急性髓系白血病干细胞表面标记物:从经典表型到多维组学

    Surface Markers of Leukemia Stem Cells in Acute Myeloid Leukemia: From Classic Phenotypes to Multidimensional Omic Profiling

    • 摘要: 急性髓系白血病(acute myeloid leukemia,AML)是一类具有高度异质性的血液系统恶性疾病,白血病干细胞(leukemia stem cells,LSCs)是导致疾病复发和治疗抵抗的核心驱动因素。精准鉴定LSCs是制定有效治疗策略的前提。受限于AML的克隆异质性以及与正常造血干细胞的表型重叠,传统的CD34+CD38表型及CD33、CD123等为主的单一识别体系虽奠定了研究基础,但难以完整覆盖功能性LSCs群体。随着高通量多组学技术的应用,LSCs识别策略已转变为对多维共表达网络及动态细胞状态的系统解析。因此,本综述从传统流式标记物出发,探讨单细胞转录组学、质谱流式及多组学联合分析在新型LSCs标记物发现中的应用,并围绕LSCs与造血干细胞的表达差异、标记物调控机制、联合检测网络及临床转化价值进行系统总结,旨在为AML精准诊疗的临床转化提供参考。

       

      Abstract: Acute myeloid leukemia(AML) is a highly heterogeneous hematological malignancy, in which leukemia stem cells(LSCs) serve as the core drivers of disease relapse and therapeutic resistance. The precise identification of LSCs is a prerequisite for developing effective therapeutic strategies. Although conventional single-marker identification systems—primarily centered on the CD34+CD38 phenotype and antigens such as CD33 and CD123—established the methodological foundation, they fail to comprehensively encompass the functional LSCs compartment. This limitation arises from the profound clonal heterogeneity of AML and significant phenotypic overlap with normal hematopoietic stem cells(HSCs). Driven by the application of high-throughput multi-omics technologies, LSCs identification strategies have transitioned toward the systemic elucidation of multidimensional co-expression networks and dynamic cellular states. Therefore, advancing from conventional flow cytometric markers, the applications of single-cell transcriptomics, mass cytometry, and integrated multi-omics analyses in the discovery of novel LSCs markers are explored. Furthermore, the differential expression profiles between LSCs and HSCs, regulatory mechanisms of these markers, combinatorial detection networks, and their clinical translational value are systematically summarized, aiming to provide a reference for the clinical translation of precision diagnostics and therapeutics in AML.

       

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