Impact of hemodilution on flow cytometry based measurable residual disease assessment in acute myeloid leukemia.

Measurable residual disease (MRD) measured in the bone marrow (BM) of acute myeloid leukemia (AML) patients after induction chemotherapy is an established prognostic factor. Hemodilution, stemming from peripheral blood (PB) mixing within BM during aspiration, can yield false-negative MRD results. We prospectively examined hemodilution by measuring MRD in BM aspirates obtained from three consecutive 2 mL pulls, along with PB samples. Our results demonstrated a significant decrease in MRD percentages between the first and second pulls (P = 0.025) and between the second and third pulls (P = 0.025), highlighting the impact of hemodilution. Initially, 39% of MRD levels (18/46 leukemia-associated immunophenotypes) exceeded the 0.1% cut-off, decreasing to 30% (14/46) in the third pull. Additionally, we assessed the performance of six published methods and parameters for distinguishing BM from PB samples, addressing or compensating for hemodilution. The most promising results relied on the percentages of CD16dim granulocytic population (scarce in BM) and CD117high mast cells (exclusive to BM). Our findings highlight the importance of estimating hemodilution in MRD assessment to qualify MRD results, particularly near the common 0.1% cut-off. To avoid false-negative results by hemodilution, it is essential to collect high-quality BM aspirations and preferably utilizing the initial pull for MRD testing.

Analytical assay validation for acute myeloid leukemia measurable residual disease assessment by multiparametric flow cytometry.

BACKGROUND: Measurable residual disease (MRD) assessed by multiparametric flow cytometry (MFC) has gained importance in clinical decision-making for acute myeloid leukemia (AML) patients. However, complying with the recent In Vitro Diagnostic Regulations (IVDR) in Europe and Food and Drug Administration (FDA) guidance in the United States requires rigorous validation prior to their use in investigational clinical trials and diagnostics. Validating AML MRD-MFC assays poses challenges due to the unique underlying disease biology and paucity of patient specimens. In this study, we describe an experimental framework for validation that meets regulatory expectations. METHODS: Our validation efforts focused on evaluating assay accuracy, analytical specificity, analytical and functional sensitivity (limit of blank (LoB), detection (LLoD) and quantitation (LLoQ)), precision, linearity, sample/reagent stability and establishing the assay background frequencies. RESULTS: Correlation between different MFC methods was highly significant (r = 0.99 for %blasts and r = 0.93 for %LAIPs). The analysis of LAIP specificity accurately discriminated from negative control cells. The assay demonstrated a LoB of 0.03, LLoD of 0.04, and LLoQ of 0.1%. Precision experiments yielded highly reproducible results (Coefficient of Variation <20%). Stability experiments demonstrated reliable measurement of samples up to 96 h from collection. Furthermore, the reference range of LAIP frequencies in non-AML patients was below 0.1%, ranging from 0.0% to 0.04%. CONCLUSION: In this manuscript, we present the validation of an AML MFC-MRD assay using BM/PB patient specimens, adhering to best practices. Our approach is expected to assist other laboratories in expediting their validation activities to fulfill recent health authority guidelines.

Characterization of myelodysplastic syndromes hematopoietic stem and progenitor cells using mass cytometry.

BACKGROUND: Myelodysplastic syndromes (MDS) at risk of transformation to acute myeloid leukemia (AML) are difficult to identify. The bone marrows of MDS patients harbor specific hematopoietic stem and progenitor cell (HSPC) abnormalities that may be associated with sub-types and risk-groups. Leukemia-associated characteristics of such cells may identify MDS patients at risk of progression to AML and provide insight in the pathobiology of MDS. METHODS: Bone marrow samples from healthy donors (n = 10), low risk (n = 12) and high risk (n = 13) MDS patients were collected, in addition, AML samples for 5 out of 6 MDS patients that progressed. Mass cytometry was applied to assess expression of stem cell subset and leukemia-associated immunophenotype markers. RESULTS: We analyzed the data using FlowSOM to cluster cells with similar expression of 10 commonly used stem cell markers. Metaclusters (n = 20) of these clusters represented populations of cells with a related phenotype, largely resembling known stem cell subsets. Within specific subsets, intra-cellular expression levels of pCREB, IkBα, or pS6 differed significantly between healthy bone marrow (HBM) and MDS or consecutive secondary AML samples. CD34, CD44, and CD49f expression was significantly increased in high risk MDS and AML-associated metaclusters. We identified MDS/sAML cells with aberrant phenotypes when compared to HBM. Such cells were observed in clusters of both primary MDS and secondary AML samples. CONCLUSIONS: High-dimensional mass cytometry and computational data analyses enabled characterization of HSPC subsets in MDS and identification of leukemia stem cell populations based on their immunophenotype. Stem cells in MDS that display leukemia-associated features may predict the risk of developing AML.

Concordance in measurable residual disease result after first and second induction cycle in acute myeloid leukemia: An outcome- and cost-analysis.

Measurable residual disease (MRD) measured using multiparameter flow-cytometry (MFC) has proven to be an important prognostic biomarker in acute myeloid leukemia (AML). In addition, MRD is increasingly used to guide consolidation treatment towards a non-allogenic stem cell transplantation treatment for MRD-negative patients in the ELN-2017 intermediate risk group. Currently, measurement of MFC-MRD in bone marrow is used for clinical decision making after 2 cycles of induction chemotherapy. However, measurement after 1 cycle has also been shown to have prognostic value, so the optimal time point remains a question of debate. We assessed the independent prognostic value of MRD results at either time point and concordance between these for 273 AML patients treated within and according to the HOVON-SAKK 92, 102, 103 and 132 trials. Cumulative incidence of relapse, event free survival and overall survival were significantly better for MRD-negative (<0.1%) patients compared to MRD-positive patients after cycle 1 and cycle 2 (p ≤ 0.002, for all comparisons). A total of 196 patients (71.8%) were MRD-negative after cycle 1, of which the vast majority remained negative after cycle 2 (180 patients; 91.8%). In contrast, of the 77 MRD-positive patients after cycle 1, only 41 patients (53.2%) remained positive. A cost reduction of -€571,751 per 100 patients could be achieved by initiating the donor search based on the MRD-result after cycle 1. This equals to a 50.7% cost reduction compared to the current care strategy in which the donor search is initiated for all patients. These results show that MRD after cycle 1 has prognostic value and is highly concordant with MRD status after cycle 2. When MRD-MFC is used to guide consolidation treatment (allo vs non-allo) in intermediate risk patients, allogeneic donor search may be postponed or omitted after cycle 1. Since the majority of MRD-negative patients remain negative after cycle 2, this could safely reduce the number of allogeneic donor searches and reduce costs.

Characteristics of leukemic stem cells in acute leukemia and potential targeted therapies for their specific eradication.

In acute myeloid leukemia (AML), a small cell population that contains stem cell features such as lack of differentiation, self-renewal potential, and drug resistance, can be identified. These so-called leukemic stem cells (LSCs) are thought to be responsible for relapse initiation after initial treatment leading to successful eradication of the bulk AML cell population. Since many studies have aimed to characterize and eliminate LSCs to prevent relapse and increase survival rates of patients, LSCs are one of the best characterized cancer stem cells. The specific elimination of LSCs, while sparing the healthy normal hematopoietic stem cells (HSCs), is one of the major challenges in the treatment of leukemia. This review focuses on several surface markers and intracellular transcription factors that can distinguish AML LSCs from HSCs and, therefore, specifically eliminate these stem cell-like leukemic cells. Moreover, previous and ongoing clinical trials of acute leukemia patients treated with therapies targeting these markers are discussed. In contrast to knowledge on LSCs in AML, insight into LSCs in acute lymphoid leukemia (ALL) is limited. This review therefore also addresses the latest insight into LSCs in ALL.

Technical Aspects of Flow Cytometry-based Measurable Residual Disease Quantification in Acute Myeloid Leukemia: Experience of the European LeukemiaNet MRD Working Party.

Measurable residual disease (MRD) quantified by multiparameter flow cytometry (MFC) is a strong and independent prognostic factor in acute myeloid leukemia (AML). However, several technical factors may affect the final read-out of the assay. Experts from the MRD Working Party of the European LeukemiaNet evaluated which aspects are crucial for accurate MFC-MRD measurement. Here, we report on the agreement, obtained via a combination of a cross-sectional questionnaire, live discussions, and a Delphi poll. The recommendations consist of several key issues from bone marrow sampling to final laboratory reporting to ensure quality and reproducibility of results. Furthermore, the experiences were tested by comparing two 8-color MRD panels in multiple laboratories. The results presented here underscore the feasibility and the utility of a harmonized theoretical and practical MFC-MRD assessment and are a next step toward further harmonization.

2021 Update on MRD in acute myeloid leukemia: a consensus document from the European LeukemiaNet MRD Working Party.

Measurable residual disease (MRD) is an important biomarker in acute myeloid leukemia (AML) that is used for prognostic, predictive, monitoring, and efficacy-response assessments. The European LeukemiaNet (ELN) MRD Working Party evaluated standardization and harmonization of MRD in an ongoing manner and has updated the 2018 ELN MRD recommendations based on significant developments in the field. New and revised recommendations were established during in-person and online meetings, and a 2-stage Delphi poll was conducted to optimize consensus. All recommendations are graded by levels of evidence and agreement. Major changes include technical specifications for next-generation sequencing-based MRD testing and integrative assessments of MRD irrespective of technology. Other topics include use of MRD as a prognostic and surrogate end point for drug testing; selection of the technique, material, and appropriate time points for MRD assessment; and clinical implications of MRD assessment. In addition to technical recommendations for flow- and molecular-MRD analysis, we provide MRD thresholds and define MRD response, and detail how MRD results should be reported and combined if several techniques are used. MRD assessment in AML is complex and clinically relevant, and standardized approaches to application, interpretation, technical conduct, and reporting are of critical importance.

Computational flow cytometry as a diagnostic tool in suspected-myelodysplastic syndromes.

The diagnostic work-up of patients suspected for myelodysplastic syndromes is challenging and mainly relies on bone marrow morphology and cytogenetics. In this study, we developed and prospectively validated a fully computational tool for flow cytometry diagnostics in suspected-MDS. The computational diagnostic workflow consists of methods for pre-processing flow cytometry data, followed by a cell population detection method (FlowSOM) and a machine learning classifier (Random Forest). Based on a six tubes FC panel, the workflow obtained a 90% sensitivity and 93% specificity in an independent validation cohort. For practical advantages (e.g., reduced processing time and costs), a second computational diagnostic workflow was trained, solely based on the best performing single tube of the training cohort. This workflow obtained 97% sensitivity and 95% specificity in the prospective validation cohort. Both workflows outperformed the conventional, expert analyzed flow cytometry scores for diagnosis with respect to accuracy, objectivity and time investment (less than 2 min per patient).

Harnessing Gene Expression Profiles for the Identification of Ex Vivo Drug Response Genes in Pediatric Acute Myeloid Leukemia.

Novel treatment strategies are of paramount importance to improve clinical outcomes in pediatric AML. Since chemotherapy is likely to remain the cornerstone of curative treatment of AML, insights in the molecular mechanisms that determine its cytotoxic effects could aid further treatment optimization. To assess which genes and pathways are implicated in tumor drug resistance, we correlated ex vivo drug response data to genome-wide gene expression profiles of 73 primary pediatric AML samples obtained at initial diagnosis. Ex vivo response of primary AML blasts towards cytarabine (Ara C), daunorubicin (DNR), etoposide (VP16), and cladribine (2-CdA) was associated with the expression of 101, 345, 206, and 599 genes, respectively (p < 0.001, FDR 0.004-0.416). Microarray based expression of multiple genes was technically validated using qRT-PCR for a selection of genes. Moreover, expression levels of BRE, HIF1A, and CLEC7A were confirmed to be significantly (p < 0.05) associated with ex vivo drug response in an independent set of 48 primary pediatric AML patients. We present unique data that addresses transcriptomic analyses of the mechanisms underlying ex vivo drug response of primary tumor samples. Our data suggest that distinct gene expression profiles are associated with ex vivo drug response, and may confer a priori drug resistance in leukemic cells. The described associations represent a fundament for the development of interventions to overcome drug resistance in AML, and maximize the benefits of current chemotherapy for sensitive patients.

Applicability and reproducibility of acute myeloid leukaemia stem cell assessment in a multi-centre setting.

Leukaemic stem cells (LSC) have been experimentally defined as the leukaemia-propagating population and are thought to be the cellular reservoir of relapse in acute myeloid leukaemia (AML). Therefore, LSC measurements are warranted to facilitate accurate risk stratification. Previously, we published the composition of a one-tube flow cytometric assay, characterised by the presence of 13 important membrane markers for LSC detection. Here we present the validation experiments of the assay in several large AML research centres, both in Europe and the United States. Variability within instruments and sample processing showed high correlations between different instruments (Rpearson  > 0·91, P < 0·001). Multi-centre testing introduced variation in reported LSC percentages but was found to be below the clinical relevant threshold. Clear gating protocols resulted in all laboratories being able to perform LSC assessment of the validation set. Participating centres were nearly unanimously able to distinguish LSChigh (>0·03% LSC) from LSClow (<0·03% LSC) despite inter-laboratory variation in reported LSC percentages. This study proves that the LSC assay is highly reproducible. These results together with the high prognostic impact of LSC load at diagnosis in AML patients render the one-tube LSC assessment a good marker for future risk classification.

Computational analysis of flow cytometry data in hematological malignancies: future clinical practice?

PURPOSE OF REVIEW: This review outlines the advancements that have been made in computational analysis for clinical flow cytometry data in hematological malignancies. RECENT FINDINGS: In recent years, computational analysis methods have been applied to clinical flow cytometry data of hematological malignancies with promising results. Most studies combined dimension reduction (principle component analysis) or clustering methods (FlowSOM, generalized mixture models) with machine learning classifiers (support vector machines, random forest). For diagnosis and classification of hematological malignancies, many studies have reported results concordant with manual expert analysis, including B-cell chronic lymphoid leukemia detection and acute leukemia classification. Other studies, e.g. concerning diagnosis of myelodysplastic syndromes and classification of lymphoma, have shown to be able to increase diagnostic accuracy. With respect to treatment response monitoring, studies have focused on, for example, computational minimal residual disease detection in multiple myeloma and posttreatment classification of healthy or diseased in acute myeloid leukemia. The results of these studies are encouraging, although accurate relapse prediction remains challenging. To facilitate clinical implementation, collaboration and (prospective) validation in multicenter setting are necessary. SUMMARY: Computational analysis methods for clinical flow cytometry data hold the potential to increase ease of use, objectivity and accuracy in the clinical work-up of hematological malignancies.

TP53 mutations and relevance of expression of TP53 pathway genes in paediatric acute myeloid leukaemia.

Limited data are available on the incidence and impact of TP53 alterations and TP53 pathway deregulation in paediatric acute myeloid leukaemia (AML). We analysed TP53 alterations in bone marrow samples of 229 patients with de novo paediatric AML, and detected heterozygous missense exon mutations in two patients (1%) and 17p deletions of the TP53 gene in four patients (2%). These patients more frequently had complex karyotype (50% vs. 4%, P = 0·002) or adverse cytogenetic abnormalities, including complex karyotype (67% vs. 17%, P = 0·013), compared to TP53 wild-type. Differential expression of TP53 pathway genes was associated with poor survival, indicating a role for TP53 regulators and effector genes.

Targeting the cell cycle in head and neck cancer by Chk1 inhibition: a novel concept of bimodal cell death.

Head and neck squamous cell carcinomas (HNSCCs) coincide with poor survival rates. The lack of driver oncogenes complicates the development of targeted treatments for HNSCC. Here, we follow-up on two previous genome-wide RNA and microRNA interference screens in HNSCC to cross-examine tumor-specific lethality by targeting ATM, ATR, CHEK1, or CHEK2. Our results uncover CHEK1 as the most promising target for HNSCC. CHEK1 expression is essential across a panel of HNSCC cell lines but redundant for growth and survival of untransformed oral keratinocytes and fibroblasts. LY2603618 (Rabusertib), which specifically targets Chk1 kinase, kills HNSCC cells effectively and specifically. Our findings show that HNSCC cells depend on Chk1-mediated signaling to progress through S-phase successfully. Chk1 inhibition coincides with stalled DNA replication, replication fork collapses, and accumulation of DNA damage. We further show that Chk1 inhibition leads to bimodal HNSCC cell killing. In the most sensitive cell lines, apoptosis is induced in S-phase, whereas more resistant cell lines manage to bypass replication-associated apoptosis, but accumulate chromosomal breaks that become lethal in subsequent mitosis. Interestingly, CDK1 expression correlates with treatment outcome. Moreover, sensitivity to Chk1 inhibition requires functional CDK1 and CDK4/6 to drive cell cycle progression, arguing against combining Chk1 inhibitors with CDK inhibitors. In contrast, Wee1 inhibitor Adavosertib progresses the cell cycle and thereby increases lethality to Chk1 inhibition in HNSCC cell lines. We conclude that Chk1 has become a key molecule in HNSCC cell cycle regulation and a very promising therapeutic target. Chk1 inhibition leads to S-phase apoptosis or death in mitosis. We provide a potential efficacy biomarker and combination therapy to follow-up in clinical setting.

Rscreenorm: normalization of CRISPR and siRNA screen data for more reproducible hit selection.

BACKGROUND: Reproducibility of hits from independent CRISPR or siRNA screens is poor. This is partly due to data normalization primarily addressing technical variability within independent screens, and not the technical differences between them. RESULTS: We present "rscreenorm", a method that standardizes the functional data ranges between screens using assay controls, and subsequently performs a piecewise-linear normalization to make data distributions across all screens comparable. In simulation studies, rscreenorm reduces false positives. Using two multiple-cell lines siRNA screens, rscreenorm increased reproducibility between 27 and 62% for hits, and up to 5-fold for non-hits. Using publicly available CRISPR-Cas screen data, application of commonly used median centering yields merely 34% of overlapping hits, in contrast with rscreenorm yielding 84% of overlapping hits. Furthermore, rscreenorm yielded at most 8% discordant results, whilst median-centering yielded as much as 55%. CONCLUSIONS: Rscreenorm yields more consistent results and keeps false positive rates under control, improving reproducibility of genetic screens data analysis from multiple cell lines.

Gene expression profiles associated with pediatric relapsed AML.

Development of relapse remains a problem for further improvements in the survival of pediatric AML patients. While virtually all patients show a good response to initial treatment, more patients respond poorly when treated at relapse. The cellular characteristics of leukemic blast cells that allow survival of initial treatment, relapse development and subsequent resistance to salvage treatment remain largely elusive. Therefore, we studied if leukemic blasts at relapse biologically resemble their initial diagnosis counterparts. We performed microarray gene expression profiling on paired initial and relapse samples of 23 pediatric AML patients. In 11 out of 23 patients, gene expression profiles of initial and corresponding relapse samples end up in different clusters in unsupervised analysis, indicating altered gene expression profiles. In addition, shifts in type I/II mutational status were found in 5 of these 11 patients, while shifts were found in 3 of the remaining 12 patients. Although differentially expressed genes varied between patients, they were commonly related to hematopoietic differentiation, encompassed genes involved in chromatin remodeling and showed associations with similar transcription factors. The top five were CEBPA, GFI1, SATB1, KLF2 and TBP. In conclusion, the leukemic blasts at relapse are biologically different from their diagnosis counterparts. These differences may be exploited for further development of novel treatment strategies.

Clinical relevance of molecular aberrations in paediatric acute myeloid leukaemia at first relapse.

Outcome for relapsed paediatric acute myeloid leukaemia (AML) remains poor. Strong prognostic factors at first relapse are lacking, which hampers optimization of therapy. We assessed the frequency of molecular aberrations (FLT3, NRAS, KRAS, KIT, WT1 and NPM1 genes) at first relapse in a large set (n = 198) of relapsed non-French-American-British M3, non-Down syndrome AML patients that received similar relapse treatment. We correlated molecular aberrations with clinical and biological factors and studied their prognostic relevance. Hotspot mutations in the analysed genes were detected in 92 out of 198 patients (46·5%). In 72 of these 92 patients (78%), molecular aberrations were mutually exclusive for the currently analysed genes. FLT3-internal tandem repeat (ITD) (18% of total group) mutations were most frequent, followed by NRAS (10·2%), KRAS (8%), WT1 (8%), KIT (8%), NPM1 (5%) and FLT3-tyrosine kinase domain (3%) mutations. Presence of a WT1 aberration was an independent risk factor for second relapse (Hazard Ratio [HR] = 2·74, P = 0·013). In patients who achieved second complete remission (70·2%), WT1 and FLT3-ITD aberrations were independent risk factors for poor overall survival (HR = 2·32, P = 0·038 and HR = 1·89, P = 0·045 respectively). These data show that molecular aberrations at first relapse are of prognostic relevance and potentially useful for risk group stratification of paediatric relapsed AML and for identification of patients eligible for personalized treatment.