文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

对代谢途径进行系统筛查,以识别具有不同免疫特征的两种乳腺癌亚型。

Systematic screening of metabolic pathways to identify two breast cancer subtypes with divergent immune characteristics.

作者信息

Cheng Xiangshu, Zhang Shuhao, Meng Xin, Chen Rui, Tang Hao, Wang Jiacheng, Jiang Yongshuai, Zhang Ruijie

机构信息

College of Bioinformatics Science and Technology, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, Heilongiiang Province, China.

出版信息

Sci Rep. 2025 Jul 1;15(1):20996. doi: 10.1038/s41598-025-05179-7.


DOI:10.1038/s41598-025-05179-7
PMID:40594370
Abstract

Due to the high heterogeneity among breast cancer (BRCA) patients, most individuals show a limited response rate to one specific treatment. The metabolic plasticity of BRCA cells is one of the main causes of their heterogeneity, affecting not only their own growth and function but also their metabolites have an impact on the tumor immune microenvironment (TIME). However systematic evaluation of metabolic pathways in BRCA is lacking. We identified BRCA metabolic subtypes (BCMS) by consensus clustering 26 KEGG/Reactome pathways in the TCGA BRCA discovery cohort (n = 1094). Nine independent bulk transcriptome cohorts (total n > 4000), including METABRIC and GEO datasets, were used for validation via random forest classification. To characterize BCMS, we applied an analytical framework encompassing functional enrichment (GSEA), immune infiltration (Mcpcounter), clinical correlation, drug sensitivity (oncoPredict) on bulk transcriptome data, cell-cell communication analysis (CellChat) on single-cell RNA sequencing (scRNA-seq) data, and spatial co-localization analysis (CellTrek) on spatial RNA sequencing (spRNA-seq) data. We identified two distinct BCMS. BCMS-I exhibited upregulated lipid metabolism-related pathways, characterized by immune activation, a better prognosis, and higher infiltration of immune cells, including B cells, T cells, NK cells, macrophages, and neutrophils. Spatial co-localization analysis further revealed that BCMS-I demonstrated spatial co-localization with immune cells. In contrast, BCMS-II showed upregulation of amino acid and vitamin metabolism-related pathways, with tumor cell proliferation, a poorer prognosis, and a lack of immune cell infiltration. The immune activation in BCMS-I is marked by the significant activation of the MHC-I signaling pathway in interactions between tumor cells and T/NK cells, and of the MHC-II signaling pathway in interactions between tumor cells and dendritic cells/macrophages. In contrast, the proliferative characteristics of BCMS-II are associated with the co-activation of the GRN signaling pathway by myeloid immune cells and stromal cells within the tumor microenvironment. Drug sensitivity analysis revealed that BCMS-II was highly sensitive to Ganitumab, Carboplatin + ABT-888, and Pembrolizumab. This study established a novel Breast Cancer Metabolic Subtyping System (BCMSS) based on metabolic pathway analysis. Our findings highlight the heterogeneity of BRCA in terms of metabolic features, immune characteristics, clinical prognosis, and drug sensitivity. The novel classification system provides valuable insights for clinical diagnosis and treatment, serving as a foundation for precision diagnosis and personalized therapies in BRCA.

摘要

由于乳腺癌(BRCA)患者之间存在高度异质性,大多数个体对一种特定治疗的反应率有限。BRCA细胞的代谢可塑性是其异质性的主要原因之一,不仅影响其自身的生长和功能,而且其代谢产物还会对肿瘤免疫微环境(TIME)产生影响。然而,目前缺乏对BRCA中代谢途径的系统评估。我们通过对TCGA BRCA发现队列(n = 1094)中的26条KEGG/Reactome途径进行共识聚类,确定了BRCA代谢亚型(BCMS)。九个独立的批量转录组队列(总数n > 4000),包括METABRIC和GEO数据集,通过随机森林分类进行验证。为了表征BCMS,我们应用了一个分析框架,包括对批量转录组数据的功能富集(GSEA)、免疫浸润(Mcpcounter)、临床相关性、药物敏感性(oncoPredict),对单细胞RNA测序(scRNA-seq)数据的细胞间通讯分析(CellChat),以及对空间RNA测序(spRNA-seq)数据的空间共定位分析(CellTrek)。我们确定了两种不同的BCMS。BCMS-I表现出脂质代谢相关途径上调,其特征为免疫激活、预后较好以及免疫细胞(包括B细胞、T细胞、NK细胞、巨噬细胞和中性粒细胞)浸润较高。空间共定位分析进一步显示,BCMS-I与免疫细胞表现出空间共定位。相比之下,BCMS-II显示氨基酸和维生素代谢相关途径上调,伴有肿瘤细胞增殖、预后较差且缺乏免疫细胞浸润。BCMS-I中的免疫激活以肿瘤细胞与T/NK细胞相互作用中MHC-I信号通路的显著激活,以及肿瘤细胞与树突状细胞/巨噬细胞相互作用中MHC-II信号通路的显著激活为特征。相比之下,BCMS-II的增殖特征与肿瘤微环境中髓样免疫细胞和基质细胞对GRN信号通路的共同激活有关。药物敏感性分析显示,BCMS-II对甘尼单抗、卡铂 + ABT-888和派姆单抗高度敏感。本研究基于代谢途径分析建立了一种新型的乳腺癌代谢分型系统(BCMSS)。我们的研究结果突出了BRCA在代谢特征、免疫特性、临床预后和药物敏感性方面的异质性。这种新型分类系统为临床诊断和治疗提供了有价值的见解,为BRCA的精准诊断和个性化治疗奠定了基础。

相似文献

[1]
Systematic screening of metabolic pathways to identify two breast cancer subtypes with divergent immune characteristics.

Sci Rep. 2025-7-1

[2]
Integrated proteomics and transcriptomics analysis reveals key regulatory genes between ER-positive/PR-positive and ER-positive/PR-negative breast cancer.

BMC Cancer. 2025-7-1

[3]
Identification and validation of a KRAS-macrophage-associated gene signature as prognostic biomarkers and potential therapeutic targets in melanoma.

Front Immunol. 2025-6-18

[4]
Systemic treatments for metastatic cutaneous melanoma.

Cochrane Database Syst Rev. 2018-2-6

[5]
Cost-effectiveness of using prognostic information to select women with breast cancer for adjuvant systemic therapy.

Health Technol Assess. 2006-9

[6]
Pathway-based cancer transcriptome deciphers a high-resolution intrinsic heterogeneity within bladder cancer classification.

J Transl Med. 2025-6-17

[7]
Molecular feature-based classification of retroperitoneal liposarcoma: a prospective cohort study.

Elife. 2025-5-23

[8]
Unraveling the role of GPCR signaling in metabolic reprogramming and immune microenvironment of lung adenocarcinoma: a multi-omics study with experimental validation.

Front Immunol. 2025-6-6

[9]
Drugs for preventing postoperative nausea and vomiting in adults after general anaesthesia: a network meta-analysis.

Cochrane Database Syst Rev. 2020-10-19

[10]
Falls prevention interventions for community-dwelling older adults: systematic review and meta-analysis of benefits, harms, and patient values and preferences.

Syst Rev. 2024-11-26

本文引用的文献

[1]
Thirteen years of clusterProfiler.

Innovation (Camb). 2024-10-21

[2]
Spatially resolved metabolomics: From metabolite mapping to function visualising.

Clin Transl Med. 2024-11

[3]
KEGG: biological systems database as a model of the real world.

Nucleic Acids Res. 2025-1-6

[4]
Deciphering breast cancer dynamics: insights from single-cell and spatial profiling in the multi-omics era.

Biomark Res. 2024-9-18

[5]
Single-Cell RNA-Sequencing: Opening New Horizons for Breast Cancer Research.

Int J Mol Sci. 2024-8-31

[6]
Author Correction: Cancer cell metabolism and antitumour immunity.

Nat Rev Immunol. 2024-7

[7]
Stratification and prognostic evaluation of breast cancer subtypes defined by obesity-associated genes.

Discov Oncol. 2024-4-27

[8]
Cancer cell metabolism and antitumour immunity.

Nat Rev Immunol. 2024-9

[9]
Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.

CA Cancer J Clin. 2024

[10]
Dietary elaidic acid boosts tumoral antigen presentation and cancer immunity via ACSL5.

Cell Metab. 2024-4-2

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索