Profiling of the TNBC Tumor Microenvironment's Functional Heterogeneity by CITE-seq to Guide Personalized Medicine.

IF 1.7 4区 医学 Q4 BIOCHEMICAL RESEARCH METHODS
Zhang Yiping, Zhang Xin, Tian Jinqiang
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引用次数: 0

Abstract

Introduction / Objective: Triple-negative breast cancer (TNBC) is an aggressive subtype with few effective treatments and frequent resistance to immune checkpoint inhibitors. The heterogeneous and plastic tumor microenvironment (TME) is a dynamic, complex ecosystem. This study aims to deconstruct the TNBC immune ecosystem and generate a cellular atlas of its tumor microenvironment.

Methods: In this study, we apply three CITE-seq datasets from murine TNBC tumors, totaling 2,356 cells. After correcting for technical batch effects, we perform clustering to identify major cell types, followed by focused sub-clustering of tumor-associated macrophages (TAMs) and T cells to analysis their functional states and potential differentiation trajectories.

Results: Batch-corrected analysis resolves six primary cell populations within the TNBC microenvironment. TAMs segregate into three distinct subpopulations: a classical antigen-presenting subset, a metabolically active subset enriched for mitochondrial gene expression, and a unique subset with an erythroid-like gene signature consistent with active erythrophagocytosis. T-cell analysis reveals five major states. Furthermore, we identify several therapeutic targets.

Discussion: These findings reveal substantial functional diversity within key immune compartments of TNBC, particularly TAMs and T cells, including metabolically specialized and erythrophagocytic TAMs, as well as distinct T cells. Besides, we also identify several potential drug targets for targeted treatment.

Conclusion: This work provides a detailed single-cell atlas of the TNBC tumor microenvironment and uncovers functional heterogeneity in its immune cells. The resulting map offers a foundation for precision medicine, facilitating patient stratification and the design of tailored therapies that target the specific cellular ecosystems driving TNBC progression.

利用CITE-seq分析TNBC肿瘤微环境功能异质性,指导个体化治疗。
简介/目的:三阴性乳腺癌(TNBC)是一种侵袭性亚型,有效的治疗方法很少,并且经常对免疫检查点抑制剂产生耐药性。肿瘤微环境是一个动态的、复杂的生态系统。本研究旨在解构TNBC免疫生态系统并生成其肿瘤微环境的细胞图谱。方法:在本研究中,我们使用了来自小鼠TNBC肿瘤的三个CITE-seq数据集,共计2,356个细胞。在校正技术批效应后,我们进行聚类以识别主要细胞类型,然后对肿瘤相关巨噬细胞(tam)和T细胞进行集中亚聚类以分析其功能状态和潜在分化轨迹。结果:批量校正分析解决了TNBC微环境中的六个原代细胞群。tam分为三个不同的亚群:一个典型的抗原呈递亚群,一个富含线粒体基因表达的代谢活跃亚群,以及一个具有与活跃的红细胞吞噬一致的红细胞样基因特征的独特亚群。t细胞分析揭示了五种主要状态。此外,我们确定了几个治疗靶点。讨论:这些发现揭示了TNBC关键免疫区室内的实质性功能多样性,特别是tam和T细胞,包括代谢特化和红细胞tam,以及不同的T细胞。此外,我们还确定了几个潜在的靶向治疗药物靶点。结论:本工作提供了TNBC肿瘤微环境的详细单细胞图谱,揭示了其免疫细胞的功能异质性。由此产生的图谱为精准医学提供了基础,促进了患者分层,并设计了针对驱动TNBC进展的特定细胞生态系统的定制疗法。
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来源期刊
CiteScore
3.10
自引率
5.60%
发文量
327
审稿时长
7.5 months
期刊介绍: Combinatorial Chemistry & High Throughput Screening (CCHTS) publishes full length original research articles and reviews/mini-reviews dealing with various topics related to chemical biology (High Throughput Screening, Combinatorial Chemistry, Chemoinformatics, Laboratory Automation and Compound management) in advancing drug discovery research. Original research articles and reviews in the following areas are of special interest to the readers of this journal: Target identification and validation Assay design, development, miniaturization and comparison High throughput/high content/in silico screening and associated technologies Label-free detection technologies and applications Stem cell technologies Biomarkers ADMET/PK/PD methodologies and screening Probe discovery and development, hit to lead optimization Combinatorial chemistry (e.g. small molecules, peptide, nucleic acid or phage display libraries) Chemical library design and chemical diversity Chemo/bio-informatics, data mining Compound management Pharmacognosy Natural Products Research (Chemistry, Biology and Pharmacology of Natural Products) Natural Product Analytical Studies Bipharmaceutical studies of Natural products Drug repurposing Data management and statistical analysis Laboratory automation, robotics, microfluidics, signal detection technologies Current & Future Institutional Research Profile Technology transfer, legal and licensing issues Patents.
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