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Novel single-cell technologies in acute myeloid leukemia research

  • Soumyasri Das Gupta
    Affiliations
    Division of Hematology, Oncology, and Transplantation, Department Medicine, University of Minnesota, Minneapolis, Minn
    Search for articles by this author
  • Zohar Sachs
    Correspondence
    Reprint requests: Dr. Zohar Sachs, Division of Hematology, Oncology, and Transplantation, Department Medicine, University of Minnesota, Minneapolis, MN 55455
    Affiliations
    Division of Hematology, Oncology, and Transplantation, Department Medicine, University of Minnesota, Minneapolis, Minn

    Masonic Cancer Center, University of Minnesota, Minneapolis, Minn
    Search for articles by this author
      Acute myeloid leukemia (AML) is a lethal malignancy because patients who initially respond to chemotherapy eventually relapse with treatment refractory disease. Relapse is caused by leukemia stem cells (LSCs) that reestablish the disease through self-renewal. Self-renewal is the ability of a stem cell to produce copies of itself and give rise to progeny cells. Therefore, therapeutic strategies eradicating LSCs are essential to prevent relapse and achieve long-term remission in AML. AML is a heterogeneous disease both at phenotypic and genotypic levels, and this heterogeneity extends to LSCs. Classical studies in AML have aimed at characterization of the bulk tumor population, thereby masking cellular heterogeneity. Single-cell approaches provide a novel opportunity to elucidate molecular mechanisms in heterogeneous diseases such as AML. In recent years, major advancements in single-cell measurement systems have revolutionized our understanding of the pathophysiology of AML and enabled the characterization of LSCs. Identifying the molecular mechanisms critical to AML LSCs will aid in the development of targeted therapeutic strategies to combat this deadly disease.

      Abbreviations:

      AML (acute myeloid leukemia), LSCs (leukemic stem cells), HSCs (hematopoietic stem cells), qPCR (quantitative polymerase chain reaction), FACS (fluorescence-activated cell sorting), NGS (next generation sequencing), SCNP (single-cell network profiling)
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      References

        • Behbehani G.K.
        • Samusik N.
        • Bjornson Z.B.
        • Fantl W.J.
        • Medeiros B.C.
        • Nolan G.P.
        Mass cytometric functional profiling of acute myeloid leukemia defines cell-cycle and immunophenotypic properties that correlate with known responses to therapy.
        Cancer Discov. 2015; 5: 988-1003
        • Jamieson A.R.
        • Giger M.L.
        • Drukker K.
        • Li H.
        • Yuan Y.
        • Bhooshan N.
        Exploring nonlinear feature space dimension reduction and data representation in breast Cadx with Laplacian eigenmaps and t-SNE.
        Med Phys. 2010; 37: 339-351
        • Jan M.
        • Snyder T.M.
        • Corces-Zimmerman M.R.
        • et al.
        Clonal evolution of preleukemic hematopoietic stem cells precedes human acute myeloid leukemia.
        Sci Transl Med. 2012; 4: 149ra18
        • Shlush L.I.
        • Zandi S.
        • Mitchell A.
        • et al.
        Identification of pre-leukaemic haematopoietic stem cells in acute leukaemia.
        Nature. 2014; 506: 328-333
        • Cesano A.
        • Willman C.L.
        • Kopecky K.J.
        • et al.
        Cell signaling-based classifier predicts response to induction therapy in elderly patients with acute myeloid leukemia.
        PLoS One. 2015; 10: e0118485
        • Smith C.C.
        • Paguirigan A.
        • Jeschke G.R.
        • et al.
        Heterogeneous resistance to quizartinib in acute myeloid leukemia revealed by single-cell analysis.
        Blood. 2017; 130: 48-58
        • Smith C.C.
        • Wang Q.
        • Chin C.S.
        • et al.
        Validation of ITD mutations in FLT3 as a therapeutic target in human acute myeloid leukaemia.
        Nature. 2012; 485: 260-263
        • Ley T.J.
        • Mardis E.R.
        • Ding L.
        • et al.
        DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome.
        Nature. 2008; 456: 66-72
        • Petropoulos S.
        • Edsgard D.
        • Reinius B.
        • et al.
        Single-cell RNA-seq reveals lineage and X chromosome dynamics in human preimplantation embryos.
        Cell. 2016; 165: 1012-1026
        • Dal Molin A.
        • Baruzzo G.
        • Di Camillo B.
        Single-cell RNA-sequencing: assessment of differential expression analysis methods.
        Front Genet. 2017; 8: 62
        • Smith C.C.
        • Paguirigan A.
        • Jeschke G.R.
        • et al.
        Heterogeneous resistance to quizartinib in acute myeloid leukemia revealed by single-cell analysis.
        Blood. 2017; 130: 48-58
        • Deng Q.
        • Ramskold D.
        • Reinius B.
        • Sandberg R.
        Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells.
        Science. 2014; 343: 193-196
        • Bendall S.C.
        • Simonds E.F.
        • Qiu P.
        • et al.
        Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum.
        Science. 2011; 332: 687-696
        • Qiu P.
        • Simonds E.F.
        • Bendall S.C.
        • et al.
        Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE.
        Nat Biotechnol. 2011; 29: 886-891
        • Amir el A.D.
        • Davis K.L.
        • Tadmor M.D.
        • et al.
        viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia.
        Nat Biotechnol. 2013; 31: 545-552
        • Gibbs Jr., K.D.
        • Jager A.
        • Crespo O.
        • et al.
        Decoupling of tumor-initiating activity from stable immunophenotype in HoxA9-Meis1-driven AML.
        Cell Stem Cell. 2012; 10: 210-217
        • Saadatpour A.
        • Guo G.
        • Orkin S.H.
        • Yuan G.-C.
        Characterizing heterogeneity in leukemic cells using single-cell gene expression analysis.
        Genome Biol. 2014; 15: 525
        • Levine J.H.
        • Simonds E.F.
        • Bendall S.C.
        • et al.
        Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis.
        Cell. 2015; 162: 184-197
        • Han L.
        • Qiu P.
        • Zeng Z.
        • et al.
        Single-cell mass cytometry reveals intracellular survival/proliferative signaling in FLT3-ITD-mutated AML stem/progenitor cells.
        Cytometry A. 2015; 87: 346-356
        • Kovarik M.L.
        • Shah P.K.
        • Armistead P.M.
        • Allbritton N.L.
        Microfluidic chemical cytometry of peptide degradation in single drug-treated acute myeloid leukemia cells.
        Anal Chem. 2013; 85: 4991-4997
        • Hughes A.E.
        • Magrini V.
        • Demeter R.
        • et al.
        Clonal architecture of secondary acute myeloid leukemia defined by single-cell sequencing.
        PLoS Genet. 2014; 10: e1004462
        • Dai Y.J.
        • Wang Y.Y.
        • Huang J.Y.
        • et al.
        Conditional knockin of Dnmt3a R878H initiates acute myeloid leukemia with mTOR pathway involvement.
        Proc Natl Acad Sci U S A. 2017; 114: 5237-5242
        • Gao K.
        • Huang X.
        • Chiang C.L.
        • et al.
        Induced apoptosis investigation in wild-type and FLT3-ITD acute myeloid leukemia cells by nanochannel electroporation and single-cell qRT-PCR.
        Mol Ther. 2016; 24: 956-964
        • Corces M.R.
        • Buenrostro J.D.
        • Wu B.
        • et al.
        Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution.
        Nat Genet. 2016; 48: 1193-1203
        • Finak G.
        • McDavid A.
        • Yajima M.
        • et al.
        MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data.
        Genome Biol. 2015; 16: 278
        • Setty M.
        • Tadmor M.D.
        • Reich-Zeliger S.
        • et al.
        Wishbone identifies bifurcating developmental trajectories from single-cell data.
        Nat Biotechnol. 2016; 34: 637-645
        • Frei A.P.
        • Bava F.A.
        • Zunder E.R.
        • et al.
        Highly multiplexed simultaneous detection of RNAs and proteins in single cells.
        Nat Methods. 2016; 13: 269-275
        • Stahlberg A.
        • Thomsen C.
        • Ruff D.
        • Aman P.
        Quantitative PCR analysis of DNA, RNAs, and proteins in the same single cell.
        Clin Chem. 2012; 58: 1682-1691
        • Xue M.
        • Wei W.
        • Su Y.
        • et al.
        Chemical methods for the simultaneous quantitation of metabolites and proteins from single cells.
        J Am Chem Soc. 2015; 137: 4066-4069
        • Bonnet D.
        • Dick J.E.
        Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell.
        Nat Med. 1997; 3: 730-737
        • Goardon N.
        • Marchi E.
        • Atzberger A.
        • et al.
        Coexistence of LMPP-like and GMP-like leukemia stem cells in acute myeloid leukemia.
        Cancer Cell. 2011; 19: 138-152
        • Taussig D.C.
        • Vargaftig J.
        • Miraki-Moud F.
        • et al.
        Leukemia-initiating cells from some acute myeloid leukemia patients with mutated nucleophosmin reside in the CD34(-) fraction.
        Blood. 2010; 115: 1976-1984
        • Ng S.W.
        • Mitchell A.
        • Kennedy J.A.
        • et al.
        A 17-gene stemness score for rapid determination of risk in acute leukaemia.
        Nature. 2016; 540: 433-437
        • Ho T.C.
        • LaMere M.
        • Stevens B.M.
        • et al.
        Evolution of acute myelogenous leukemia stem cell properties after treatment and progression.
        Blood. 2016; 128: 1671-1678
        • Kroon E.
        • Krosl J.
        • Thorsteinsdottir U.
        • Baban S.
        • Buchberg A.M.
        • Sauvageau G.
        Hoxa9 transforms primary bone marrow cells through specific collaboration with Meis1a but not Pbx1b.
        EMBO J. 1998; 17: 3714-3725
        • Nolan G.P.
        Flow cytometry in the post fluorescence era.
        Best Pract Res Clin Haematol. 2011; 24: 505-508
        • Bandura D.R.
        • Baranov V.I.
        • Ornatsky O.I.
        • et al.
        Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry.
        Anal Chem. 2009; 81: 6813-6822
        • Kim W.I.
        • Matise I.
        • Diers M.D.
        • Largaespada D.A.
        RAS oncogene suppression induces apoptosis followed by more differentiated and less myelosuppressive disease upon relapse of acute myeloid leukemia.
        Blood. 2009; 113: 1086-1096
        • Sachs Z.
        • LaRue R.S.
        • Nguyen H.T.
        • et al.
        NRASG12V oncogene facilitates self-renewal in a murine model of acute myelogenous leukemia.
        Blood. 2014; 124: 3274-3283
        • Marusyk A.
        • Almendro V.
        • Polyak K.
        Intra-tumour heterogeneity: a looking glass for cancer?.
        Nat Rev Cancer. 2012; 12: 323-334
        • Eppert K.
        • Takenaka K.
        • Lechman E.R.
        • et al.
        Stem cell gene expression programs influence clinical outcome in human leukemia.
        Nat Med. 2011; 17: 1086-1093
      1. Eaton D. Murphy K.P. Exact Bayesian structure learning from uncertain interventions. AISTATS, San Juan, PR, 2007
        • Sachs K.
        • Perez O.
        • Pe'er D.
        • Lauffenburger D.A.
        • Nolan G.P.
        Causal protein-signaling networks derived from multiparameter single-cell data.
        Science. 2005; 308: 523-529
        • Sachs K.
        • Itani S.
        • Fitzgerald J.
        • et al.
        Learning cyclic signaling pathway structures while minimizing data requirements.
        Pac Symp Biocomput. 2009; : 63-74
        • Fisher D.A.C.
        • Malkova O.
        • Engle E.K.
        • et al.
        Mass cytometry analysis reveals hyperactive NF Kappa B signaling in myelofibrosis and secondary acute myeloid leukemia.
        Leukemia. 2017; 31: 1962-1974
        • Lam K.
        • Zhang D.E.
        RUNX1 and RUNX1-ETO: roles in hematopoiesis and leukemogenesis.
        Front Biosci (Landmark Ed). 2012; 17: 1120-1139
        • Unnikrishnan A.
        • Guan Y.F.
        • Huang Y.
        • et al.
        A quantitative proteomics approach identifies ETV6 and IKZF1 as new regulators of an ERG-driven transcriptional network.
        Nucleic Acids Res. 2016; 44: 10644-10661
        • Fu L.L.
        • Tian M.
        • Li X.
        • et al.
        Inhibition of BET bromodomains as a therapeutic strategy for cancer drug discovery.
        Oncotarget. 2015; 6: 5501-5516
        • Tirosh I.
        • Venteicher A.S.
        • Hebert C.
        • et al.
        Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma.
        Nature. 2016; 539: 309-313
        • Trapnell C.
        • Cacchiarelli D.
        • Grimsby J.
        • et al.
        The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells.
        Nat Biotechnol. 2014; 32: 381-386
        • Jan M.
        • Majeti R.
        Clonal evolution of acute leukemia genomes.
        Oncogene. 2013; 32: 135-140
        • Greaves M.
        • Maley C.C.
        Clonal evolution in cancer.
        Nature. 2012; 481: 306-313
        • Turner N.C.
        • Reis-Filho J.S.
        Genetic heterogeneity and cancer drug resistance.
        Lancet Oncol. 2012; 13: e178-e185
        • Welch J.S.
        • Ley T.J.
        • Link D.C.
        • et al.
        The origin and evolution of mutations in acute myeloid leukemia.
        Cell. 2012; 150: 264-278
        • Klco J.M.
        • Spencer D.H.
        • Miller C.A.
        • et al.
        Functional heterogeneity of genetically defined subclones in acute myeloid leukemia.
        Cancer Cell. 2014; 25: 379-392
        • Paguirigan A.L.
        • Smith J.
        • Meshinchi S.
        • Carroll M.
        • Maley C.
        • Radich J.P.
        Single-cell genotyping demonstrates complex clonal diversity in acute myeloid leukemia.
        Sci Transl Med. 2015; 7: 281re2
        • Becker H.
        • Yoshida K.
        • Blagitko-Dorfs N.
        • et al.
        Tracing the development of acute myeloid leukemia in CBL syndrome.
        Blood. 2014; 123: 1883-1886
        • Niemoller C.
        • Renz N.
        • Bleul S.
        • et al.
        Single cell genotyping of exome sequencing-identified mutations to characterize the clonal composition and evolution of inv(16) AML in a CBL mutated clonal hematopoiesis.
        Leuk Res. 2016; 47: 41-46
        • Murata T.
        • Takayama K.
        • Katayama S.
        • et al.
        miR-148a is an androgen-responsive microRNA that promotes LNCaP prostate cell growth by repressing its target CAND1 expression.
        Prostate Cancer Prostatic Dis. 2010; 13: 356-361
        • Miyamoto Y.
        • Yamauchi J.
        • Sanbe A.
        • Tanoue A.
        Dock6, a Dock-C subfamily guanine nucleotide exchanger, has the dual specificity for Rac1 and Cdc42 and regulates neurite outgrowth.
        Exp Cell Res. 2007; 313: 791-804
        • Peyser N.D.
        • Freilino M.
        • Wang L.
        • et al.
        Frequent promoter hypermethylation of PTPRT increases STAT3 activation and sensitivity to STAT3 inhibition in head and neck cancer.
        Oncogene. 2016; 35: 1163-1169
        • Irish J.M.
        • Hovland R.
        • Krutzik P.O.
        • et al.
        Single cell profiling of potentiated phospho-protein networks in cancer cells.
        Cell. 2004; 118: 217-228
        • Irish J.M.
        • Kotecha N.
        • Nolan G.P.
        Mapping normal and cancer cell signalling networks: towards single-cell proteomics.
        Nat Rev Cancer. 2006; 6: 146-155
        • Krutzik P.O.
        • Nolan G.P.
        Fluorescent cell barcoding in flow cytometry allows high-throughput drug screening and signaling profiling.
        Nat Methods. 2006; 3: 361-368
        • Rosen D.B.
        • Cordeiro J.A.
        • Cohen A.
        • et al.
        Assessing signaling pathways associated with in vitro resistance to cytotoxic agents in AML.
        Leuk Res. 2012; 36: 900-904
        • Kornblau S.M.
        • Minden M.D.
        • Rosen D.B.
        • et al.
        Dynamic single-cell network profiles in acute myelogenous leukemia are associated with patient response to standard induction therapy.
        Clin Cancer Res. 2010; 16: 3721-3733
        • Borland L.M.
        • Kottegoda S.
        • Phillips K.S.
        • Allbritton N.L.
        Chemical analysis of single cells.
        Annu Rev Anal Chem (Palo Alto, Calif). 2008; 1: 191-227
        • Shaffer B.C.
        • Gillet J.P.
        • Patel C.
        • Baer M.R.
        • Bates S.E.
        • Gottesman M.M.
        Drug resistance: still a daunting challenge to the successful treatment of AML.
        Drug Resist Updat. 2012; 15: 62-69
        • Khamenehfar A.
        • Gandhi M.K.
        • Chen Y.
        • Hogge D.E.
        • Li P.C.
        Dielectrophoretic microfluidic chip enables single-cell measurements for multidrug resistance in heterogeneous acute myeloid leukemia patient samples.
        Anal Chem. 2016; 88: 5680-5688
        • Jalal S.
        • Earley J.N.
        • Turchi J.J.
        DNA repair: from genome maintenance to biomarker and therapeutic target.
        Clin Cancer Res. 2011; 17: 6973-6984
        • Harper J.W.
        • Elledge S.J.
        The DNA damage response: ten years after.
        Mol Cell. 2007; 28: 739-745
        • Rosen D.B.
        • Leung L.Y.
        • Louie B.
        • et al.
        Quantitative measurement of alterations in DNA damage repair (DDR) pathways using single cell network profiling (SCNP).
        J Transl Med. 2014; 12: 184
        • Glaser S.P.
        • Lee E.F.
        • Trounson E.
        • et al.
        Anti-apoptotic Mcl-1 is essential for the development and sustained growth of acute myeloid leukemia.
        Genes Dev. 2012; 26: 120-125
        • Yoshimoto G.
        • Miyamoto T.
        • Jabbarzadeh-Tabrizi S.
        • et al.
        FLT3-ITD up-regulates MCL-1 to promote survival of stem cells in acute myeloid leukemia via FLT3-ITD-specific STAT5 activation.
        Blood. 2009; 114: 5034-5043
        • Kasper S.
        • Breitenbuecher F.
        • Heidel F.
        • et al.
        Targeting MCL-1 sensitizes FLT3-ITD-positive leukemias to cytotoxic therapies.
        Blood Cancer J. 2012; 2: e60
        • Boukany P.E.
        • Morss A.
        • Liao W.C.
        • et al.
        Nanochannel electroporation delivers precise amounts of biomolecules into living cells.
        Nat Nanotechnol. 2011; 6: 747-754
        • Gao K.
        • Li L.
        • He L.
        • et al.
        Design of a microchannel-nanochannel-microchannel array based nanoelectroporation system for precise gene transfection.
        Small. 2014; 10: 1015-1023
        • White A.K.
        • VanInsberghe M.
        • Petriv O.I.
        • et al.
        High-throughput microfluidic single-cell RT-qPCR.
        Proc Natl Acad Sci U S A. 2011; 108: 13999-14004
        • Yeh H.Y.
        • Yates M.V.
        • Mulchandani A.
        • Chen W.
        Visualizing the dynamics of viral replication in living cells via Tat peptide delivery of nuclease-resistant molecular beacons.
        Proc Natl Acad Sci U S A. 2008; 105: 17522-17525
        • Vargas D.Y.
        • Raj A.
        • Marras S.A.
        • Kramer F.R.
        • Tyagi S.
        Mechanism of mRNA transport in the nucleus.
        Proc Natl Acad Sci U S A. 2005; 102: 17008-17013