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通过液质联用技术定义胶质母细胞瘤干细胞的表型和功能异质性。

Defining phenotypic and functional heterogeneity of glioblastoma stem cells by mass cytometry.

机构信息

Department of Medicine.

Center for Human Immunology and Immunotherapy Programs, and.

出版信息

JCI Insight. 2021 Feb 22;6(4):128456. doi: 10.1172/jci.insight.128456.

DOI:10.1172/jci.insight.128456
PMID:33400685
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7934942/
Abstract

Most patients with glioblastoma (GBM) die within 2 years. A major therapeutic goal is to target GBM stem cells (GSCs), a subpopulation of cells that contribute to treatment resistance and recurrence. Since their discovery in 2003, GSCs have been isolated using single-surface markers, such as CD15, CD44, CD133, and α6 integrin. It remains unknown how these single-surface marker-defined GSC populations compare with each other in terms of signaling and function and whether expression of different combinations of these markers is associated with different functional capacity. Using mass cytometry and fresh operating room specimens, we found 15 distinct GSC subpopulations in patients, and they differed in their MEK/ERK, WNT, and AKT pathway activation status. Once in culture, some subpopulations were lost and previously undetectable ones materialized. GSCs that highly expressed all 4 surface markers had the greatest self-renewal capacity, WNT inhibitor sensitivity, and in vivo tumorigenicity. This work highlights the potential signaling and phenotypic diversity of GSCs. Larger patient sample sizes and antibody panels are required to confirm these findings.

摘要

大多数胶质母细胞瘤(GBM)患者在 2 年内死亡。主要的治疗目标是针对 GBM 干细胞(GSCs),这是一种有助于治疗抵抗和复发的细胞亚群。自 2003 年发现以来,GSCs 一直使用单一表面标志物(如 CD15、CD44、CD133 和 α6 整合素)进行分离。目前尚不清楚这些单一表面标志物定义的 GSC 群体在信号和功能方面彼此之间的差异,以及这些标志物的不同组合的表达是否与不同的功能能力相关。使用质谱流式细胞术和新鲜手术室标本,我们在患者中发现了 15 种不同的 GSC 亚群,它们在 MEK/ERK、WNT 和 AKT 通路激活状态方面存在差异。一旦进入培养,一些亚群就会丢失,以前无法检测到的亚群就会显现出来。高表达所有 4 种表面标志物的 GSCs 具有最强的自我更新能力、WNT 抑制剂敏感性和体内致瘤性。这项工作强调了 GSCs 的潜在信号和表型多样性。需要更大的患者样本量和抗体面板来验证这些发现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/43e99bbe38a6/jciinsight-6-128456-g178.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/1d284c09ab74/jciinsight-6-128456-g170.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/e80d9b58048b/jciinsight-6-128456-g171.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/e4120ac00cda/jciinsight-6-128456-g172.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/b6e3a37306eb/jciinsight-6-128456-g173.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/91ec02d90f85/jciinsight-6-128456-g174.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/e90ec360feb3/jciinsight-6-128456-g175.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/d6cce0c9f263/jciinsight-6-128456-g176.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/31096ade3821/jciinsight-6-128456-g177.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/43e99bbe38a6/jciinsight-6-128456-g178.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/1d284c09ab74/jciinsight-6-128456-g170.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/e80d9b58048b/jciinsight-6-128456-g171.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/e4120ac00cda/jciinsight-6-128456-g172.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/b6e3a37306eb/jciinsight-6-128456-g173.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/91ec02d90f85/jciinsight-6-128456-g174.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/e90ec360feb3/jciinsight-6-128456-g175.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/d6cce0c9f263/jciinsight-6-128456-g176.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/31096ade3821/jciinsight-6-128456-g177.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b8/7934942/43e99bbe38a6/jciinsight-6-128456-g178.jpg

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