Survival Stratification In Acute Myeloid Leukemia By Single Cell Signal Profiling

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2625-2625 ◽  
Author(s):  
Jørn Skavland ◽  
Håkon Reikvam ◽  
Øystein Bruserud ◽  
Bjorn T. Gjertsen
Keyword(s):  
Principal Component Analysis ◽  
Acute Myeloid Leukemia ◽  
Ribosomal Protein ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Principal Component ◽  
Leukemic Cells ◽  
Ribosomal Protein S6 ◽  
Phosphorylation Level ◽  
Acute Myeloid

Abstract Introduction Dysregulation and mutations in signaling genes of cancer cells characterize more than half of the acute myeloid leukemia (AML) patients, and contribute to chemoresistance through regulation of cellular processes including apoptosis and DNA repair. We investigated if determination of single cell basal phosphorylation of signaling proteins reflected mutation of FLT3 and NPM1, cytogenetics, response to first course of chemotherapy or overall survival. Methods We employed flow cytometric single cell analysis of phosphoproteins central to signal transduction pathways in myeloid cancer cells and analyzed peripheral blood leukocytes from 93 acute myeloid leukemia (AML) patients. Blood samples from consecutively diagnosed AML patients with high peripheral blood blast counts (>7x109/L, >70% blasts) were collected after informed consent was given and biobanked by cryo-preservation. AML samples was thawed and equilibrated for one hour in a defined serum-free medium (StemSpan SFEM medium, Stem Cell Technologies) which include insulin and transferrin. All samples were viability controlled and validated for growth factor response. Basal phosphorylation was determined using 17 phosphorylation specific antibodies: All staining panels contain the same 4 surface antibodies and a live dead discriminator; CD33(P67.6) PerCP-Cy5.5, CD38(HB7) PE-Cy7, CD34(581) PE, CD45(MEM-28) PE-Dynamics590 and phospho c-PARP(Asp214) Alexa Flour 700. Two phosphospecific antibodies were added to each panel with the respective direct conjugated dye Alexa Flour 488 and Alexa Flour 647; p38(pT180/pY182) and ERK2(pT202/pY204), SRC(pY418) and Akt(pT308), PDK1(pS241) and Akt(pS473), STAT1(pY701) and ribosomal protein S6(pS235/36), STAT3(pY705) and STAT5(pY694), CREB(pS133) and STAT3(pS727), ribosomal protein S6(pS240) and NFkB(pS529), 4EBP(pT37/pT45) and STAT6(Y641), without p-antibody and JNK(pT183/pY185). The lowest median signal for each phosphoprotein in AML cells and lymphocytes, respectively, were used as reference value for calculation of basal phosphorylation. Hierarchical clustering with the use of complete linkage were created using TM4, and Principal Component Analysis was carried out using Unscrambler X (CAMO Software). Results Unsupervised clustering revealed two distinct signature clusters based on low or elevated phosphorylation level among AML cells. A similar cluster signature was absent in endogenous non-leukemic lymphocytes from the same patients. No correlations between basal phosphorylation and prognostic mutations (FLT3 or NPM1), cytogenetics or response to first course of chemotherapy were found. In AML patients treated with intensive chemotherapy (n=45) the cluster with low phosphorylation level (n=19) correlated with significant (p=0.007) shorter overall survival. Principal component analysis verified the cluster analysis and guided a reduction to only three phosphoproteins (STAT3, 4EBP1, ribosomal protein S6) with statistically significant (p=0.014) stratification of survival. Conclusion Leukemic cells demonstrated a phosphorylation profile that reflected survival of the intensively treated patients, but surprisingly not correlated with mutational status of FLT3, NPM1, cytogenetics or first course remission status. This suggests that phosphoprotein determination in leukemic cells provide prognostic information so far not available with current diagnostics. The robust and relatively simple method of single cell signal profiling should be tested in clinical trials to examine its feasibility in therapy response prediction. More extensive mutational and epigenetic analyses are needed in search for the molecular origin of the low/high signal profiles. (A) Unsupervised hierarchical cluster analysis based on three phospho protein analysis stratified in two distinct clusters of patients receiving standard intensive induction chemotherapy (n=45; daunorubicin + cytarabine or idarubicin + cytarabine (3+7) similar to HOVON AML protocols 103 and 102, respectively). (B) Kaplan-Meier plot was performed calculating P value with the use mantel-Cox log-rank test. Disclosures: No relevant conflicts of interest to declare.

scholarly journals MutaSeq reveals the transcriptomic consequences of clonal evolution in acute myeloid leukemia

2018 ◽  
Author(s):  
Lars Velten ◽  
Benjamin A. Story ◽  
Pablo Hernandez-Malmierca ◽  
Jennifer Milbank ◽  
Malte Paulsen ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Clonal Evolution ◽  
Depth Profiling ◽  
Therapy Resistance ◽  
Leukemic Cells ◽  
Cancer Evolution ◽  
Transcriptomic Changes ◽  
Acute Myeloid

The step-wise acquisition of genetic abnormalities in cancer is thought to represent a major driver of disease initiation, relapse and therapy resistance. Acute myeloid leukemia (AML) represents a prime example of an aggressive cancer that develops in a multi-step manner from multipotent hematopoietic progenitors via pre-leukemic intermediates to leukemic cells. While bulk and single-cell genomics provide powerful tools to study the phylogenetics of cancer evolution, the specific transcriptomic changes induced by the accumulation of mutations remain largely unexplored. Here, we introduce MutaSeq, a combined single-cell genetic and transcriptomics platform for the identification of molecular consequences of cancer evolution. Through in-depth profiling of an AML patient, we demonstrate that MutaSeq is capable of: (1) fine-mapping clonal and developmental hierarchies (2) quantifying the ability of leukemic and pre-leukemic clones to give rise to mature lineages and (3) identifying surface markers and mRNA transcripts specific to pre-leukemic, leukemic, and residual healthy cells. The experimental and analytical approach presented here is broadly applicable to other types of cancer, and can help identify targets for eradicating both pre-cancerous and cancerous reservoirs of relapse.

scholarly journals Computational reconstruction of clonal hierarchies from bulk sequencing data of acute myeloid leukemia samples

2021 ◽  
Author(s):  
Thomas Stiehl ◽  
Anna Marciniak-Czochra
Keyword(s):  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Clonal Evolution ◽  
Malignant Cell ◽  
Leukemic Cells ◽  
Sequencing Data ◽  
Single Cell Sequencing ◽  
Computational Reconstruction ◽  
Acute Myeloid

AbstractAcute myeloid leukemia is an aggressive cancer of the blood forming system. The malignant cell population is composed of multiple clones that evolve over time. Clonal data reflect the mechanisms governing treatment response and relapse. Single cell sequencing provides most direct insights into the clonal composition of the leukemic cells, however it is still not routinely available in clinical practice. In this work we develop a computational algorithm that allows identifying all clonal hierarchies that are compatible with bulk variant allele frequencies measured in a patient sample. The clonal hierarchies represent descendance relations between the different clones and reveal the order in which mutations have been acquired. The proposed computational approach is tested using single cell sequencing data that allow comparing the outcome of the algorithm with the true structure of the clonal hierarchy. We investigate which problems occur during reconstruction of clonal hierarchies from bulk sequencing data. Our results suggest that in many cases only a small number of possible hierarchies fits the bulk data. This implies that bulk sequencing data can be used to obtain insights in clonal evolution.

scholarly journals Computational Reconstruction of Clonal Hierarchies From Bulk Sequencing Data of Acute Myeloid Leukemia Samples

2021 ◽  
Vol 12 ◽  
Author(s):  
Thomas Stiehl ◽  
Anna Marciniak-Czochra
Keyword(s):  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Clonal Evolution ◽  
Malignant Cell ◽  
Leukemic Cells ◽  
Sequencing Data ◽  
Single Cell Sequencing ◽  
Computational Reconstruction ◽  
Acute Myeloid

Acute myeloid leukemia is an aggressive cancer of the blood forming system. The malignant cell population is composed of multiple clones that evolve over time. Clonal data reflect the mechanisms governing treatment response and relapse. Single cell sequencing provides most direct insights into the clonal composition of the leukemic cells, however it is still not routinely available in clinical practice. In this work we develop a computational algorithm that allows identifying all clonal hierarchies that are compatible with bulk variant allele frequencies measured in a patient sample. The clonal hierarchies represent descendance relations between the different clones and reveal the order in which mutations have been acquired. The proposed computational approach is tested using single cell sequencing data that allow comparing the outcome of the algorithm with the true structure of the clonal hierarchy. We investigate which problems occur during reconstruction of clonal hierarchies from bulk sequencing data. Our results suggest that in many cases only a small number of possible hierarchies fits the bulk data. This implies that bulk sequencing data can be used to obtain insights in clonal evolution.

scholarly journals Acute myeloid leukemia with leukemic pleural effusion and high levels of pleural adenosine deaminase: A case report and review of literature

Open Medicine ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. 387-396
Author(s):  
Sing-Ting Wang ◽  
Chieh-Lung Chen ◽  
Shih-Hsin Liang ◽  
Shih-Peng Yeh ◽  
Wen-Chien Cheng
Keyword(s):  
Acute Myeloid Leukemia ◽  
Pleural Effusion ◽  
Adenosine Deaminase ◽  
Myeloid Leukemia ◽  
Diagnostic Yield ◽  
Leukemic Cells ◽  
Pleural Effusions ◽  
Diagnostic Dilemma ◽  
True Incidence ◽  
Acute Myeloid

Abstract Pleural effusions are rarely observed in association with acute myeloid leukemia (AML), and their true incidence remains unknown. Given the low diagnostic yield from cytopathologic analysis of malignant pleural effusions and the fact that patients with leukemia are often thrombocytopenic and unable to tolerate invasive procedures, the incidence of leukemic effusions may be underestimated. Here, we report a rare case of pleural effusion in a patient with newly diagnosed AML. Initial analysis revealed an exudative, lymphocyte-predominant effusion. High levels of adenosine deaminase (ADA) were detected in pleural fluid, consistent with a diagnosis of tuberculosis. However, the analysis of pleural cytology revealed leukemic cells, permitting the diagnosis of leukemic effusion to be made. The patient underwent induction chemotherapy and pleural effusion resolved without recurrence. This case emphasizes the diagnostic dilemma presented by high levels of ADA in a leukemic pleural effusion, as this association has not been previously considered in the literature.

scholarly journals Single-cell map of diverse immune phenotypes in the acute myeloid leukemia microenvironment

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Rongqun Guo ◽  
Mengdie Lü ◽  
Fujiao Cao ◽  
Guanghua Wu ◽  
Fengcai Gao ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Immune Cell ◽  
Immune Surveillance ◽  
Cell Types ◽  
Developmental Trajectory ◽  
Significant Difference ◽  
Cell Phenotypes ◽  
Acute Myeloid

Abstract Background Knowledge of immune cell phenotypes, function, and developmental trajectory in acute myeloid leukemia (AML) microenvironment is essential for understanding mechanisms of evading immune surveillance and immunotherapy response of targeting special microenvironment components. Methods Using a single-cell RNA sequencing (scRNA-seq) dataset, we analyzed the immune cell phenotypes, function, and developmental trajectory of bone marrow (BM) samples from 16 AML patients and 4 healthy donors, but not AML blasts. Results We observed a significant difference between normal and AML BM immune cells. Here, we defined the diversity of dendritic cells (DC) and macrophages in different AML patients. We also identified several unique immune cell types including T helper cell 17 (TH17)-like intermediate population, cytotoxic CD4+ T subset, T cell: erythrocyte complexes, activated regulatory T cells (Treg), and CD8+ memory-like subset. Emerging AML cells remodels the BM immune microenvironment powerfully, leads to immunosuppression by accumulating exhausted/dysfunctional immune effectors, expending immune-activated types, and promoting the formation of suppressive subsets. Conclusion Our results provide a comprehensive AML BM immune cell census, which can help to select pinpoint targeted drug and predict efficacy of immunotherapy.

scholarly journals Evidence for malignant transformation in acute myeloid leukemia at the level of early hematopoietic stem cells by cytogenetic analysis of CD34+ subpopulations

Blood ◽  
1995 ◽  
Vol 86 (8) ◽  
pp. 2906-2912 ◽  
Author(s):  
D Haase ◽  
M Feuring-Buske ◽  
S Konemann ◽  
C Fonatsch ◽  
C Troff ◽  
...  
Keyword(s):  
Stem Cells ◽  
Acute Myeloid Leukemia ◽  
Hematopoietic Stem Cells ◽  
Malignant Transformation ◽  
Cell Sorting ◽  
Myeloid Leukemia ◽  
De Novo ◽  
Leukemic Cells ◽  
Hematopoietic Stem ◽  
Acute Myeloid

Acute myeloid leukemia (AML) is a heterogenous disease according to morphology, immunophenotype, and genetics. The retained capacity of differentiation is the basis for the phenotypic classification of the bulk population of leukemic blasts and the identification of distinct subpopulations. Within the hierarchy of hematopoietic development and differentiation it is still unknown at which stage the malignant transformation occurs. It was our aim to analyze the potential involvement of cells with the immunophenotype of pluripotent stem cells in the leukemic process by the use of cytogenetic and cell sorting techniques. Cytogenetic analyses of bone marrow aspirates were performed in 13 patients with AML (11 de novo and 2 secondary) and showed karyotype abnormalities in 10 cases [2q+, +4, 6p, t(6:9), 7, +8 in 1 patient each and inv(16) in 4 patients each]. Aliquots of the samples were fractionated by fluorescence-activated cell sorting of CD34+ cells. Two subpopulations, CD34+/CD38-(early hematopoietic stem cells) and CD34+/CD38+ (more mature progenitor cells), were screened for karyotype aberations as a marker for leukemic cells. Clonal abnormalities and evaluable metaphases were found in 8 highly purified CD34+/CD38-populations and in 9 of the CD34+/CD38-specimens, respectively. In the majority of cases (CD34+/CD38-, 6 of 8 informative samples; CD34+/CD38+, 5 of 9 informative samples), the highly purified CD34+ specimens also contained cytogenetically normal cells. Secondary, progression-associated chromosomal changes (+8, 12) were identified in the CD34+/CD38-cells of 2 patients. We conclude that clonal karyotypic abnormalities are frequently found in the stem cell-like (CD34+/CD38-) and more mature (CD34+/CD38+) populations of patients with AML, irrespective of the phenotype of the bulk population of leukemic blasts and of the primary or secondary character of the leukemia. Our data suggest that, in AML, malignant transformation as well as disease progression may occur at the level of CD34+/CD38-cells with multilineage potential.

scholarly journals High expression of bcl-2 protein in acute myeloid leukemia cells is associated with poor response to chemotherapy

Blood ◽  
1993 ◽  
Vol 81 (11) ◽  
pp. 3091-3096 ◽  
Author(s):  
L Campos ◽  
JP Rouault ◽  
O Sabido ◽  
P Oriol ◽  
N Roubi ◽  
...  
Keyword(s):  
Cell Death ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Mitochondrial Protein ◽  
High Expression ◽  
Leukemic Cells ◽  
Stem Cell Marker ◽  
Cell Counts ◽  
Response To Chemotherapy ◽  
Acute Myeloid

The BCL-2 proto-oncogene encodes a mitochondrial protein that blocks programmed cell death. High amounts of bcl-2 protein are found not only in lymphoid malignancies, but also in normal tissues characterized by apoptotic cell death, including bone marrow. Using a monoclonal antibody to bcl-2 protein, we analyzed 82 samples of newly diagnosed acute myeloid leukemia. The number of bcl-2+ cells in each sample was heterogeneous (range, 0% to 95%), with a mean of 23%. The percentage of bcl-2+ cells was higher in M4 and M5 types, according to French- American-British classification, and in cases with high white blood cell counts. bcl-2 expression was also correlated with that of the stem cell marker CD34. In vitro survival of leukemic cells maintained in liquid culture in the absence of growth factors was significantly longer in cases with a high percentage of bcl-2+ cells. High expression of bcl-2 was associated with a low complete remission rate after intensive chemotherapy (29% in cases with 20% or more positive cells v 85% in cases with less than 20% positive cells, P < 10(-5)) and with a significantly shorter survival. In multivariate analysis, the percentage of bcl-2+ cells (or the blast survival in culture), age, and the percentage of CD34+ cells were independently associated with poor survival.

scholarly journals Mitochondrial Spare Reserve Capacity : A New Predictive Metabolic Biomarker for Aggressiveness of Acute Myeloid Leukemia

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 7-7
Author(s):  
Quentin Fovez ◽  
Bruno Quesnel ◽  
William Laine ◽  
Raeeka Khamari ◽  
Celine Berthon ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Oxygen Consumption ◽  
Oxidative Phosphorylation ◽  
Mutation Rate ◽  
Myeloid Leukemia ◽  
Leukemic Cells ◽  
Reserve Capacity ◽  
Glycolytic Activity ◽  
Acute Myeloid

Introduction The persistence of leukemic cells after treatment limits the effectiveness of anticancer drugs and is the cause of relapse in patients with acute myeloid leukemia (AML). After exposure to chemotherapeutic drugs, the survival of leukemic cells is mainly supported by mitochondrial energy metabolism. Several preclinical studies have shown that the combination of mitochondrial oxidative phosphorylation inhibitors with various anticancer treatments constitutes an effective therapeutic combination in vitro to eradicate the surviving leukemic cells. Evaluating the mitochondrial bioenergetic activity of blasts from AML patients could therefore provide predictive information on treatment response. The basal oxygen consumption of cells varies according to hematopoietic differentiation and depends on the energy needs in the in vitro condition of measurement. But it is necessary to treat the cells with uncoupling agents (eg FCCP) to assess the maximum activity that the respiratory chain could reach to respond to energy stress. Then, the switch from a basal level of oxygen consumption to a maximum level defines the mitochondrial spare reserve capacity (SRC). In this study, we propose to determine whether spare reserve capacity of blasts is a potential biomarker of AML aggressiveness in patients and to characterize the biochemical processes involved in the control of SRC in leukemic cells. Results Using the XFe24 Seahorse fluorometric oximeter, we first determined the mitochondrial oxygen consumption and glycolytic activity in hematopoietic cells (monocytes, lymphocytes, dendritic cells) of healthy donors, in AML patient blasts at diagnosis or at relapse and in AML cell lines (HL-60, MOLM-13, THP-1, KG1, OCI-AML3, MV-4-11, U-937). All measures have been assessed from freshly collected samples of peripheral blood and of bone marrow. As expected, AMLs are characterized by low oxidative phosphorylation activity compared to normal hematopoietic cells. From all the OXPHOS values obtained we defined a SRC threshold above which the SRC is considered high. This threshold has been set at a capacity to increase basal respiration by 250%. From patients blasts, we have therefore defined two groups characterized by high (n=14) or low (n=21) mitochondrial spare reserve capacity. Blasts with high SRC exhibit high glycolytic activity suggesting a link between spare reserve capacity and glucose metabolism. Using U-13C6 glucose and pharmacological inhibitors, we have demonstrated that the utilization of the mitochondrial spare reserve capacity of leukemic cells is supported through glycolysis and that mitochondrial oxidation of pyruvate is a key element for SRC recruitment. Mitochondrial pyruvate carrier inhibitors (as UK-5099) or gene silencing of BRP44 abolish the SRC of leukemic cells highlighting the importance of pyruvate oxidation to increase oxygen consumption. Since high mutation rate is recognized as an unfavorable prognostic factor in AML, we have also sequenced 45 commonly genes mutated in AMLs characterized by high or low SRC blasts. Interestingly, DNA sequencing analysis showed that AML with low SRC blasts have a higher mutation rate than high SRC blasts and also exhibited exclusive mutations such as ASXL1 (25%), IDH2 (25%), NPM1 (25%), IDH1 (13%), JAK2 (13%) and SF3B1 (13%). Conclusion Currently, most of the clinical biomarkers used to predict AML aggressiveness are based on DNA analysis, but the emergence of mutations is not always associated with phenotypic changes. This study shows that the mitochondrial spare reserve capacity of blasts represents a new functional biomarker based on the assessment of the energetic phenotype and could help the clinicians to determine the prognosis of AML. Moreover we have showed that altering pyruvate metabolism highly decrease spare reserve capacity of blasts and then could be evaluated as metabolic strategies to improve the therapeutic response in patients with AML. Disclosures Kluza: Daiichi-Sankyo: Research Funding.

scholarly journals Massively parallel quantification of phenotypic heterogeneity in single cell drug responses

2020 ◽  
Author(s):  
Benjamin B. Yellen ◽  
Jon S. Zawistowski ◽  
Eric A. Czech ◽  
Caleb I. Sanford ◽  
Elliott D. SoRelle ◽  
...  
Keyword(s):  
Machine Learning ◽  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Single Cell Analysis ◽  
Phenotypic Heterogeneity ◽  
Massively Parallel ◽  
Cell Analysis ◽  
On Chip ◽  
Acute Myeloid

AbstractSingle cell analysis tools have made significant advances in characterizing genomic heterogeneity, however tools for measuring phenotypic heterogeneity have lagged due to the increased difficulty of handling live biology. Here, we report a single cell phenotyping tool capable of measuring image-based clonal properties at scales approaching 100,000 clones per experiment. These advances are achieved by exploiting a novel flow regime in ladder microfluidic networks that, under appropriate conditions, yield a mathematically perfect cell trap. Machine learning and computer vision tools are used to control the imaging hardware and analyze the cellular phenotypic parameters within these images. Using this platform, we quantified the responses of tens of thousands of single cell-derived acute myeloid leukemia (AML) clones to targeted therapy, identifying rare resistance and morphological phenotypes at frequencies down to 0.05%. This approach can be extended to higher-level cellular architectures such as cell pairs and organoids and on-chip live-cell fluorescence assays.

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