scholarly journals High Throughput Immunophenotyping and Expression Profiling at Single Cell Level Reveal BCR-ABL1 Dependent Surface Markers of Chronic Myeloid Leukemia Stem Cells

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 2920-2920
Author(s):  
Marianna Romzova ◽  
Dagmar Smitalova ◽  
Peter Taus ◽  
Jiri Mayer ◽  
Martin Culen
Keyword(s):  
Stem Cells ◽  
Single Cell ◽  
Expression Profiling ◽  
Myeloid Leukemia ◽  
Single Cells ◽  
Transcript Level ◽  
Surface Expression ◽  
Surface Markers ◽  
Cell Level ◽  
Tki Treatment

BACKGROUND: Bcr-abl1 oncogene targeted treatment with tyrosine kinase inhibitors (TKI) showed an impressive efficacy against proliferating chronic myeloid leukemia (CML) cells. However, rapid relapses in more than half of CML patients after discontinuation of the treatment suggest a presence of quiescent leukemic stem cells inherently resistant to BCR-ABL1 inhibition. Understanding the heterogeneity of CML stem cell compartment is crucial for preventing the treatment failure. Specificity of already established leukemic stem cell (LSC) markers has been tested mainly in bulk CD34+CD38- populations at diagnosis. Phenotypes and molecular signatures of therapy resistant BCR ABL1 positive stem cells is however yet to be established. AIMS: Identification of BCR-ABL1 dependent LSC markers at single cell level by direct comparison their surface and transcript expression with the levels and the presence of BCR-ABL1 transcript at diagnosis and after administration of TKI treatment. METHODS: Total number of 375 cells were obtained from bone marrow and peripheral blood of 4 chronic phase CML patients. Cells were collected prior any treatment and three months after TKI treatment initiation. Normal bone marrow cells and BCR-ABL1 positive K562 cell line were used as controls. Indexed immuno-phenotyping and sorting of CD34+CD38- single cells was performed using a panel of 11 specific surface markers. Collected single cells were lysed and cDNA was enriched for 11 targets using 22 cycle pre-amplification. Expression profiling was carried on SmartChip real-time PCR system (Takara Bio) detecting following genes: BCR-ABL1, CD26, CD25, IL1-Rap, CD56, CD90, CD93, CD69, KI67, and control genes GUS and HPRT. Unsupervised clustering was performed using principal component analysis (PCA). Correlations were measured by Spearman rank method. RESULTS: At diagnosis, majority of BCR-ABL1+ C34+CD38- stem cells co-express IL1-Rap, CD26, and CD69 on their surface (88%, 82%, 78% overlap). Only 56% of BCR-ABL1+ cells positive for aforementioned markers co-express CD25, 28% CD93 and 16% CD56. The expression of these markers could also be detected in 4-11% of BCR-ABL1- cell, although this could be technical inaccuracy caused by the single cell profiling. CD90 marker did not show any correlation with BCR-ABL1 expression. At transcript level the expression of IL-1Rap, CD26, CD25 and CD56 was observed in 62%, 52% 45% and 16% BCR-ABL1+ cells, and up to 7% of BCR-ABL1- cells. CD69 expression was observed in 90% of BCR-ABL+ cells at transcript level, but also in 71% BCR-ABL- cells. BCR-ABL1 independent expression was observed for cKIT. (60% vs. 76 % in positive vs negative). Finally proliferation marker KI67 was expressed only in 6% of the BCR-ABL1+ cells. PCA analysis divided cells into several distinct clusters with BCR-ABL1 as the main contributor, and cKIT, CD69 and CD26, IL-1RAP as other significant factors. Interestingly BCR-ABL1+ cells collected during TKI treatment showed persistent surface expression of IL-1Rap and CD26, while CD56, CD69 and CD93 were only on part of the BCR-ABL1+ cells. CD25 was significantly deregulated during TKI treatment. CONCLUSION: At diagnosis up to 80% of LSC co-express 3 specific surface markers - IL-1RAP, CD26 and CD69. Variable portion of LSC co-express additional markers such are CD25, CD56 and CD93. During TKI treatment the surface expression of majority of markers is decreased, where the best correlated LSC marker is IL-1Rap, followed by CD26 and CD69. CD56 marker seems to persist in the same proportion of cells while CD25 disappears. cKIT is highly expressed in normal BM and HSC from CML patients, but also in some LSC. CD34+CD38- cells show non-proliferating phenotype. Disclosures Mayer: AOP Orphan Pharmaceuticals AG: Research Funding.

scholarly journals Crucial stem cell experiments? Stem cells, uncertainty, and single-cell experiments

2015 ◽  
Vol 30 (2) ◽  
pp. 183
Author(s):  
Melinda Fagan
Keyword(s):  
Stem Cells ◽  
Stem Cell ◽  
Single Cell ◽  
Single Cells ◽  
Single Cell Level ◽  
Epistemic Circularity ◽  
Cell Level ◽  
Differentiation Potential ◽  
Self Renewal

I have previously argued that stem cell experiments cannot in principle demonstrate that a single cell is a stem cell ([reference omitted for anonymous review]).  Laplane and others dispute this claim, citing experiments that identify stem cells at the single-cell level.  This paper rebuts the counterexample, arguing that these alleged ‘crucial stem cell experiments’ do not measure self-renewal for a single cell, do not establish a single cell’s differentiation potential, and, if interpreted as providing results about single cells, fall into epistemic circularity.  I then examine the source of the dispute, noting differences in philosophical and experimental perspectives.

scholarly journals Characterization of Leukemic Stem Cells Heterogeneity in Chronic Myeloid Leukemia

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 4140-4140
Author(s):  
Rebecca Warfvinge ◽  
Mikael Sommarin ◽  
Parashar Dhapola ◽  
Ulrich Pfisterer ◽  
Linda Geironson Ulfsson ◽  
...  
Keyword(s):  
Stem Cells ◽  
Chronic Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Kinase Inhibitor ◽  
Single Cell Analysis ◽  
Therapy Response ◽  
Surface Markers ◽  
Sequencing Analysis ◽  
Leukemic Stem Cells

In chronic myeloid leukemia (CML), a rare subset of leukemic stem cells (LSC) persists in patients responding to conventional tyrosine kinase inhibitor (TKI) therapy. The failure to eradicate these LSCs results in indefinite therapy dependence and a risk of leukemic relapse. However, the conventional LSC compartment (Lin-CD34+CD38-) is highly heterogeneous where only a subpopulation is believed to be functional, TKI-insensitive LSCs. Previously, using single-cell gene expression analysis we characterized the heterogeneity within the LSC population (Lin-CD34+CD38-) in CML patients using a selected panel of 96 primers. Interestingly, by comparing LSC heterogeneity at diagnosis with the heterogeneity following 3 months of TKI therapy we uncovered a therapy-insensitive, quiescent subpopulation, which could be isolated at high-purity using a combination of the surface markers: Lin-CD34+CD38-CD45RA-cKIT-CD26+ (Warfvinge, Geironson, Sommarin et al., 2017). Here, we expand the single-cell analysis of CML LSC populations to include combined immunophenotype-/RNA sequencing analysis (CITE-seq). CITE-seq allows for unbiased, further in-depth transcriptome analysis as wells as immunophenotypic characterization by pre-staining cells with a panel of DNA-barcoded antibodies prior to sequencing. DNA-barcoded antibodies convert the protein expression into readable sequences through unique oligo-conjugates as identifiers. Using CITE-seq with a panel of 44 distinct surface markers designed to immunophenotypically differentiate between stem/progenitors cells and leukemic clones we simultaneously characterize the molecular and immunophenotypic heterogeneity within Lin-CD34+/Lin-CD34+CD38- CML stem/progenitor compartment at diagnosis. Additionally by comparing the LSCs transcriptome from patients with different therapeutic outcome after 12 months of therapy we describe how differences in heterogeneity and the presence of immunophenotypic therapy-insensitive LSCs at diagnosis (Lin-CD34+CD38-CD45RA-cKIT-CD26+) contribute to therapy response. Disclosures Richter: Novartis: Consultancy; Pfizer: Consultancy, Research Funding.

scholarly journals SUGAR-seq enables simultaneous detection of glycans, epitopes, and the transcriptome in single cells

2021 ◽  
Vol 7 (8) ◽  
pp. eabe3610
Author(s):  
Conor J. Kearney ◽  
Stephin J. Vervoort ◽  
Kelly M. Ramsbottom ◽  
Izabela Todorovski ◽  
Emily J. Lelliott ◽  
...  
Keyword(s):  
Single Cell ◽  
Posttranslational Modification ◽  
Cellular Differentiation ◽  
Single Cells ◽  
Simultaneous Detection ◽  
Surface Protein ◽  
Rna Seq ◽  
Cell Level ◽  
Simultaneous Integration ◽  
Unique Surface

Multimodal single-cell RNA sequencing enables the precise mapping of transcriptional and phenotypic features of cellular differentiation states but does not allow for simultaneous integration of critical posttranslational modification data. Here, we describe SUrface-protein Glycan And RNA-seq (SUGAR-seq), a method that enables detection and analysis of N-linked glycosylation, extracellular epitopes, and the transcriptome at the single-cell level. Integrated SUGAR-seq and glycoproteome analysis identified tumor-infiltrating T cells with unique surface glycan properties that report their epigenetic and functional state.

scholarly journals Single-Cell Transcriptome Analysis as a Promising Tool to Study Pluripotent Stem Cell Reprogramming

2021 ◽  
Vol 22 (11) ◽  
pp. 5988
Author(s):  
Hyun Kyu Kim ◽  
Tae Won Ha ◽  
Man Ryul Lee
Keyword(s):  
Stem Cells ◽  
Single Cell ◽  
Cell Fate ◽  
Human Cell ◽  
Transcriptome Analysis ◽  
Single Cell Analysis ◽  
Embryonic Stem ◽  
Single Cell Level ◽  
Cell Analysis ◽  
Cell Level

Cells are the basic units of all organisms and are involved in all vital activities, such as proliferation, differentiation, senescence, and apoptosis. A human body consists of more than 30 trillion cells generated through repeated division and differentiation from a single-cell fertilized egg in a highly organized programmatic fashion. Since the recent formation of the Human Cell Atlas consortium, establishing the Human Cell Atlas at the single-cell level has been an ongoing activity with the goal of understanding the mechanisms underlying diseases and vital cellular activities at the level of the single cell. In particular, transcriptome analysis of embryonic stem cells at the single-cell level is of great importance, as these cells are responsible for determining cell fate. Here, we review single-cell analysis techniques that have been actively used in recent years, introduce the single-cell analysis studies currently in progress in pluripotent stem cells and reprogramming, and forecast future studies.

scholarly journals Microfluidic Platforms Designed for Morphological and Photosynthetic Investigations of Chlamydomonas reinhardtii on a Single-Cell Level

Cells ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 285
Author(s):  
Eszter Széles ◽  
Krisztina Nagy ◽  
Ágnes Ábrahám ◽  
Sándor Kovács ◽  
Anna Podmaniczki ◽  
...  
Keyword(s):  
Chlamydomonas Reinhardtii ◽  
Single Cell ◽  
Single Cells ◽  
Fluorescence Induction ◽  
Photochemical Quenching ◽  
Support Surface ◽  
Single Cell Level ◽  
Microfluidic Platforms ◽  
Cell Level ◽  
Non Photochemical Quenching

Chlamydomonas reinhardtii is a model organism of increasing biotechnological importance, yet, the evaluation of its life cycle processes and photosynthesis on a single-cell level is largely unresolved. To facilitate the study of the relationship between morphology and photochemistry, we established microfluidics in combination with chlorophyll a fluorescence induction measurements. We developed two types of microfluidic platforms for single-cell investigations: (i) The traps of the “Tulip” device are suitable for capturing and immobilizing single cells, enabling the assessment of their photosynthesis for several hours without binding to a solid support surface. Using this “Tulip” platform, we performed high-quality non-photochemical quenching measurements and confirmed our earlier results on bulk cultures that non-photochemical quenching is higher in ascorbate-deficient mutants (Crvtc2-1) than in the wild-type. (ii) The traps of the “Pot” device were designed for capturing single cells and allowing the growth of the daughter cells within the traps. Using our most performant “Pot” device, we could demonstrate that the FV/FM parameter, an indicator of photosynthetic efficiency, varies considerably during the cell cycle. Our microfluidic devices, therefore, represent versatile platforms for the simultaneous morphological and photosynthetic investigations of C. reinhardtii on a single-cell level.

scholarly journals Multiplexed Profiling of Single-cell Extracellular Vesicles Secretion

2018 ◽  
Author(s):  
Yahui Ji ◽  
Dongyuan Qi ◽  
Linmei Li ◽  
Haoran Su ◽  
Xiaojie Li ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Lines ◽  
Extracellular Vesicles ◽  
Single Cells ◽  
Cell Communication ◽  
Deep Understanding ◽  
Surface Markers ◽  
Cell Heterogeneity ◽  
Health And Disease ◽  
Cytokines Secretion

AbstractExtracellular vesicles (EVs) are important intercellular mediators regulating health and disease. Conventional EVs surface marker profiling, which was based on population measurements, masked the cell-to-cell heterogeneity in the quantity and phenotypes of EVs secretion. Herein, by using spatially patterned antibodies barcode, we realized multiplexed profiling of single-cell EVs secretion from more than 1000 single cells simultaneously. Applying this platform to profile human oral squamous cell carcinoma (OSCC) cell lines led to deep understanding of previously undifferentiated single cell heterogeneity underlying EVs secretion. Notably, we observed the decrement of certain EV phenotypes (e.g. CD63+EVs) were associated with the invasive feature of both OSCC cell lines and primary OSCC cells. We also realized multiplexed detection of EVs secretion and cytokines secretion simultaneously from the same single cells to investigate multidimensional spectrum of intercellular communications, from which we resolved three functional subgroups with distinct secretion profiles by visualized clustering. In particular, we found EVs secretion and cytokines secretion were generally dominated by different cell subgroups. The technology introduced here enables comprehensive evaluation of EVs secretion heterogeneity at single cell level, which may become an indispensable tool to complement current single cell analysis and EV research.SignificanceExtracellular vesicles (EVs) are cell derived nano-sized particles medicating cell-cell communication and transferring biology information molecules like nucleic acids to regulate human health and disease. Conventional methods for EV surface markers profiling can’t tell the differences in the quantity and phenotypes of EVs secretion between cells. To address this need, we developed a platform for profiling an array of surface markers on EVs from large numbers of single cells, enabling more comprehensive monitoring of cellular communications. Single cell EVs secretion assay led to previously unobserved cell heterogeneity underlying EVs secretion, which might open up new avenues for studying cell communication and cell microenvironment in both basic and clinical research.

scholarly journals Multicolor Immunophenotyping of Candidate Leukemic Stem Cell Markers in CD34+CD38- Chronic Myeloid Leukemia Stem Cells

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 2922-2922
Author(s):  
Martin Culen ◽  
Marianna Romzova ◽  
Dagmar Smitalova ◽  
Tomas Loja ◽  
Jiri Mayer
Keyword(s):  
Stem Cells ◽  
Chronic Myeloid Leukemia ◽  
Correlation Coefficient ◽  
Myeloid Leukemia ◽  
Chronic Phase ◽  
Surface Expression ◽  
Specific Marker ◽  
Stem Cell Markers ◽  
Similar Frequency ◽  
Median Difference

Introduction: Detection of leukemic stem cells (LSCs) may represent a new potential prognostic parameter in chronic myeloid leukemia (CML) and a tool for minimal residual disease monitoring in combination with standard qPCR method. To date CD26 is studied as a most specific marker for CML LSC detection. Several other candidate LSC markers have been reported, such as IL1-RAP, CD25 and CD93, however a side-by-side testing of their specificity is lacking. Recently, we have identified CD69 molecule to be overexpressed in CD34+CD38-CD26+ cells, which makes this antigen another candidate marker for LSC. Aim: To compare the surface expression of LSC markers CD69, CD26, CD25, CD56, IL1-RAP, CD56, CD93 in bulk CD34+CD38- population at diagnosis using a multicolor phenotypization assay Methods: In total, 44 patients were analyzed at diagnosis of chronic phase CML before administration of any treatment. Fresh (n=38) or cryopreserved (n=6) leukocytes obtained by erythrolysis were stained with CD45, CD34, CD38, CD25, CD26, CD56, CD69, CD93, IL1-RAP antibodies and 7-AAD for selection of live cells. Analysis was performed on FACSAria Fusion (BD Biosciences). Acquisition of live mononuclear cells ranged from 2×104 to 2.5×106. Results: Expression of candidate LSC markers CD26, CD25, CD56, IL1-RAP, CD56, CD93 was analyzed in BM of 35 patients who carried at least 30 CD34+CD38- cells. Median percentage of marker positive cells was 34% for IL1-RAP, 31% for CD25, 23% for CD26, 16% for CD56 and 2% for CD93, from the parent CD34+CD38- population. Next we analyzed the overlap and combination for the three best markers - IL1-RAP, CD25 and CD26. The 3-combination (defined as IL1-RAP or CD25 or CD26 expression) identified 40% of CD34+CD38- positive cells, which was more than any of the markers alone. Expression of the three markers showed good overlap and ruled out mutually exclusive expression of the markers. This was demonstrated by median difference of 0.4% of CD34+CD38- cells (range: 0-18%) and a correlation coefficient r2=0.9914, when comparing the 3-combination and the best performing marker in each patient. In contrast, in 12/35 (34%) of patients, one of the three markers failed to identify at least half of the cells positive for another marker. In 21/35 patients, we also analyzed the expression of CD69 in the CD34+CD38- compartment. The CD69 showed similar performance as the 3-combination of CD26, CD25, and IL1-RAP, 59% vs 54% positive cells, respectively. We observed excellent overlap between CD69 and 3-combination expression in individual patients with median difference of 0% of CD34+CD38- cells (range 0-15%) and correlation coefficient r2=0.9890. Furthermore, we compared marker positivity in BM vs PB in 19 paired samples. Both, sample types showed similar frequency of CD34+CD38- cells (5×10-3 in BM, and 2×10-3 for PB), but PB carried higher percentage of LSCs identified by the 3-combination - median 76 vs 52% cells. Conclusions: We show an overlap in surface expression of three previously reported CML LSC markers - IL1-RAP, CD25 and CD26. Nevertheless, a combination of these markers can detect more positive cells than any of the markers alone. Moreover, we demonstrate that CD69 identifies the same cells within the CD34+CD38- compartment as the combination of three above mentioned markers, which makes CD69 the best candidate for routine CML LSC quantification. Disclosures Mayer: AOP Orphan Pharmaceuticals AG: Research Funding.

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