Imaging Flow Cytometry and Convolutional Neural Network-Based Classification Enable Discrimination of Hematopoietic and Leukemic Stem Cells in Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is a heterogenous blood cancer with a dismal prognosis. It emanates from leukemic stem cells (LSCs) arising from the genetic transformation of hematopoietic stem cells (HSCs). LSCs hold prognostic value, but their molecular and immunophenotypic heterogeneity poses challenges: there is no single marker for identifying all LSCs across AML samples. We hypothesized that imaging flow cytometry (IFC) paired with artificial intelligence-driven image analysis could visually distinguish LSCs from HSCs based solely on morphology. Initially, a seven-color IFC panel was employed to immunophenotypically identify LSCs and HSCs in bone marrow samples from five AML patients and ten healthy donors, respectively. Next, we developed convolutional neural network (CNN) models for HSC-LSC discrimination using brightfield (BF), side scatter (SSC), and DNA images. Classification using only BF images achieved 86.96% accuracy, indicating significant morphological differences. Accuracy increased to 93.42% when combining BF with DNA images, highlighting differences in nuclear morphology, although DNA images alone were inadequate for accurate HSC-LSC discrimination. Model development using SSC images revealed minor granularity differences. Performance metrics varied substantially between AML patients, indicating considerable morphologic variations among LSCs. Overall, we demonstrate proof-of-concept results for accurate CNN-based HSC-LSC differentiation, instigating the development of a novel technique within AML monitoring.

Comparative analysis of feature-based ML and CNN for binucleated erythroblast quantification in myelodysplastic syndrome patients using imaging flow cytometry data.

Myelodysplastic syndrome is primarily characterized by dysplasia in the bone marrow (BM), presenting a challenge in consistent morphology interpretation. Accurate diagnosis through traditional slide-based analysis is difficult, necessitating a standardized objective technique. Over the past two decades, imaging flow cytometry (IFC) has proven effective in combining image-based morphometric analyses with high-parameter phenotyping. We have previously demonstrated the effectiveness of combining IFC with a feature-based machine learning algorithm to accurately identify and quantify rare binucleated erythroblasts (BNEs) in dyserythropoietic BM cells. However, a feature-based workflow poses challenges requiring software-specific expertise. Here we employ a Convolutional Neural Network (CNN) algorithm for BNE identification and differentiation from doublets and cells with irregular nuclear morphology in IFC data. We demonstrate that this simplified AI workflow, coupled with a powerful CNN algorithm, achieves comparable BNE quantification accuracy to manual and feature-based analysis with substantial time savings, eliminating workflow complexity. This streamlined approach holds significant clinical value, enhancing IFC accessibility for routine diagnostic purposes.

A T cell receptor targeting a recurrent driver mutation in FLT3 mediates elimination of primary human acute myeloid leukemia in vivo.

Acute myeloid leukemia (AML), the most frequent leukemia in adults, is driven by recurrent somatically acquired genetic lesions in a restricted number of genes. Treatment with tyrosine kinase inhibitors has demonstrated that targeting of prevalent FMS-related receptor tyrosine kinase 3 (FLT3) gain-of-function mutations can provide significant survival benefits for patients, although the efficacy of FLT3 inhibitors in eliminating FLT3-mutated clones is variable. We identified a T cell receptor (TCR) reactive to the recurrent D835Y driver mutation in the FLT3 tyrosine kinase domain (TCRFLT3D/Y). TCRFLT3D/Y-redirected T cells selectively eliminated primary human AML cells harboring the FLT3D835Y mutation in vitro and in vivo. TCRFLT3D/Y cells rejected both CD34+ and CD34- AML in mice engrafted with primary leukemia from patients, reaching minimal residual disease-negative levels, and eliminated primary CD34+ AML leukemia-propagating cells in vivo. Thus, T cells targeting a single shared mutation can provide efficient immunotherapy toward selective elimination of clonally involved primary AML cells in vivo.

Dual intron-targeted CRISPR-Cas9-mediated disruption of the AML RUNX1-RUNX1T1 fusion gene effectively inhibits proliferation and decreases tumor volume in vitro and in vivo.

Oncogenic fusion drivers are common in hematological cancers and are thus relevant targets of future CRISPR-Cas9-based treatment strategies. However, breakpoint-location variation in patients pose a challenge to traditional breakpoint-targeting CRISPR-Cas9-mediated disruption strategies. Here we present a new dual intron-targeting CRISPR-Cas9 treatment strategy, for targeting t(8;21) found in 5-10% of de novo acute myeloid leukemia (AML), which efficiently disrupts fusion genes without prior identification of breakpoint location. We show in vitro growth rate and proliferation reduction by 69 and 94% in AML t(8;21) Kasumi-1 cells, following dual intron-targeted disruption of RUNX1-RUNX1T1 compared to a non t(8;21) AML control. Furthermore, mice injected with RUNX1-RUNX1T1-disrupted Kasumi-1 cells had in vivo tumor growth reduction by 69 and 91% compared to controls. Demonstrating the feasibility of RUNX1-RUNX1T1 disruption, these findings were substantiated in isolated primary cells from a patient diagnosed with AML t(8;21). In conclusion, we demonstrate proof-of-principle of a dual intron-targeting CRISPR-Cas9 treatment strategy in AML t(8;21) without need for precise knowledge of the breakpoint location.

Proteomic Profiling Identifies Specific Leukemic Stem Cell-Associated Protein Expression Patterns in Pediatric AML Patients.

Novel therapeutic tools are warranted to improve outcomes for children with acute myeloid leukemia (AML). Differences in the proteome of leukemic blasts and stem cells (AML-SCs) in AML compared with normal hematopoietic stem cells (HSCs) may facilitate the identification of potential targets for future treatment strategies. In this explorative study, we used mass spectrometry to compare the proteome of AML-SCs and CLEC12A+ blasts from five pediatric AML patients with HSCs and hematopoietic progenitor cells from hematologically healthy, age-matched controls. A total of 456 shared proteins were identified in both leukemic and control samples. Varying protein expression profiles were observed in AML-SCs and leukemic blasts, none having any overall resemblance to healthy counterpart cell populations. Thirty-four proteins were differentially expressed between AML-SCs and HSCs, including the upregulation of HSPE1, SRSF1, and NUP210, and the enrichment of proteins suggestive of protein synthesis perturbations through the downregulation of EIF2 signaling was found. Among others, NUP210 and calreticulin were upregulated in CLEC12A+ blasts compared with HSCs. In conclusion, the observed differences in protein expression between pediatric patients with AML and pediatric controls, in particular when comparing stem cell subsets, encourages the extended exploration of leukemia and AML-SC-specific biomarkers of potential relevance in the development of future therapeutic options in pediatric AML.

Immunophenotypically defined stem cell subsets in paediatric AML are highly heterogeneous and demonstrate differences in BCL-2 expression by cytogenetic subgroups.

In adult acute myeloid leukaemia (AML), immunophenotypic differences enable discrimination of leukaemic stem cells (LSCs) from healthy haematopoietic stem cells (HSCs). However, immunophenotypic stem cell characteristics are less explored in paediatric AML. Employing a 15-colour flow cytometry assay, we analysed the expression of eight aberrant surface markers together with BCL-2 on CD34+ CD38- bone marrow stem cells from 38 paediatric AML patients and seven non-leukaemic, age-matched controls. Furthermore, clonality was investigated by genetic analyses of sorted immunophenotypically abnormal stem cells from six patients. A total of 50 aberrant marker positive (non-HSC-like) subsets with 41 different immunophenotypic profiles were detected. CD123, CLEC12A, and IL1RAP were the most frequently expressed markers. IL1RAP, CD93, and CD25 expression were not restricted to stem cells harbouring leukaemia-associated mutations. Differential BCL-2 expression was found among defined cytogenetic subgroups. Interestingly, only immunophenotypically abnormal non-HSC-like subsets demonstrated BCL-2 overexpression. Collectively, we observed pronounced immunophenotypic heterogeneity within the stem cell compartment of paediatric AML patients. Additionally, certain aberrant markers used in adults seemed to be ineligible for detection of leukaemia-representing stem cells in paediatric patients implying that inference from adult studies must be done with caution.

Clonal evolution in patients developing therapy-related myeloid neoplasms following autologous stem cell transplantation.

Clonal hematopoiesis (CH) denotes somatic mutations in genes related to myeloid neoplasms present at any variant allele frequency (VAF). Clonal hematopoiesis is associated with increasing age and with a factor 6 increase in the risk of developing therapy-related myeloid neoplasms (tMNs) following autologous stem cell transplantation (ASCT). However, the impact of specific mutations on progression from CH to tMN has yet to be unraveled, and it remains unclear whether mutations directly impact or even drive the development of tMN. We performed deep sequencing in longitudinal samples from a cohort of 12 patients with either multiple myeloma or lymphoma who developed tMN following ASCT. Nine patients had one or more mutations that could be tracked longitudinally. Seven patients had clonal expansion from time of ASCT to diagnosis of tMN. Of these, six patients had CH at VAF < 2% at baseline. The median VAF of non-DNMT3A clones increased from 1% (IQR 0.7%-10.0%) at time of ASCT to 37% (IQR 17%-47%) at tMN diagnosis (P = 0.002), while DNMT3A clones showed quiescent trajectories (P = 0.625). Our data provide evidence to support the hypothesis that the development of tMN following ASCT is likely instigated by CH present at VAFs as low as 0.5%, detectable years before tMN onset.

Imaging flow cytometry reveals a subset of TdT negative T-ALL blasts with very low forward scatter on conventional flow cytometry.

BACKGROUND: Studies in T-cell acute lymphoblastic leukemia (T-ALL) have shown that leukemic blast populations may display immunophenotypic heterogeneity. In the clinical setting, evaluation of measurable residual disease during treatment and follow-up is highly dependent on knowledge of the diversity of blast subsets. Here, we set out to evaluate whether variation in expression of the blast marker, TdT, in T-ALL blasts could correspond to differences in morphometric features. METHODS: We investigated diagnostic bone marrow samples from six individual T-ALL patients run in parallel on imaging flow cytometry (IFC) and conventional flow cytometry (CFC). RESULTS: Guided by the imagery available in IFC, we identified distinct TdTneg and TdTpos subpopulations with apparent differences in internal complexity. As TdTneg blasts predominantly displayed very low forward scatter (FSC) on CFC, these subsets were initially excluded from routine analysis as debris, elements of small diameter, apoptotic, and/or dead cells. However, IFC-based morphometric analyses demonstrated that cell size and shape of TdTneg blasts were comparable to the TdTpos cells and without morphometric apoptotic hallmarks, supporting that the TdTneg subpopulation corresponded to T-ALL blasts. Fluorescence in situ hybridization analyses substantiated the clinical relevance of TdTneg FSCvery-low cells by retrieving known diagnostic cytogenetic abnormalities at comparable frequencies in purified TdTneg FSCvery-low and TdTpos FSCint subsets. CONCLUSION: We highlight this finding as knowledge of phenotypic heterogeneity is of crucial importance in the clinical setting for delineation and quantification of blast subpopulations of potential biological relevance. We argue that the IFC imagery may allow for visual verification and improvement of applied gating strategies.

OMIP 072: A 15-color panel for immunophenotypic identification, quantification, and characterization of leukemic stem cells in children with acute myeloid leukemia.

This panel was designed to identify, quantify and phenotypically characterize putative leukemic stem cells (LSCs) in bone marrow (BM) samples from individual pediatric patients diagnosed with acute myeloid leukemia (AML). Based on an aberrant expression on immunophenotypically defined hematopoietic stem cells (HSCs), several antigens have been proposed as LSC markers in AML research, using healthy adult BM samples as reference material. Generally, these antigens have been evaluated individually in smaller panels (e.g. 8-color panels). This necessitates several tubes to characterize the LSC phenotype and compromises the ability to evaluate LSC heterogeneity. The present 15-color OMIP incorporates nine suggested LSC markers to comprehensively capture LSC immunophenotypes and to explore heterogenic marker-patterns within LSC populations in a single tube. Importantly, this single tube approach requires less input material, which is essential when sampling BM aspirates from pediatric patients where sample volumes often are sparse. As knowledge on normal expression levels of the included LSC markers in HSCs from hematologically healthy children are a prerequisite for labelling a phenotype as abnormal, we have evaluated the applicability of the panel on cryopreserved mononuclear cells (MNCs) isolated from BM samples from pediatric patients without hematological disorders as well as pediatric AML patients. The panel is optimized for cryopreserved BM MNCs, but could in principle, be utilized for LSC detection in any biological material containing human hematopoietic cells.

Exploring dyserythropoiesis in patients with myelodysplastic syndrome by imaging flow cytometry and machine-learning assisted morphometrics.

BACKGROUND: The hallmark of myelodysplastic syndrome (MDS) remains dysplasia in the bone marrow (BM). However, diagnosing MDS may be challenging and subject to inter-observer variability. Thus, there is an unmet need for novel objective, standardized and reproducible methods for evaluating dysplasia. Imaging flow cytometry (IFC) offers combined analyses of phenotypic and image-based morphometric parameters, for example, cell size and nuclearity. Hence, we hypothesized IFC to be a useful tool in MDS diagnostics. METHODS: Using a different-from-normal approach, we investigated dyserythropoiesis by quantifying morphometric features in a median of 5953 erythroblasts (range: 489-68,503) from 14 MDS patients, 11 healthy donors, 6 non-MDS controls with increased erythropoiesis, and 6 patients with cytopenia. RESULTS: First, we morphometrically confirmed normal erythroid maturation, as immunophenotypically defined erythroid precursors could be sequenced by significantly decreasing cell-, nuclear- and cytoplasm area. In MDS samples, we demonstrated cell size enlargement and increased fractions of macronormoblasts in late-stage erythroblasts (both p < .0001). Interestingly, cytopenic controls with high-risk mutational patterns displayed highly aberrant cell size morphometrics. Furthermore, assisted by machine learning algorithms, we reliably identified and enumerated true binucleated erythroblasts at a significantly higher frequency in two out of three erythroblast maturation stages in MDS patients compared to normal BM (both p = .0001). CONCLUSION: We demonstrate proof-of-concept results of the applicability of automated IFC-based techniques to study and quantify morphometric changes in dyserythropoietic BM cells. We propose that IFC holds great promise as a powerful and objective tool in the complex setting of MDS diagnostics with the potential for minimizing inter-observer variability.

Clonal hematopoiesis predicts development of therapy-related myeloid neoplasms post-autologous stem cell transplantation.

Therapy-related myeloid neoplasms (tMN) develop after exposure to cytotoxic and radiation therapy, and due to their adverse prognosis, it is of paramount interest to identify patients at high risk. The presence of clonal hematopoiesis has been shown to increase the risk of developing tMN. The value of analyzing hematopoietic stem cells harvested at leukapheresis before autologous stem cell transplantation (ASCT) with next-generation sequencing and immunophenotyping represents potentially informative parameters that have yet to be discovered. We performed a nested case-control study to elucidate the association between clonal hematopoiesis, mobilization potential, and aberrant immunophenotype in leukapheresis products with the development of tMN after ASCT. A total of 36 patients with nonmyeloid disease who were diagnosed with tMN after treatment with ASCT were included as case subjects. Case subjects were identified from a cohort of 1130 patients treated with ASCT and matched with 36 control subjects who did not develop tMN after ASCT. Case subjects were significantly poorer mobilizers of CD34+ cells at leukapheresis (P = .016), indicating that these patients possess inferior bone marrow function. Both clonal hematopoiesis (odds ratio, 5.9; 95% confidence interval, 1.8-19.1; P = .003) and aberrant expression of CD7 (odds ratio, 6.6; 95% confidence interval, 1.6-26.2; P = .004) at the time of ASCT were associated with an increased risk of developing tMN after ASCT. In conclusion, clonal hematopoiesis, present at low variant allele frequencies, and aberrant CD7 expression on stem cells in leukapheresis products from patients with nonmyeloid hematologic cancer hold potential for the early identification of patients at high risk of developing tMN after ASCT.

The concept of leukaemic stem cells in acute myeloid leukaemia 25 years on: hitting a moving target.

The concept of leukaemic stem cells (LSCs) was experimentally suggested 25 years ago through seminal data from John Dick's group, who showed that a small fraction of cells from acute myeloid leukaemia (AML) patients were able to be adoptively transferred into immunodeficient mice. The initial estimation of the frequency was 1:250 000 leukaemic cells, clearly indicating the difficulties ahead in translating knowledge on LSCs to the clinical setting. However, the field has steadily grown in interest, expanse and importance, concomitantly with the realisation of the molecular background for AML culminating in the sequencing of hundreds of AML genomes. The literature is now ripe with contributions describing how different molecular aberrations are more or less specific for LSCs, as well as reports showing selectivity in targeting LSCs in comparison to normal haematopoietic stem and progenitor cells. However, we argue here that these important data have not yet been fully realised within the clinical setting. In this clinically focused review, we outline the difficulties in identifying and defining LSCs at the individual patient level, with special emphasis on intraclonal heterogeneity. In addition, we suggest areas of future focus in order to realise the concept as real-time benefit for AML patients.

Revisiting CLEC12A as leukaemic stem cell marker in AML: highlighting the necessity of precision diagnostics in patients eligible for targeted therapy.

Targeted therapy directed against rare disease-propagating leukaemic stem cells (LSCs) is a promising prospect for improving the outcome of acute myeloid leukaemia (AML) patients. Thus, distinguishing LSCs from normal haematopoietic stem and progenitor cells (HSPCs) is essential. The CLEC12A receptor has been proposed as a specific marker of LSCs, and consequently as an appealing treatment target. To explore the role of CLEC12A in further detail, we investigated whether a sorting strategy based on the activity of aldehyde dehydrogenase and CLEC12A expression could separate residual normal HSPCs from LSCs in bone marrow from 5 AML patients. We demonstrate that this distinction was possible in 2/5 cases, however with evidence of pre-leukaemic mutations in the CLEC12A- stem cells in one case. In contrast, cytogenetic and/or molecular aberrations were detected in both the CLEC12A+/- cell subsets in 3/5 AML cases studied. Furthermore, targeted next generation sequencing (NGS) of the sorted cell subsets revealed a pronounced clonal heterogeneity in the CLEC12A- cells suggestive of the leukaemia often originating in this immature cell subset. In conclusion, we provide proof-of-concept that precision diagnostics employing targeted cytogenetic/NGS-based analyses on highly purified cell subsets could be a powerful tool for selecting patients eligible for LSC-directed therapy.

Mapping the CLEC12A expression on myeloid progenitors in normal bone marrow; implications for understanding CLEC12A-related cancer stem cell biology.

The C-type lectin domain family 12, member A (CLEC12A) receptor has emerged as a leukaemia-associated and cancer stem cell marker in myeloid malignancies. However, a detailed delineation of its expression in normal haematopoiesis is lacking. Here, we have characterized the expression pattern of CLEC12A on the earliest stem- and myeloid progenitor subsets in normal bone marrow. We demonstrate distinct CLEC12A expression in the classically defined myeloid progenitors, where on average 39.1% (95% CI [32.5;45.7]) of the common myeloid progenitors (CMPs) expressed CLEC12A, while for granulocyte-macrophage progenitors and megakaryocyte-erythroid progenitors (MEPs), the average percentages were 81.0% (95% CI [76.0;85.9]) and 11.9% (95% CI [9.3;14.6]), respectively. In line with the reduced CLEC12A expression on MEPs, functional assessment of purified CLEC12A+/- CMPs and MEPs in the colony-forming unit assay demonstrated CLEC12A+ subsets to favour non-erythroid colony growth. In conclusion, we provide evidence that the earliest CLEC12A+ cell in the haematopoietic tree is the classically defined CMP. Furthermore, we show that CLEC12A-expressing CMPs and MEPs are functionally different than their negative counterparts. Importantly, these data can help determine which cells will be spared during CLEC12A-targeted therapy, and we propose CLEC12A to be included in future studies of myeloid cancer stem cell biology.