鉴定,并使用Slingshot推断亚型分化轨迹。使用CellChat分析肿瘤细胞亚型与其他细胞之间的细胞通讯动态。利用pySCENIC软件包分析已鉴定肿瘤细胞亚型中的转录因子调控网络。结果通过体外实验进行验证。开发了一种风险评分模型来评估患者的预后。

结果

本研究采用scRNA-seq对HR+BC肿瘤亚型进行了全面分析,确定了C3 PCLAF+肿瘤细胞亚型,该亚型显示出高增殖和分化潜力。通过MK信号通路发现C3 PCLAF+肿瘤细胞亚型与癌症相关成纤维细胞密切相关,促进肿瘤进展。此外,我们发现MAZ在C3 PCLAF+肿瘤细胞亚型中显著表达,体外实验证实MAZ基因敲低抑制肿瘤生长,突出了其作为治疗靶点的潜在能力。此外,我们基于PCLAF+/MAZ调控网络内关键预后基因的表达谱开发了一种新的预后模型。该模型将高PCLAF+肿瘤风险评分与不良生存结果和特定的免疫微环境特征联系起来。

结论

本研究利用scRNA-seq揭示了C3 PCLAF+肿瘤细胞亚型在HR+BC中的作用,强调了其与不良预后和内分泌治疗耐药性的关联。MAZ被确定为关键调节因子,促进肿瘤进展,而肿瘤微环境在免疫逃逸中具有关键作用。这些发现强调了克服耐药性、识别新的治疗靶点以及制定个性化诊断方案的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/258d/11780959/2cc3847fe7f0/ga1.jpg

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