CAR-T(CAR-T)细胞疗法在非肿瘤性疾病中的应用
Chimeric antigen receptor T (CAR-T) cell therapy in non-oncological diseases.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Spectral Flow Cytometry Methods and Pipelines for Comprehensive Immunoprofiling of Human Peripheral Blood and Bone Marrow.
Spectral Flow Cytometry Methods and Pipelines for Comprehensive Immunoprofiling of Human Peripheral Blood and Bone Marrow.
分数与星级只用于站内排序 —— 不代表疗效、安全性或个人适用性。
对造血细胞和免疫细胞进行谱型分析可为疾病风险、疾病状态和治疗反应提供重要信息。光谱流式细胞术能够以高通量方式对大队列进行高维度单细胞评估。本研究设计、优化并实施了基于光谱流式细胞术的人外周血和骨髓深度免疫表型分析新方法。两个血液抗体组合可捕获48种细胞表面标志物,在不到2 mL血液中评估超过58种细胞表型,包括T细胞、B细胞、单核细胞、自然杀伤(NK)细胞和树突状细胞的亚群,及其 respective 的耗竭、活化和分化标志物。一个骨髓抗体组合在单管中捕获32种标志物,用于35种细胞表型,包括干/祖细胞群、T细胞亚群、树突状细胞、NK细胞和髓系细胞。我们改编并开发了最初为单细胞基因组学设计的创新流式细胞分析算法,以改进数据整合和可视化。我们还强调了用户需注意的技术要点,以确保数据保真度。我们的方案和分析流程能够准确识别稀有细胞类型,辨别不同供者之间细胞丰度和表型的差异,并在已知血液系统恶性肿瘤患者中显示出一致的免疫景观趋势。 意义:本研究引入了优化的方法和分析算法,增强了利用光谱流式细胞术对人血液和骨髓进行全面免疫表型分析的能力。该方法有助于检测稀有细胞类型,能够测量不同供者之间的细胞变异,并为识别已知血液系统恶性肿瘤提供了概念验证。通过在单细胞水平揭示造血和免疫景观的复杂性,这一进展为理解疾病状态和治疗反应提供了潜力。
UNLABELLED: Profiling hematopoietic and immune cells provides important information about disease risk, disease status, and therapeutic responses. Spectral flow cytometry enables high-dimensional single-cell evaluation of large cohorts in a high-throughput manner.
Here, we designed, optimized, and implemented new methods for deep immunophenotyping of human peripheral blood and bone marrow by spectral flow cytometry. Two blood antibody panels capture 48 cell-surface markers to assess more than 58 cell phenotypes, including subsets of T cells, B cells, monocytes, natural killer (NK) cells, and dendritic cells, and their respective markers of exhaustion, activation, and differentiation in less than 2 mL of blood.
A bone marrow antibody panel captures 32 markers for 35 cell phenotypes, including stem/progenitor populations, T-cell subsets, dendritic cells, NK cells, and myeloid cells in a single tube.
We adapted and developed innovative flow cytometric analysis algorithms, originally developed for single-cell genomics, to improve data integration and visualization.
We also highlight technical considerations for users to ensure data fidelity.
Our protocol and analysis pipeline accurately identifies rare cell types, discerns differences in cell abundance and phenotype across donors, and shows concordant immune landscape trends in patients with known hematologic malignancy. SIGNIFICANCE: This study introduces optimized methods and analysis algorithms that enhance capabilities in comprehensive immunophenotyping of human blood and bone marrow using spectral flow cytometry.
This approach facilitates detection of rare cell types, enables measurement of cell variations across donors, and provides proof-of-concept in identifying known hematologic malignancies. By unlocking complexities of hematopoietic and immune landscapes at the single-cell level, this advancement holds potential for understanding disease states and therapeutic responses.
在 PubMed 查看 → 出版商原文(DOI) 全文 PDF(PMC)· 可下载 治疗专题与资料阅读指南 资料来源与翻译说明 报告译文或资料问题 →
MEMBER ACCOUNT
登录成功会直接打开下一页。