A new gene-expression atlas developed using single-cell RNA sequencing data sheds light on how normal hematopoietic cells differentiate and was used to catalog the multiple ways aberrant differentiation can lead to acute myeloid leukemia (AML). Andy G.X. Zeng, PhD, an MD/PhD candidate at the University of Toronto, presented these study findings on behalf of his colleagues at the 2025 American Association for Cancer Research (AACR) Annual Meeting (Abstract 3806). An accompanying commentary was simultaneously published in the AACR journal Blood Cancer Discovery.
The comprehensive data set may shed light on how AML driver genes affect cell differentiation in different contexts, which may inform new biomarkers and drug targets. It also provides a toolkit with which AML researchers can interrogate their own data to address new hypotheses.
“This represents an important step in evaluating cell state heterogeneity within and across AML patients in a more quantitative way, adding a new tool to the toolkit for AML researchers,” stated Dr. Zeng.
Background
AML is characterized by extensive heterogeneity, which can hinder the effective prediction of prognosis and response to therapy, Dr. Zeng explained. He emphasized that not all this heterogeneity is driven by genetic mutations, and different types of leukemia cells can exist within an individual patient’s disease. He believes a more thorough understanding of gene-expression changes during the development and progression of AML may help researchers to better define and target different types of AML cells.
To understand how hematopoiesis “goes wrong” to cause AML, researchers must first characterize normal hematopoiesis. However, building a precise and comprehensive reference map of normal hematopoiesis has been a significant technical challenge for the field, according to Dr. Zeng. “The purpose of this study was to establish an authoritative reference of hematopoiesis and to use that reference to comprehensively catalog all the different types of leukemia cells present in AML,” he noted.
Study Details
Dr. Zeng and colleagues—including the study’s senior author John E. Dick, PhD, FAACR, a senior scientist at the Princess Margaret Cancer Centre and a member of the AACR Hematologic Malignancies Working Group Steering Committee—assembled a reference atlas of normal human hematopoiesis using gene-expression data from 263,519 individual cells enriched for hematopoietic stem and progenitor cells (HSPCs). Upon establishing this atlas, the researchers mapped the transcriptional profiles of more than 1.2 million cells from 318 patients with leukemia to distinct cell states. The cohort chiefly consisted of patients with AML but also included patients with mixed-phenotype acute leukemia (MPAL) and acute erythroid leukemia (AEL), two rare leukemia types that have some overlapping characteristics with AML.
The researchers identified at least 12 distinct differentiation patterns across the AML samples. Some of these patterns closely resembled MPAL or AEL, highlighting how patients with distinct disease diagnoses can nonetheless share similar differentiation anomalies. These similarities emphasize the ambiguity in the diagnostic boundaries between the disease classes, Dr. Zeng said.
The investigators further sought to characterize the genetic underpinnings of these differentiation patterns. Using bulk RNA-sequencing data from more than 1,200 AML patient samples, they estimated the abundance of each leukemia cell state in each patient sample and correlated these cell states with common genetic alterations. They found the same mutation could shift cells in different directions depending on the cell of origin and/or on other co-occurring mutations. In this way, a single leukemia-initiating genetic alteration may generate leukemias with different biological properties.
“These findings reveal that the phenotypic heterogeneity in AML arises from the interplay between genetic drivers and the specific cellular context, helping us begin to decipher the ‘rules’ governing the factors that shape the disease,” Dr. Zeng said.
Clinical Implications
Ultimately, the data offer a toolkit with which researchers can interrogate their own AML samples to find detailed associations between cell states and genetic or clinical variables with potential therapeutic applications. The investigators hope that using these tools will uncover clinical biomarkers of these cell states that could better predict prognosis and facilitate precision medicine for patients with AML.
“By establishing a high-resolution, single-cell reference atlas of hematopoiesis, we’ve not only advanced our understanding of how differentiation goes awry in AML, but we’ve also provided an accessible toolkit for other researchers to rapidly map and classify their own blood samples profiled by single-cell RNA sequencing,” Dr. Zeng stated. “We also hope this motivates others outside of the AML space to adopt similar analytical frameworks that precisely compare cancers with their normal tissue counterparts, as these approaches may allow them to integrate genetic and cellular models of cancer heterogeneity to advance precision medicine across oncology.”
Disclosure: Funding for this study was provided by the University of Toronto, the Princess Margaret Cancer Foundation, the Ontario Institute for Cancer Research, the Canadian Institutes of Health Research, the International Development Research Centre of Ottawa, the Canadian Cancer Society, the Terry Fox New Frontiers Program, the University of Toronto Medicine by Design Initiative with funding from the Canada First Research Excellence Fund, the Ontario Ministry of Health, the Canada Research Chairs Program, the American Lebanese Syrian Associated Charities of St. Jude Children’s Research Hospital, the Alex’s Lemonade Stand Foundation for Childhood Cancer, the National Cancer Institute of the National Institutes of Health, St. Baldrick’s Foundation, and the Henry Schueler 41 & 9 Foundation. Dr. Zeng reported no conflicts of interest. For full disclosures of the other study authors, visit abstractsonline.com.
