加拿大多伦多大学John E. Dick团队近期取得重要工作进展，他们研究开发出一个能理解异质性和预测急性髓系白血病药物反应的细胞层次框架。该项研究成果2022年5月26日在线出版于《自然—医学》杂志。

为了了解疾病异质性如何与治疗反应联系起来，研究人员通过使用白血病干细胞、祖细胞和成熟细胞类型的单细胞参考谱进行反卷积，从1,000多名患者的大量转录组中确定了白血病细胞的层次结构。白血病等级组成与功能、基因组和临床特性相关，并融合为四个总体类别，包括原始、成熟、GMP和中间。

至关重要的是，沿原始与GMP或原始与成熟轴的层次结构的变化分别与对化疗反应或靶向治疗的药物敏感性相关。源自原始与成熟轴的七基因生物标志物与对105种研究药物的反应相关。细胞层次结构构成了理解疾病生物学和推进AML精准医学的新框架。

据介绍，急性髓系白血病(AML)的治疗前景正在发展，有希望的疗法进入临床应用转化，但患者反应仍然是异质的，并且缺乏用于定制治疗的生物标志物。

附：英文原文

Title: A cellular hierarchy framework for understanding heterogeneity and predicting drug response in acute myeloid leukemia

Author: Zeng, Andy G. X., Bansal, Suraj, Jin, Liqing, Mitchell, Amanda, Chen, Weihsu Claire, Abbas, Hussein A., Chan-Seng-Yue, Michelle, Voisin, Veronique, van Galen, Peter, Tierens, Anne, Cheok, Meyling, Preudhomme, Claude, Dombret, Herv, Daver, Naval, Futreal, P. Andrew, Minden, Mark D., Kennedy, James A., Wang, Jean C. Y., Dick, John E.

Issue&Volume: 2022-05-26

Abstract: The treatment landscape of acute myeloid leukemia (AML) is evolving, with promising therapies entering clinical translation, yet patient responses remain heterogeneous, and biomarkers for tailoring treatment are lacking. To understand how disease heterogeneity links with therapy response, we determined the leukemia cell hierarchy makeup from bulk transcriptomes of more than 1,000 patients through deconvolution using single-cell reference profiles of leukemia stem, progenitor and mature cell types. Leukemia hierarchy composition was associated with functional, genomic and clinical properties and converged into four overall classes, spanning Primitive, Mature, GMP and Intermediate. Critically, variation in hierarchy composition along the Primitive versus GMP or Primitive versus Mature axes were associated with response to chemotherapy or drug sensitivity profiles of targeted therapies, respectively. A seven-gene biomarker derived from the Primitive versus Mature axis was associated with response to 105 investigational drugs. Cellular hierarchy composition constitutes a novel framework for understanding disease biology and advancing precision medicine in AML. A novel gene expression classifier of AML heterogeneity captures patient-specific variation in leukemia cell composition and predicts clinical responses to treatment.

DOI: 10.1038/s41591-022-01819-x

Source: https://www.nature.com/articles/s41591-022-01819-x