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单细胞转录组学为乳腺癌的转移相关亚群提供了深入了解。

Single-cell transcriptomics provide insight into metastasis-related subsets of breast cancer.

机构信息

Department of Laboratory Medicine, The Affiliated Hospital of Southwest Medical University, Sichuan Province Engineering Technology Research Center of Molecular Diagnosis of Clinical Diseases, Molecular Diagnosis of Clinical Diseases Key Laboratory of Luzhou, Sichuan, China.

出版信息

Breast Cancer Res. 2023 Oct 19;25(1):126. doi: 10.1186/s13058-023-01728-y.

DOI:10.1186/s13058-023-01728-y
PMID:37858183
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10588105/
Abstract

Breast cancer metastasis is a complex, multi-step process, with high cellular heterogeneity between primary and metastatic breast cancer, and more complex interactions between metastatic cancer cells and other cells in the tumor microenvironment. High-resolution single-cell transcriptome sequencing technology can visualize the heterogeneity of malignant and non-malignant cells in the tumor microenvironment in real time, especially combined with spatial transcriptome analysis, which can directly compare changes between different stages of metastatic samples. Therefore, this study takes single-cell analysis as the first perspective to deeply explore special or rare cell subpopulations related to breast cancer metastasis, systematically summarizes their functions, molecular features, and corresponding treatment strategies, which will contribute to accurately identify, understand, and target tumor metastasis-related driving events, provide a research basis for the mechanistic study of breast cancer metastasis, and provide new clues for its personalized precision treatment.

摘要

乳腺癌转移是一个复杂的、多步骤的过程,原发和转移性乳腺癌之间具有高度的细胞异质性,转移性癌细胞与肿瘤微环境中的其他细胞之间的相互作用也更加复杂。高分辨率单细胞转录组测序技术可以实时可视化肿瘤微环境中恶性和非恶性细胞的异质性,特别是与空间转录组分析相结合,可以直接比较转移样本不同阶段之间的变化。因此,本研究以单细胞分析为第一视角,深入探索与乳腺癌转移相关的特殊或罕见细胞亚群,系统总结其功能、分子特征和相应的治疗策略,这将有助于准确识别、理解和靶向肿瘤转移相关的驱动事件,为乳腺癌转移的机制研究提供依据,并为其个体化精准治疗提供新线索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8871/10588105/030a7e02b7a0/13058_2023_1728_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8871/10588105/030a7e02b7a0/13058_2023_1728_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8871/10588105/030a7e02b7a0/13058_2023_1728_Fig1_HTML.jpg

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本文引用的文献

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Combined Single-Cell and Spatial Transcriptomics Reveal the Metabolic Evolvement of Breast Cancer during Early Dissemination.单细胞联合空间转录组解析早期转移乳腺癌代谢演变
Adv Sci (Weinh). 2023 Feb;10(6):e2205395. doi: 10.1002/advs.202205395. Epub 2023 Jan 3.
2
HMGA1 As a Potential Prognostic and Therapeutic Biomarker in Breast Cancer.HMGA1 作为乳腺癌潜在的预后和治疗生物标志物。
Dis Markers. 2022 Nov 26;2022:7466555. doi: 10.1155/2022/7466555. eCollection 2022.
3
Microenvironment components and spatially resolved single-cell transcriptome atlas of breast cancer metastatic axillary lymph nodes.
乳腺癌转移性腋窝淋巴结的微环境成分和空间分辨单细胞转录组图谱。
Acta Biochim Biophys Sin (Shanghai). 2022 Sep 25;54(9):1336-1348. doi: 10.3724/abbs.2022131.
4
Aberrant paracrine signalling for bone remodelling underlies the mutant histone-driven giant cell tumour of bone.异常的旁分泌信号导致破骨细胞重塑,这是突变组蛋白驱动的骨巨细胞瘤的基础。
Cell Death Differ. 2022 Dec;29(12):2459-2471. doi: 10.1038/s41418-022-01031-x. Epub 2022 Aug 3.
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Breast carcinomas with osteoclast-like giant cells: a comprehensive clinico-pathological and molecular portrait and evidence of RANK-L expression.乳腺癌伴破骨细胞样巨细胞:全面的临床病理和分子特征及 RANK-L 表达的证据。
Mod Pathol. 2022 Nov;35(11):1624-1635. doi: 10.1038/s41379-022-01112-9. Epub 2022 Jun 13.
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Identification of two cancer stem cell-like populations in triple-negative breast cancer xenografts.鉴定三阴性乳腺癌异种移植中的两个癌症干细胞样群体。
Dis Model Mech. 2022 Jun 1;15(6). doi: 10.1242/dmm.049538. Epub 2022 Jun 23.
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