Mariam M. Youssef
Christopher Y. Park- Pathology, New York University Grossman School of Medicine, New York, NY, United States
The assessment of measurable residual disease (MRD) plays a critical role in acute myeloid leukemia (AML) treatment response evaluation and prognosis. However, current AML MRD detection by flow cytometry (FC) is limited in sensitivity due to immunophenotypic variability, similarities to normal hematopoietic stem/progenitor cells, and the lack of stable leukemia-associated immunophenotypes. A significant proportion of AML patients classified as MRD-negative by FC eventually relapse, likely due to the persistence of therapy-resistant leukemic stem cells (LSCs) that are not sensitively detected by routine clinical flow panels. Flow cytometry panels designed to detect LSC antigens, while promising, face challenges like immunophenotypic heterogeneity across AML subtypes, lack of standardized marker panels across laboratories, and limited validation. Here, we summarize the current state of FC-based LSC detection in AML, discussing commonly used markers, immunophenotypic variability, assay setup challenges, and we review recent clinical studies on LSC assessment, outlining their main findings and implications for prognosis and MRD integration. We also consider advances in spectral flow cytometry for improved LSC detection.
Introduction
Acute myeloid leukemia (AML) is an aggressive cancer of hematopoietic stem and progenitor cells (HSPCs), affecting approximately 20,000 individuals annually in the United States (Dohner et al., 2015). Despite therapeutic advances, prognosis remains poor with a 60%–70% mortality rate (National Cancer Institute, 2024), primarily due to post-remission relapse.
Measurable residual disease (MRD) detection is essential in guiding treatment for several hematologic malignancies (Short et al., 2020). In B-lymphoblastic leukemia (B-ALL), MRD detection by flow cytometry (FC) achieves high sensitivity, often below 0.01% (Theunissen et al., 2017), and holds prognostic significance (Verbeek and van der Velden, 2024). Similarly, in multiple myeloma FC–based MRD detection is highly sensitive to 0.001%, offering strong prognostic value and thus routinely incorporated into response assessments (Medina-Herrera et al., 2023; Flores-Montero et al., 2017). However, in AML, MRD detection remains challenging, primarily due to patient-to-patient immunophenotypic variability and the lack of stable, aberrant leukemia-associated immunophenotypes (van der Linde et al., 2023). The sensitivity of FC for MRD detection in AML is typically limited to around 0.1%, as estimated in clinical studies (Blachly et al., 2022; Hanekamp et al., 2020). A significant proportion of AML patients deemed MRD-negative by FC ultimately relapse (Ivey et al., 2016; Terwijn et al., 2013), indicating that current MRD assays fail to detect low-levels of clinically relevant AML blasts (Thakral et al., 2022), supporting the notion that therapy-resistant clones that include functional leukemic stem cells (LSCs) enriched for self-renewal, dormancy, and drug resistance (Ivey et al., 2016; Terwijn et al., 2013), persist after treatment and drive disease recurrence (Joshi et al., 2019). Detecting LSCs by FC remains a significant challenge due to their low frequency, antigen heterogeneity, and overlap with normal HSPCs (Terwijn et al., 2010; Srinivasan Rajsri et al., 2023). Moreover, the great majority of reported LSC antigens have not been incorporated into routine MRD panels in clinical flow cytometry laboratories.
In this review, we summarize current knowledge on the application of FC to identify LSCs in AML. We discuss the phenotypic characteristics of LSC-enriched fractions, commonly used surface markers, and how these profiles vary across AML molecular subtypes. We also highlight supporting evidence from functional assays such as xenotransplantation, address key technical considerations (e.g., required cell numbers, optimal sample processing), and explore the clinical implications and limitations of FC-based LSC detection in the context of MRD monitoring. Finally, we consider how advances in spectral (full-spectrum) FC are expanding the possibilities for deeper, more precise immunophenotyping of rare and heterogeneous LSC populations.
Immunophenotypic identification of leukemic stem cells
The search for methods to identify LSC antigens has been based on the longstanding paradigm that AML blasts are transformed HSPCs expressing novel antigens or antigenic patterns that reflect the normal sequence of antigen expression in normal HSPCs. Efforts to identify normal human hematopoietic stem cells (HSCs) led to reports in 1991 that CD34+CD38− cells contain primitive progenitors (Terstappen et al., 1991), and in 1992, the addition of CD90 enriched for cells capable of multilineage engraftment in immunodeficient mice (Baum et al., 1992). This foundational work helped establish the commonly accepted phenotype of human HSCs as CD34+CD38−CD90+Lineage−, although subsequent studies further refined this phenotype and showed that HSCs are CD45RA- (Majeti et al., 2007) and can be further enriched by identifying CD49f+ cells in the CD34+CD38−CD90+CD45RA-Lineage- fraction (Notta et al., 2011). In 1994, Lapidot et al. demonstrated that rare AML cells with a CD34+CD38− phenotype could initiate leukemia in immunodeficient mice (Lapidot et al., 1994), establishing this population as enriched for LSC activity. The CD34+CD38− compartment has since served as the primary focus for LSC identification in AML, although subsequent studies demonstrate that other blast fractions harbor LSC activity, albeit at reduced frequencies (Eppert et al., 2011; Ng et al., 2016). This raises important questions: Are LSCs defined by a uniform phenotype? Do distinct LSC populations arise in different AML subtypes? And do LSCs represent cell states without normal counterparts in normal hematopoietic development?
In a pivotal study, Goardon et al. demonstrated that LSCs are not confined to a single immunophenotype but can be found in two hierarchically related compartments (Goardon et al., 2011). In the majority of AML cases, they identified both a CD34+CD38−CD90−CD45RA+ population resembling lymphoid-primed multipotent progenitors (LMPP-like LSCs) and a more differentiated CD34+CD38+CD123+/lowCD110−CD45RA+ population resembling granulocyte-monocyte progenitors (GMP-like LSCs). Crucially, only LMPP-like LSCs were able to generate GMP-like cells in vitro and in vivo, but not the reverse, indicating a developmental hierarchy and suggesting greater stemness potential of the LMPP-like subset (Goardon et al., 2011).
Although CD45RA positivity has been proposed to distinguish LSCs from HSCs (Cloos et al., 2018; Boyer et al., 2018), CD45RA expression alone may not be sufficient to effectively distinguish LSCs from normal progenitors since AML blasts frequently lose CD90 expression (Holden et al., 1995; Inaba et al., 1997; Kozii et al., 1997). A study observed that LMPPs express CD38 at an intermediate level between CD38− stem cells and CD38+ progenitors, recommending a narrower CD38 negative gate to reduce misclassification (Kersten et al., 2016). Therefore, using CD45RA in conjunction with other aberrant LSC markers may enhance the specificity and accuracy of LSC identification.
Altough the CD34+CD38− compartment is frequently enriched for LSC activity in CD34+ AMLs, LSCs have also been described in AMLs lacking CD34 expression, which show <1% CD34 expression and comprise approximately 20% of all AMLs (van der Pol et al., 2003; Zeijlemaker et al., 2015; van Rhenen et al., 2005). Therefore, alternative markers such as CD117 have been used to enrich for stem-like cells (Quek et al., 2016). In NPM1-mutated AML, which is often associated with low CD34 expression, studies have shown that some cases harbor LSCs exclusively within the CD34− fraction, while others contain LSCs in both the CD34+ and CD34− fractions (Taussig et al., 2010; Quek et al., 2016). More recently, venetoclax resistance in monocytic AML has been attributed to a distinct monocytic LSC population (CD34−CD14−CD11b−CD36−), which is immunophenotypically distinct from previously described CD34− LSC subsets and characterized by reduced BCL2 dependence (Pei et al., 2023). Together, these observations underscore the immunophenotypic heterogeneity of AML LSCs and highlight the limitations of relying on single-marker gating. To address this, additional markers such as CD99 (Chung et al., 2017). CD133 (Reuvekamp et al., 2025a) CD32 (Ho et al., 2016), CLL-1 (Larsen et al., 2012), CD244 (Quek et al., 2014) have been explored in CD34− AML, either individually or in combination with CD38 (Ho et al., 2016). The most commonly reported markers that enrich for LSCs in AML are listed in Table 1.
Table 1. Review of surface markers that enrich for leukemic stem cells in acute myeloid leukemia.
Functional validation and limitations of stemness assays
Functional validation serves as the gold standard for confirming that immunophenotypically defined cell populations truly represent LSCs. This process relies heavily on xenotransplantation into immunodeficient mice to initiate disease as well as serial engrafment in order to demonstrate self-renewal capacity. However, these assays have inherent limitations. Successful engraftment depends on multiple factors including homing efficiency, immune evasion, and responsiveness to murine cytokines. Thus, it is possible that some LSCs with true leukemogenic potential may fail to engraft due to species-specific barriers. Indeed, using xenograft models, LSC frequencies have been reported to range from as high as ∼1 in 104 cells to as low as ∼1 in 107 cells, underscoring both their rarity and the marked variability between patients (Sarry et al., 2011; Bonnet and Dick, 1997). This necessitates complementary approaches, such as fluorescence in situ hybridization (FISH), next-generation sequencing (NGS), and targeted mutational profiling, to confirm the presence of leukemia-specific cytogenetic or molecular abnormalities. Moreover, linking these features with clinical outcomes like disease-free and overall survival is crucial to establish their clinical relevance.
Exploration of alternative LSC identification strategies that do not rely solely on surface antigens has been pursued. Some studies highlight metabolic distinctions, with LSCs in the CD34+CD38− fraction usually exhibiting lower aldehyde dehydrogenase (ALDH) activity than residual normal HSCs in AML bone marrows (Schuurhuis et al., 2013). However, AML LSCs with high ALDH activity have also been described (Hoang et al., 2015; Ran et al., 2009; Blume et al., 2018), indicating that ALDH-based discrimination is variable across subtypes and lacks the specificity to serve as a standalone marker. Other strategies attempt to detect LSCs using similar methods to HSC detection, like Hoechst-low side population (SP) cells, which are enriched for stem cell activity based on dye efflux ability (Feuring-Buske and Hogge, 2001; Moshaver et al., 2008). Given that both malignant and normal stem cells exhibit these features (Moshaver et al., 2019), distinguishing between them remains a challenge requiring additional markers to distinguish between them.
Challenges in quantifying LSCs in clinical settings
Accurate identification of LSCs by FC is challenging due to the immunophenotypic heterogeneity of AML. Although employing extended antibody panels can improve detection, the variation in surface marker expression across different cases may require customized panel designs guided by initial diagnostic screening. Current FC-based strategies for LSC detection are limited by antibody panel variability among labs, the substantial phenotypic overlap between leukemic and normal progenitor compartments, subjective gating, and the lack of incorporation of antibodies that can reliably identify LSCs.
But what markers would constitute optimal markers for LSC identification? This involves assessing the specificity of candidate markers by comparing their expression in blasts and putative LSCs versus normal HSCs. Normal HSCs can be identified using negative control bone marrow samples or in the AML specimen, as we and others have shown the presence of residual HSCs in AML diagnostic samples (Jan et al., 2012; Chung et al., 2017). Ideally, a useful marker should show clear differences in marker expression within the CD34+CD38− compartment, either as a distinct population (marker+ vs. marker−) or by overexpression in LSCs relative to normal HSCs. Zeijlemaker and colleagues proposed a scoring system ranking markers by their ability to provide such distinction (Zeijlemaker et al., 2016), emphasizing the importance of minimizing contamination of LSCs in the marker-negative fraction. However, marker-negative fractions cannot always be assumed to be free of LSCs. For example, analysis of GPR56 in combination with CD34 expression revealed engraftment potential in both CD34− and CD34+ fractions, demonstrating that not all LSCs express the classical CD34+CD38− phenotype (Pabst et al., 2016). Similarly, Saito et al. showed that CD32 is highly expressed in LSCs, yet the CD32− fraction in a subset of cases also retains leukemic potential and is enriched for quiescent LSCs (Saito et al., 2010). These findings underscore the need for cautious interpretation as well as validation of markers across diverse AML subtypes.
Markers with continuous rather than bimodal expression also requires carefully defined thresholds for positivity to differentiate true aberrancy from background noise. Common approaches include using mean fluorescence intensity (MFI) ratio or fold change relative to isotype controls (Chung et al., 2017; Haubner et al., 2019), setting cutoffs at least two standard deviations from appropriate negative reference (Loghavi et al., 2021), or applying receiver operating characteristic (ROC) curves to optimize discrimination (Guy et al., 2013).
Homogeneous CD38 expression in some AML cases poses challenges for gating as a clearly defined CD38− compartment may be absent. In such cases, internal controls such as residual erythroid cells or calibration beads for CD38-negative thresholds (Cloos et al., 2018; Quek et al., 2014) and monocytes (Terwijn et al., 2014) or hematogones (Ngai et al., 2025) as CD38-positive references, provide a biologically anchored framework for interpretation.
Another consideration lies in the limitation in cell number when using conventional FC. When large panels are split across multiple tubes, sufficient events may not be acquired to confidently detect rare LSCs. To overcome this, prior studies have attempted to incorporate several LSC markers into a single fluorescence channel within a one-tube assay (Zeijlemaker et al., 2016; Li et al., 2022). However, this approach does not allow the flexibility to interpret complex expression patterns of markers and nonuniform expression of lineage markers. This issue is particularly significant for rare cells, as collective assessment of populations with different expression levels and/or autofluorescence may lead to decreased sensitivity and specificity of LSC detection (Boesch et al., 2018). Furthermore, post-therapy immunophenotypic shifts within the shared channel can affect accurate LSC measurement. However, when markers are assessed separately, it requires significant effort to determine which markers are co-expressed or absent to identify a residual LSC population as subsets may be negative for certain markers yet positive for others.
Different approaches have been used to define LSC burden. Some studies calculate the proportion of LSCs relative to total WBCs (Ngai et al., 2023; Zeijlemaker et al., 2019a; Terwijn et al., 2014), and others calculating LSCs as a percentage of CD34+ cells or primitive compartments (Ngai et al., 2025). Regardless of the method used, LSC frequency cutoffs have been calculated based on clinical endpoints. Several studies have addressed this by correlating LSC frequency with remission and relapse outcomes. For example, a cutoff of 0.03% CD34+CD38− LSCs linked to higher relapse risk, with higher frequencies associated with inferior remission rates and survival (Zeijlemaker et al., 2019b). In the post-therapy setting, thresholds are typically pushed closer to the limit of detection of FC, since residual LSCs are expected to be rare (Zeijlemaker et al., 2019a).
As the disease progresses, shifts in immunophenotype may occur due to clonal evolution, relapse, or treatment effect. Ideally, LSC markers should maintain stable expression after chemotherapy (Saito et al., 2010). Yet some, such as CD123 are also reported to be expressed in regenerating marrow, limiting specificity (van Rhenen et al., 2007a) Further work is also needed to clarify how these markers behave in the context of clonal hematopoiesis or myelodysplasia, and how to interpret LSC-like phenotypes in these settings. One study reported that post-remission clonal hematopoiesis can produce immunophenotypic alterations in myeloid progenitors exceeding typical regenerative patterns yet remaining distinct from the original AML, underscoring the need to avoid misclassifying such cells as MRD (Loghavi et al., 2021).
Flow cytometry studies of LSCs in AML
Several studies have applied multiparameter FC panels combining more than one marker to distinguish LSCs from normal HSCs and assess their prognostic relevance and ability to assess MRD. Table 2 summarizes many published studies in this area, ranging from single-center explorations to cooperative trial-based investigations. Please note that not all published studies could be included due to space limitations.
Table 2. Multiparameter flow cytometry studies of leukemic stem cells in acute myeloid leukemia.
Development of guidelines for LSC quantification in the clinical setting
In 2018, a consensus document from the European LeukemiaNet (ELN) MRD Working Party addressed key challenges in MRD assessment in AML (Schuurhuis et al., 2018). As part of their recommendations, the group proposed exploration of a separate LSC panel to assess total LSC burden at any point from diagnosis to relapse. They cited the approach described by Zeijlemaker et al. (2016) (Zeijlemaker et al., 2016), which included a panel combining CLL-1, TIM-3, CD7, CD11b, CD22, and CD56 in one channel, along with CD123, CD45RA, CD44, and CD33 in the same tube. Additional markers such as CD25, CD32, and CD99 were also noted to be potentially useful.
In the 2021 ELN MRD Working Party report (Heuser et al., 2021), evaluation of LSCs in FC-based MRD assessment was identified as a priority area for the future improvement of MRD recommendations. LSCs were defined immunophenotypically as CD34+/CD38- cells combined with aberrant markers not expressed on normal HSCs such as CD45RA, CLL-1, or CD123. The report highlighted that LSC measurements may have prognostic relevance and should be further validated in prospective clinical trials. For optimal detection, acquisition of approximately 4 million events was recommended, ideally using a single-tube assay. Building on this, the 2022 ELN international expert panel on AML diagnosis and management also acknowledged the potential prognostic relevance of residual LSCs and stressed the need for continued investigation and validation in this area (Dohner et al., 2022).
Prognostic significance and multimodal integration of LSC and MRD assessment in AML
Recent studies report that LSC burden in AML at diagnosis and post-treatment can carry prognostic value in adult and pediatric cohorts (Zeijlemaker et al., 2019a; Hanekamp et al., 2018). High LSC frequency is associated with earlier relapse and shorter overall survival (Ngai et al., 2023; Zeijlemaker et al., 2019a; Terwijn et al., 2014). Incorporating LSC assessment into MRD monitoring modestly improves risk stratification. For example, patients with both LAIP-MRDhigh and LSChigh showed significantly reduced survival than patients with only one or neither of these features (e.g., MRDlow/LSChigh, MRDhigh/LSClow, or MRDlow/LSClow) (Zeijlemaker et al., 2019a). In particular subsets such as LAIP-MRD-negative intermediate-risk patients, LSC positivity may guide considerations for transplant decisions or more intensive monitoring strategies (Li et al., 2022; Ngai et al., 2023).
Beyond its prognostic value, MRD assessment is emerging as a key component of AML management by offering enabling more risk-adapted and individualized treatment strategies. Persistently positive MRD after induction or consolidation identifies patients at elevated risk of relapse who may benefit from treatment intensification, such as allogeneic stem cell transplantation or enrollment in investigational protocols, whereas MRD negativity supports continuation of standard consolidation or therapy de-escalation (Freeman et al., 2018; Heuser et al., 2021).
Together, MRD and LSC analyses provide a complementary framework for predicting relapse and refining treatment decisions. Dual assessment enhances sensitivity and specificity over either approach alone (Li et al., 2022). Moreover, persistence or re-emergence of LSCs in the post-transplant setting has been associated with relapse (Li et al., 2025), suggesting that incorporating LSC monitoring into post-transplant surveillance could be beneficial. Collectively, these advances position LSC quantification as a powerful complement to MRD, bridging biological insight with clinical practice and refining therapeutic decision-making across the AML disease course.
Molecular MRD assessment adds an important layer of prognostic refinement in AML. Leukemia-specific assays targeting stable genetic lesions, such as NPM1 mutations, PML-RARA and core-binding factor (CBF) rearrangements, or other recurrent fusions, enable sensitive detection of residual disease in certain genetically defined AML subtypes (Heuser et al., 2021). NGS-based MRD monitoring can further enhance prognostic assessment when applied alongside multiparameter FC, detecting persistent or emerging variants that may indicate molecular persistence or disease evolution (Walter et al., 2021).
Advancing LSC detection with spectral flow cytometry
Spectral FC enables the simultaneous analysis of 20+ markers in a single tube (Bonilla et al., 2020), offering a powerful tool to interrogate rare leukemic subpopulations, including LSCs, without requiring multiple tubes or complex panel splitting. A recently developed 29-color single-tube spectral assay further exemplifies the potential of this technology (Zhang et al., 2025). Compared with conventional multicolor cytometry, spectral FC minimizes sample consumption and acquisition variability while enabling a more refined “different-from-normal” analysis strategy (Li K. et al., 2024). Dimensionality reduction algorithms further can enhance the resolution of immunophenotypic heterogeneity (Ferrer-Font et al., 2020), with LSCs occupying distinct and reproducible positions separate from normal HSPCs. Building on these advances, recent efforts have shifted from reliance on single surface markers to profiling co-expression patterns of multiple antigens (Haubner et al., 2019). Flow cytometric assessment of co-expression signatures improves diagnostic specificity, overcoming the phenotypic overlap between LSCs and normal HSCs, while also carrying therapeutic implications by informing the design of combinatorial targeted therapies that increase selectivity and minimize off-target toxicity. Collectively, these advances highlight how next-generation cytometry can refine LSC detection and accelerate translation into precision MRD monitoring and personalized therapeutic approaches in AML.
Future optimization of FC-based strategies is expected to further improve AML MRD detection sensitivity and specificity. For example, standardization of antibody panels across institutions, harmonized instrument settings and analysis thresholds, implementation of automated high-dimensional analysis pipelines, and integration with machine learning–based clustering tools will enhance reproducibility and objectivity in rare LSC detection. Increasing total event acquisition is likely to increase sensitivity of MRD detection as well. Finally, aligning FC-based and molecular MRD assessments may provide complementary information on residual disease and treatment response. Further studies are needed to determine whether single or combined MRD approaches offer the most accurate prognostic value and how they should be applied to guide personalized treatment decisions.
Author contributions
MY: Writing – review and editing, Conceptualization, Writing – original draft. CP: Supervision, Writing – original draft, Writing – review and editing, Conceptualization.
Funding
The authors declare that financial support was received for the research and/or publication of this article. Park was supported by NIH/NCI R01CA25166 and Youssef by a Paul E. Strandjord Young Investigator Award from the Academy of Clinical Laboratory Physicians and Scientists.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.
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Keywords: AML-acute myeloid leukemia, LSC-leukemic stem cells, flow cytometry, MRD-measurable residual disease, therapeutic targeting biomarkers
Citation: Youssef MM and Park CY (2025) Flow cytometric detection of leukemic stem cells in Acute Myeloid Leukemia: current status and future directions. Front. Pharmacol. 16:1724473. doi: 10.3389/fphar.2025.1724473
Received: 14 October 2025; Accepted: 14 November 2025;
Published: 10 December 2025.
Edited by:
Priyanka Sharma, University of Texas MD Anderson Cancer Center, United StatesReviewed by:
Saurabh Kumar Gupta, MD Anderson Cancer Center, United StatesAlbert Wölfler, Medical University of Graz, Austria
Copyright © 2025 Youssef and Park. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Mariam M. Youssef, bWFyaWFtLnlvdXNzZWZAbnl1bGFuZ29uZS5vcmc=; Christopher Y. Park, Q2hyaXN0b3BoZXIuUGFya0BueXVsYW5nb25lLm9yZw==