Unravelling Heterogeneity of Stem and Progenitor Cells in Myeloid Neoplasms Through Single Cell Multi-omics

Intratumoural heterogeneity (ITH) underlies many of the challenges we face in cancer medicine, including therapy-resistance, disease progression/evolution and relapse after seemingly effective therapy. Distinct tumour cell subpopulations selectively evade therapy and drive disease-progression and technologies that reveal key aspects of ITH are therefore critical for the application of precision cancer medicine. Although bulk genomic analysis has without question provided many insights into genetic ITH, this approach faces a number of fundamental limitations: ITH in cancer occurs at many levels, not restricted to genetics (mutations) but also other factors, such as presence of cancer stem cells in some tumours. Furthermore, bulk genomic analysis reveals patterns of somatic mutations, but not their molecular consequences within distinct (and therapy-resistant) cancer subclones. Whilst many of the scientific questions relating to ITH have remained the same over many decades, our ability to address these questions has advanced dramatically not least because of advances in technology. Ultimately, as the unit of evolution and clonal selection by therapy in cancer is the cell, techniques that resolve heterogeneity at the single-cell level are ideally placed to unravel ITH and provide entirely new insights into cancer biology, with enormous potential to accelerate the development of new approaches to improve outcomes for patients. However, the lack of coverage across key mutation hotspots when studying cancers using single-cell RNA-sequencing techniques has precluded the correlation of genetic and transcriptional readouts from the same single cell, limiting their application to the study of tumors. To overcome such limitation, we developed TARGET-seq, a single cell multi-omic method for the high-sensitivity detection of mutations within single cells in parallel with whole transcriptome analysis. TARGET-seq achieved extremely low allelic dropout rates, allowing resolution of clonal hierarchies with over 98% accuracy, while obtaining unbiased high quality transcriptomes from the same single cell. We have applied TARGET-seq to the study of over ten thousand haematopoietic stem and progenitor cells (HSPCs) from JAK2-mutant myeloproliferative neoplasms. This analysis revealed a high degree of genetic heterogeneity, identifying both linear and branching patterns of clonal evolution. At the transcriptome level different genetic subclones showed distinct transcriptional signatures, indicating that each of them was molecularly distinct. Wild-type cells from MPN patients also showed disrupted gene expression as compared to cells from normal donors, upregulating molecular pathways associated with inflammation (TNFα, TGFβ and IFN signalling). This suggests cell-extrinsic effects disrupting gene expression in non-mutant cells, which has been shown to have prognostic significance and might underlie therapy response. Moreover, TARGET-seq analysis allowed us to identify putative biomarkers of JAK2V617F mutant cells, including novel therapeutic targets to selectively eradicate JAK2-mutant cells and importantly, potential candidates for antibody-based immunotherapy. Analysis of samples from MPN patients undergoing disease transformation to Acute Myeloid Leukemia (sAML) revealed striking patterns of clonal evolution in different immunophenotypically-defined cell types. We identified pre-leukemic and leukemic subclones emerging from hematopoietic stem cells rather than more mature progenitors, in contrast to evolution patterns in de novo AML, which might indicate different cancer stem cell reservoirs. In summary, TARGET-seq allowed us to identify distinct and biologically relevant molecular signatures of different genetic subclones of HSPCs in myeloproliferative neoplasms. TARGET-seq could also be broadly applied to the study of other types of tumours, providing a powerful tool for biomarker and therapeutic target discovery for precision medicine. Disclosures Mead: Bristol Myers-Squibb: Consultancy; Pfizer: Consultancy; Novartis: Consultancy, Honoraria, Other: Travel/accommodation expenses, Research Funding, Speakers Bureau; CTI: Honoraria, Research Funding; Celgene: Consultancy, Research Funding.

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TNFα Overproduction in FANCC-Deficient Cells Is TLR8 Dependent.

Blood ◽

10.1182/blood.v114.22.494.494 ◽

2009 ◽

Vol 114 (22) ◽

pp. 494-494

Author(s):

Scott Vanderwerf ◽

Johanna Svahn ◽

Praveen Anur ◽

Ricardo Pasquini ◽

Grover C. Bagby

Keyword(s):

Gene Expression ◽

Stem Cells ◽

Bone Marrow ◽

Fanconi Anemia ◽

Bone Marrow Failure ◽

Clonal Evolution ◽

Hematopoietic Cells ◽

Mononuclear Phagocytes ◽

C Cells ◽

Mutant Cells

Abstract Abstract 494 The Fanconi anemia (FA) proteins play a role in regulating genome stability but it is not clear that loss of genoprotection in FA hematopoietic cells accounts for the molecular pathogenesis of bone marrow failure so characteristic of this disease. Other factors are known to influence survival and replication of FA stem cells. For example, not only are FA progenitors and stem cells hypersensitive to the apoptotic effects of TNFα, FA cells over-produce TNFα. Most importantly over-production of and hypersensitivity to TNFα in hematopoietic cells of Fancc-/- mice results in bone marrow hypoplasia 1;2 and long-term ex-vivo exposure of murine Fancc -/- hematopoietic cells to both growth factors and TNFα results in the evolution of cytogenetically marked preleukemic clones.3 Therefore, the hematopoietic phenotype of FA is likely multifactorial and may evolve from the overproduction of precisely the cytokine to which FA stem cells are hypersensitive. Methods: We sought to clarify the molecular basis of aberrant TNFα-production. We conducted gene expression microarray experiments using RNA samples from low density marrow cells obtained from 11 normal volunteers and 22 Fanconi anemia patients with uncomplicated marrow hypoplasia without clonal cytogenetic defects. Because the FA complex is known to enhance ubiquitinylation of FANCD2, we reasoned that the ubiquitinylation state of proteins involved in the TNF pathways might also be influenced by core FA proteins. Therefore, we conducted in vitro ubiquitinylation assays using hexahistidine-tagged ubiquitin and an ATP-recycling system added to lysates of FANCC-deficient lymphoblasts (HSC536) and control cells (isogenic cells complemented with WT FANCC cDNA). Following the ubiquitinylation reaction, ubiquitinylated proteins were affinity purified, digested and analyzed by 2D capillary LC-MS/MS. Mass spectra were obtained and peptide precursor-MS/MS spectrum pairs were analyzed using SEQUEST and support vector machine learning.4 Peptides identified only in one or the other cell line were considered. Results: Initially we anticipated focusing on the set of proteins uniquely ubiquitinated in normal cells. However, the transcriptomal results indicated that genes encoding proteins in the ubiquitin pathway were over-represented in the list of genes that were over-expressed in FA samples. Consequently, we examined both differential ubiquitination lists and found that a major regulator of TNF-gene expression, TLR8, appeared in the ubiquitinylated fraction only in mutant cells. In co-immunoprecipitation studies we confirmed that TLR8 (or a TLR8-associated protein) is ubiquitinylated in mutant FA-C cells, and using RNAi determined that high level TNFα synthesis in mutant cells depended upon TLR8 and its downstream signaling intermediates IRAK-1 and IKK-alpha/beta. FANCC deficient THP1 blue cells were created using lentiviral shRNA targeting FANCC. These cells exhibited the MMC hypersensitive phenotype and over-expressed both TNFα and an NF-kappaB reporter gene (secreted embryonic alkaline phosphatase) in response to TLR8 agonists but not to other TLR agonists. Primary splenic macrophages from Fancc-/- mice were also hypersensitive to the TLR8 agonist R848. TNFα production in FA-C cells was suppressed by inhibitors of TLR8, p38 MAPK, IRAK, and IKK. Engineered point mutants of FANCC were capable of complementing the mitomycin C hypersensitivity phenotype of FANCC mutant cells but did not suppress TNFα overproduction in FANCC mutant cells. In conclusion, TNF over-expression in FANCC-deficient cells reflects the loss of FANCC function as a suppressor of TLR8 activation. In addition, FANCC suppresses TLR8 dependent production of TNFα in normal mononuclear phagocytes at least in part by suppressing either TLR8 ubiquitinylation or by inhibiting its association with an ubiquitinylated protein. Finally, this function of FANCC is independent of its function in protecting the genome from cross-linking agent-induced damage. In light of the role of TNFα in bone marrow failure and clonal evolution in this disease, control of TNF-production by targeting the TLR8 pathway might provide an opportunity to enhance hematopoietic activity and forestall clonal evolution in patients with this disorder. 1. Sejas DP, et al, J Immunol 2007;178:5277-5287. 2. Zhang × et al, J.Cell Sci. 2007;120:1572-1583. 3. Li J, et al, J.Clin.Invest. 2007;117:3283-3295, 4. Anderson DC, et al, J Proteome.Res 2003;2:137-146. Disclosures: No relevant conflicts of interest to declare.

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Distinct Pathogenesis of Clonal Hematopoiesis Revealed By Single Cell RNA Sequencing Integrated with Highly Sensitive Genotyping Method

Blood ◽

10.1182/blood-2021-152219 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 1092-1092

Author(s):

Masahiro Marshall Nakagawa ◽

Ryosaku Inagaki ◽

Yutaka Kuroda ◽

Yasuhito Nannya ◽

Lanying Zhao ◽

...

Keyword(s):

Gene Expression ◽

Cell Proliferation ◽

Single Cell ◽

Research Funding ◽

Inflammatory Responses ◽

Inflammatory Microenvironment ◽

Single Cell Sequencing ◽

Clonal Hematopoiesis ◽

Otsuka Pharmaceutical ◽

Mutant Cells

Abstract Background Clonal hematopoiesis (CH) in apparently healthy individuals has been drawing an increasing attention of recent years due to its implication in the risk of hematopoietic malignancies and also in cardiovascular complications. However, our knowledge on CH has been largely based on genetic studies, while few functional analyses have been performed using human materials with most studies being confined to artificial models using mice. The major challenge here is the difficulty of isolating CH clones from wild-type (WT) cells in human bone marrow (BM) to elucidate the effect of CH-mutations. Methods To investigate cellular phenotypes of mutated and WT cells separately in CH, we developed a Fluidigm C1-based single cell-sequencing platform for simultaneous genotyping and gene expression analysis. We analyzed a total of 10,178 hematopoietic stem/progenitors (HSPCs) derived from BM of patients with (n=11) and without (n=17) CH. Results In the analysis of HSPCs from CH(−) elderly individuals, we found a significant positive correlation between age and expression of gene sets implicated in inflammatory responses including TGFβ signalling and IL-6. We next analysed CH(+) samples, including those with mutations in TET2, DNMT3A, SF3B1 and IDH1 in which we investigated the pathways enriched in differentially expressed genes between mutated and unmutated cells. Regardless of mutation type, mutant cells showed an upregulation of genes implicated in an enhanced cell proliferation, while genes related to inflammatory responses were significantly downregulated. These results suggest that mutant HSPCs show an enhanced cell proliferation and an attenuated response to an inflammatory microenvironment in aged BM, compared with endogenous WT counterparts. Based on these observations, we further investigated the role of the BM microenvironment in CH, in which we compared the phenotype of WT cells in age-matched CH(+) and CH(−) cases. Compared with those from CH(−) cases, WT cells from these CH(+) cases showed an enhanced response to proinflammatory cytokines, including IL-6, interferons and TNF, suggesting a possibility that CH(+) BM might be characterized by a more enhanced inflammatory microenvironment, compared with CH(−) BM. To understand the different phenotype of WT cells between CH(+) and CH(−) cases, we next investigated a possible effect of mutant cells on endogenous WT cells. Such an effect was first documented in an IDH1-mutated CH case. IDH1-mutated cells showed a gene expression profile suggestive of an enhanced cell proliferation compared with endogenous IDH1-WT cells (WT IDH1). However, on the basis of comparison of gene expression between WT cells from CH(−) cases, it was better explained by suppressed proliferation of endogenous WT cells, rather than enhanced proliferation of mutant cells. In agreement with this, mouse BM cells treated with 2-hydroxyglutalate (2HG), an oncometabolite produced by IDH1-mutant cells, mimicked the endogenous WT cells in IDH1-mutated cases, including downregulated E2F target genes and upregulated inflammation-related genes, compared with control BM cells. A non-cell autonomous effect of mutations was also seen in cases with TET2-mutated CH, in which not only TET2-mutated cells but also endogenous WT cells exhibited a significantly different gene expression profile, compared with those from CH(−) cases. Of interest, when BM cells from WT Ly5.1/5.2 mice were co-transplanted with those from heterozygous conditional Tet2 knock-out (Ly5.2) or WT (Ly5.2) mice into lethally irradiated mice (Ly5.1) and flow-sorted Lin − WT donor competitor cells were analysed using single cell sequencing, the WT HSC-like cells co-transplanted with Tet2-mutant competitors exhibited enhanced cell proliferation and IFNα and IFNγ pathway genes, compared with those co-transplanted with WT competitors. Conclusions Taken together, these results suggest that mutant cells in CH(+) BM have non-cell autonomous effects on endogenous WT cells, which might be responsible for an accelerated inflammatory microenvironment of aged BM, favor positive selection of CH-clones, and also affect the phenotype of endogenous WT cells, contributing to the pathogenesis of CH. Disclosures Nakagawa: Sumitomo Dainippon Pharma Oncology, Inc.: Research Funding. Inagaki: Sumitomo Dainippon Pharma Oncology, Inc.: Current Employment. Nannya: Otsuka Pharmaceutical Co., Ltd.: Consultancy, Speakers Bureau; Astellas: Speakers Bureau. Yoda: Chordia Therapeutics Inc.: Research Funding. Ogawa: Kan Research Laboratory, Inc.: Consultancy, Research Funding; Dainippon-Sumitomo Pharmaceutical, Inc.: Research Funding; ChordiaTherapeutics, Inc.: Consultancy, Research Funding; Ashahi Genomics: Current holder of individual stocks in a privately-held company; Otsuka Pharmaceutical Co., Ltd.: Research Funding; Eisai Co., Ltd.: Research Funding.

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Analysis of Mechanisms Underlying Clonal Evolution of AML By a New Single-Cell Sequencing Platform

Blood ◽

10.1182/blood-2019-126444 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 542-542

Author(s):

Ryosaku Inagaki ◽

Masahiro Marshall Nakagawa ◽

Yasuhito Nannya ◽

Qi Xingxing ◽

Lanying Zhao ◽

...

Keyword(s):

Gene Expression ◽

Bone Marrow ◽

Single Cell ◽

Research Funding ◽

Clonal Evolution ◽

Clonal Expansion ◽

Ras Pathway ◽

Sequencing Platform ◽

Single Cell Sequencing ◽

Equity Ownership

Background Leukemic cell populations are highly heterogeneous in terms of both gene mutations and gene expression, which is shaped by acquisition of multiple mutations and expansion of adapted clone. This evolutional process is clinically important because it is observed in the contexts of treatment resistance and relapse as well as leukemic transformation, and molecular mechanisms involved in clonal selection can be exploited as a therapeutic target. Nevertheless, direct analysis of such mechanisms in patients' cells is hampered by technical difficulties to characterize both clonal structure and gene expression at a single-cell resolution. On this issue, we have recently developed a new method which enables simultaneously detection of mutations and whole transcriptome information at single-cell level by extensively modifying an existing single cell RNA-seq (Nakagawa et al. ASH abstract 2018). The aim of this study is to understand heterogeneity of clones and to clarify mechanisms behind clonal expansion in AML by longitudinal analysis using our novel single-cell sequencing platform. Results In order to estimate clone frequencies and select samples to be analyzed by single-cell sequencing, we first sequenced bulk bone marrow cells from patients with AML. Of interest, we found that AML samples frequently harbored multiple clones having different Ras pathway mutations, most frequently involving NRAS, which exhibited dynamic change in their clone size during the course of AML. These are interesting targets of the analysis of mechanism of clonal evolution of AML. Thus, three patients having multiple (n=3-5) Ras pathway mutations were investigated by sequencing their bone marrow Lin-, CD34+ cells using the newly established single-cell method, which successfully separated distinct clones having distinct mutations, where all of detected Ras pathway mutations were present in independent clones as expected. In order to examine these independent clones with Ras pathway mutations might show equal or heterogenous cellular phenotypes, proliferation or differentiation statuses as determined from transcriptome data was analyzed for all detected NRAS mutated clones. Among the NRAS mutated clones, some showed significant increase in proliferation-associated gene expression signature (calculated as proliferation score) compared with NRAS wild type clones, and no NRAS mutated clones showed decrease of the score, which is consistent with pro-proliferative function of Ras pathway. Interestingly, such increase in proliferation showed considerable heterogeneity among clones, where some NRAS mutated clones showed greatly increased proliferation scores compared to other NRAS mutated clones. Differentiation statuses of NRAS clones also showed heterogeneity among clones. In order to examine whether this inter-clone proliferation difference correlates with clone dynamics, we then analyzed longitudinal bone marrow samples for a patient who showed different proliferation between clones. The NRAS mutated clone with highly increased proliferation compared with wild type clone (NRAS p.G12S) had undergone rapid expansion in 3 months (cell frequency 0.08 to 0.74) in spite of continuous azacitidine treatment, while the NRAS mutated clone with less increase in proliferation (NRAS p.G12D) had showed regression (cell frequency 0.72 to 0.14). To investigate the mechanism of this therapy-resistant clonal expansion, we compared transcriptome data of these clones. Unlike the regressed clone, the expanded clone uniquely exhibited increase in expression of genes in PI3K/AKT pathway and unfolded protein response (UPR) pathway, one of cellular stress response pathway. UPR is recently reported to responsible for the promoted survival and competitive advantage in mouse hematopoietic stem cells with Nras mutations (Liu et al. Nat. Cell Biol. 2019). Our data suggest that the enhanced UPR pathway contributes to clonal expansion also in human AML with Ras pathway mutations. Conclusions Using a newly developed single-cell sequencing platform, we have successfully characterized gene expression profiles associated with clonal evolution of AML with Ras pathway mutations. Simultaneous measurement of both mutations and transcriptomes at a single-cell level will help understand the mechanism of clonal evolution of AML. Disclosures Inagaki: Sumitomo Dainippon Pharma Co., Ltd.: Employment. Nakagawa:Sumitomo Dainippon Pharma Co., Ltd.: Research Funding. Yoda:Chordia Therapeutics Inc.: Research Funding. Ogawa:RegCell Corporation: Equity Ownership; Asahi Genomics: Equity Ownership; Qiagen Corporation: Patents & Royalties; Dainippon-Sumitomo Pharmaceutical, Inc.: Research Funding; ChordiaTherapeutics, Inc.: Consultancy, Equity Ownership; Kan Research Laboratory, Inc.: Consultancy.

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Single-Cell Multi-Omics Reveals the Genetic, Cellular and Molecular Landscape of TP53 Mutated Leukemic Transformation in MPN

Blood ◽

10.1182/blood-2021-150191 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 3-3

Author(s):

Alba Rodriguez-Meira ◽

Haseeb Rahman ◽

Ruggiero Norfo ◽

Wei Wen ◽

Agathe Chédeville ◽

...

Keyword(s):

Stem Cell ◽

Single Cell ◽

Board Of Directors ◽

Research Funding ◽

Clonal Evolution ◽

Wild Type ◽

Advisory Committees ◽

Tp53 Mutations ◽

Molecular Landscape ◽

Mutant Cells

Abstract In myeloid malignancies, presence of 'multi-hit' TP53 mutations is associated with lack of response to conventional therapy and dismal outcomes, particularly when found in combination with a complex karyotype. Therefore, it is crucial to understand the biological basis of TP53-mutant driven clonal evolution, suppression of antecedent clones and eventual disease transformation to inform the development of more effective therapies. Myeloproliferative neoplasms (MPN) represent an ideal tractable disease model to study this process, as progression to secondary acute myeloid leukemia (sAML) frequently occurs through the acquisition of TP53 missense mutations. To characterize tumor phylogenies, cellular hierarchies and molecular features of TP53-driven transformation, we performed single-cell multi-omic TARGET-seq analysis (PMID: 33377019 & 30765193) of 22116 hematopoietic stem and progenitor cells (HSPCs) from 35 donors and 40 timepoints (controls, MPN in chronic phase, pre-AML and TP53-mutated sAML; Figure1a). TARGET-seq uniquely enables single-cell mutation analysis with allelic resolution with parallel transcriptomic and cell-surface proteomic readouts. We invariably identified convergent clonal evolution leading to complete loss of TP53 wild-type alleles upon transformation, including parallel evolution of separate TP53 "multi-hit" subclones in the same patient (n=4/14) and JAK2-negative progression (n=2/14). Complex clonal evolution driven by chromosomal abnormalities (CAs) was present in all patients and TP53 multi-hit HSPCs without CAs were rarely observed. Subclones with recurrent CA such as monosomy 7 showed upregulation of RAS-associated transcription and preferentially expanded in xenograft models. Together, these data indicate that TP53 missense mutation, loss of TP53 wild-type allele and cytogenetic evolution are collectively required for leukemic stem cell (LSC) expansion. Integrated transcriptomic analysis of sAML samples (Figure1b) revealed three major populations: (1) a TP53-mutant cluster (Figure1c) characterized by an erythroid signature (e.g. KLF1, GATA1, GYPA; an unexpected finding as no cases showed diagnostic features of erythroid leukemia), (2) an LSC TP53-mutant cluster (Figure1d) and (3) a TP53-WT preleukemic cluster (Figure1e). The LSC cluster showed dysregulation of key stem cell regulators, from which we derived a novel 48-gene LSC score with prognostic impact in an independent AML cohort (HR=3.13; Figure1f). Importantly, this score was predictive of outcome irrespective of TP53 status for both de novo and sAML, demonstrating its broader potential clinical utility. TARGET-seq analysis uniquely allowed us to characterize rare TP53-WT preleukemic cells (preLSCs), which were almost exclusively confined to the immunophenotypic lineage-CD34+CD38-CD90+CD45RA- HSC compartment. PreLSC from sAML samples presented increased stemness, increased quiescence, aberrant inflammatory signaling and differentiation defects (Figure1g) as compared to HSCs from normal or MPN donors, both at the transcriptional and functional levels through in vitro long-term and short-term cultures. This indicates cell-extrinsic suppression of residual TP53-WT hematopoiesis. Longitudinal analysis of TP53-heterozygous mutant HSPCs at different stages of disease evolution (Figure1a) revealed that aberrant inflammatory signalling (e.g. BST2, IFITM1, IFITM3) in the genetic ancestors of TP53 "multi-hit" LSCs, but not the presence of TP53-mutations alone, was predictive of subsequent transformation. In a mouse model system, TP53-mutant cells challenged with sustained inflammatory stimuli acquired a mean 3-fold competitive advantage in WT: TP53 R172H/+chimeras. This indicates that pro-inflammatory cues from the tumour microenvironment promote fitness advantage of TP53-mutant cells whilst supressing antecedent clones. In summary, we present a comprehensive single-cell multi-omic analysis of the genetic, cellular and molecular landscape of TP53-mediated transformation, providing unique insights into the evolution of chronic hematological malignancies towards an aggressive acute leukemia (Figure1h). Since TP53 is the most commonly mutated gene in human cancer, we anticipate these findings will be of broader relevance to many other cancer types. Figure 1 Figure 1. Disclosures Kretzschmar: Vanadis Diagnostics, a PerkinElmer company.: Current Employment. Drummond: BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; CTI: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Harrison: Geron: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Galacteo: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Keros: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sierra Oncology: Honoraria; Constellation Pharmaceuticals: Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AOP Orphan Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Incyte Corporation: Speakers Bureau; Promedior: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Roche: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Shire: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead Sciences: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; CTI BioPharma: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Mead: Abbvie: Consultancy, Honoraria; Celgene/BMS: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Speakers Bureau.

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Characterizing Population Heterogeneity and Signaling Changes in Chronic Myeloid Leukemia Stem and Progenitor Cells upon Combined Treatment with Imatinib and MEK Inhibitors Using Quantitative Single Cell Phospho-Imaging

Blood ◽

10.1182/blood-2018-99-115387 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 4248-4248

Author(s):

Anna Reister Schultz ◽

Thomas Jacob ◽

Christopher A. Eide ◽

Samantha L Savage ◽

Motomi Mori ◽

...

Keyword(s):

Stem Cells ◽

Single Cell ◽

Board Of Directors ◽

Research Funding ◽

Quantitative Imaging ◽

Single Agent ◽

Imaging Method ◽

Advisory Committees ◽

Stem And Progenitor Cells ◽

Equity Ownership

Abstract Chronic myeloid leukemia (CML) is caused by the oncogenic tyrosine kinase BCR-ABL1, which is uniquely present in the leukemic cells and drives progression of the disease. Small-molecule ABL1 tyrosine kinase inhibitors (TKIs) have transformed prognosis for patients as compared to interferon or standard chemotherapy, with the vast majority of patients achieving deep, long-term remission on treatment (Druker et al., Nature Medicine 2009). However, results from multiple TKI discontinuation studies over the past decade suggest approximately 50-60% of patients must remain on therapy indefinitely, highlighting challenges associated with the retention of a residual pool of BCR-ABL1-positive leukemic stem cells (LSCs) (Mahon et al., The Lancet 2018; Ross et al., Blood 2013). Previously we have shown that, while ABL1 TKIs can effectively inhibit BCR-ABL1 kinase activity and reduce CML disease burden, LSCs avoid ABL1 TKI-induced cell death via alternate signaling pathways such as MEK/ERK and are able to persist (Corbin et al., JCI 2011). Detecting changes in phospho-activation of such alternative pathways at the single cell level using primary CML samples has yet to be characterized and will inform therapeutic options for complete disease eradication. Here, we dissect phospho-signaling diversity with single cell level granularity across heterogeneous subpopulations of CML stem (CD34+CD38-) and progenitor (CD34+CD38+) cells upon drug treatment using a new quantitative imaging method that allows for sensitive detection of critical changes in signaling (Jacob et al., Scientific Reports 2016). Briefly, primary CD34+ cells were isolated from newly diagnosed TKI naïve CML patients by MACS column and cultured ex-vivo in the presence of imatinib and MEK inhibitors (trametinib or cobimetinib), either alone or in combination. Cells were then assessed for apoptosis by flow cytometry annexin assay, followed by fixing/staining for CD38, pCRKL, and pERK, and quantified for changes in signaling upon treatment by quantitative imaging method. This new phospho-imaging method allows for low cell number input and maximizes data output per sample, opening opportunities to assess translational applicability of combinations in a highly biologically relevant context of small but critical LSC populations. Quantification of phospho-signal revealed that pCRKL was reduced in a dose dependent manner across a range of concentrations of imatinib in both CML stem and progenitor cells. In contrast, while pERK levels were also reduced with imatinib treatment, a subset of CML stem cells exhibited high levels of pERK signaling even at high (5uM) concentrations of imatinib. Combination treatment with imatinib and trametinib or cobimetinib markedly increased apoptosis in CML CD34+ cells compared to each single agent. Within the stem cell population, median pERK fluorescence was significantly reduced with imatinib or trametinib compared to untreated control (p<0.0001), and further reduced with the combination compared to each single agent (p<0.0001 and p=0.04, respectively). Furthermore, the percent of cells with pERK levels below the untreated median value was 87%, 90% and 97% upon treatment with imatinib, trametinib or the combination respectively. Together, our data suggest that variable levels of ERK phosphorylation exist within the CML stem and progenitor compartments, including a subset of CML stem cells that exhibit persistently high levels of pERK despite effective suppression of BCR-ABL1 kinase activity by imatinib. This stem cell persistence warrants the need for combination strategies to inhibit BCR-ABL1 and MEK/ERK for their complete elimination. Disclosures Tyner: AstraZeneca: Research Funding; Gilead: Research Funding; Incyte: Research Funding; Aptose: Research Funding; Janssen: Research Funding; Genentech: Research Funding; Leap Oncology: Equity Ownership; Syros: Research Funding; Takeda: Research Funding; Seattle Genetics: Research Funding; Agios: Research Funding. Druker:Celgene: Consultancy; Leukemia & Lymphoma Society: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oregon Health & Science University: Patents & Royalties; Beta Cat: Membership on an entity's Board of Directors or advisory committees; Cepheid: Consultancy, Membership on an entity's Board of Directors or advisory committees; MolecularMD: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Patient True Talk: Consultancy; Third Coast Therapeutics: Membership on an entity's Board of Directors or advisory committees; GRAIL: Consultancy, Membership on an entity's Board of Directors or advisory committees; Monojul: Consultancy; Aptose Therapeutics: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Blueprint Medicines: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Gilead Sciences: Consultancy, Membership on an entity's Board of Directors or advisory committees; Henry Stewart Talks: Patents & Royalties; Fred Hutchinson Cancer Research Center: Research Funding; McGraw Hill: Patents & Royalties; Vivid Biosciences: Membership on an entity's Board of Directors or advisory committees; Aileron Therapeutics: Consultancy; Novartis Pharmaceuticals: Research Funding; ARIAD: Research Funding; Millipore: Patents & Royalties; Amgen: Membership on an entity's Board of Directors or advisory committees; ALLCRON: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Meyers Squibb: Research Funding.

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Identification of leukemic and pre-leukemic stem cells by clonal tracking from single-cell transcriptomics

Nature Communications ◽

10.1038/s41467-021-21650-1 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Lars Velten ◽

Benjamin A. Story ◽

Pablo Hernández-Malmierca ◽

Simon Raffel ◽

Daniel R. Leonce ◽

...

Keyword(s):

Gene Expression ◽

Stem Cells ◽

Cancer Stem Cells ◽

Single Cell ◽

Lineage Tracing ◽

Specific Gene ◽

Leukemic Stem Cells ◽

Hematopoietic Stem ◽

Mutational Status

AbstractCancer stem cells drive disease progression and relapse in many types of cancer. Despite this, a thorough characterization of these cells remains elusive and with it the ability to eradicate cancer at its source. In acute myeloid leukemia (AML), leukemic stem cells (LSCs) underlie mortality but are difficult to isolate due to their low abundance and high similarity to healthy hematopoietic stem cells (HSCs). Here, we demonstrate that LSCs, HSCs, and pre-leukemic stem cells can be identified and molecularly profiled by combining single-cell transcriptomics with lineage tracing using both nuclear and mitochondrial somatic variants. While mutational status discriminates between healthy and cancerous cells, gene expression distinguishes stem cells and progenitor cell populations. Our approach enables the identification of LSC-specific gene expression programs and the characterization of differentiation blocks induced by leukemic mutations. Taken together, we demonstrate the power of single-cell multi-omic approaches in characterizing cancer stem cells.

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Heterogeneous disease-propagating stem cells in juvenile myelomonocytic leukemia

Journal of Experimental Medicine ◽

10.1084/jem.20180853 ◽

2021 ◽

Vol 218 (2) ◽

Cited By ~ 1

Author(s):

Eleni Louka ◽

Benjamin Povinelli ◽

Alba Rodriguez-Meira ◽

Gemma Buck ◽

Wei Xiong Wen ◽

...

Keyword(s):

Stem Cells ◽

Stem Cell ◽

Single Cell ◽

Rna Sequencing ◽

Childhood Leukemia ◽

Clonal Evolution ◽

Juvenile Myelomonocytic Leukemia ◽

Hematopoietic Stem ◽

Ras Pathway ◽

Myelomonocytic Leukemia

Juvenile myelomonocytic leukemia (JMML) is a poor-prognosis childhood leukemia usually caused by RAS-pathway mutations. The cellular hierarchy in JMML is poorly characterized, including the identity of leukemia stem cells (LSCs). FACS and single-cell RNA sequencing reveal marked heterogeneity of JMML hematopoietic stem/progenitor cells (HSPCs), including an aberrant Lin−CD34+CD38−CD90+CD45RA+ population. Single-cell HSPC index-sorting and clonogenic assays show that (1) all somatic mutations can be backtracked to the phenotypic HSC compartment, with RAS-pathway mutations as a “first hit,” (2) mutations are acquired with both linear and branching patterns of clonal evolution, and (3) mutant HSPCs are present after allogeneic HSC transplant before molecular/clinical evidence of relapse. Stem cell assays reveal interpatient heterogeneity of JMML LSCs, which are present in, but not confined to, the phenotypic HSC compartment. RNA sequencing of JMML LSC reveals up-regulation of stem cell and fetal genes (HLF, MEIS1, CNN3, VNN2, and HMGA2) and candidate therapeutic targets/biomarkers (MTOR, SLC2A1, and CD96), paving the way for LSC-directed disease monitoring and therapy in this disease.

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Single cell 3’UTR analysis identifies changes in alternative polyadenylation throughout neuronal differentiation and in autism

10.1101/2020.08.12.247627 ◽

2020 ◽

Author(s):

Manuel Göpferich ◽

Nikhil Oommen George ◽

Ana Domingo Muelas ◽

Alex Bizyn ◽

Rosa Pascual ◽

...

Keyword(s):

Gene Expression ◽

Stem Cells ◽

Neural Stem Cells ◽

Single Cell ◽

Neuronal Differentiation ◽

Mrna Translation ◽

Autism Spectrum ◽

Adult Brain ◽

Control Of Gene Expression ◽

Risk Genes

SUMMARYAutism spectrum disorder (ASD) is a neurodevelopmental disease affecting social behavior. Many of the high-confident ASD risk genes relate to mRNA translation. Specifically, many of these genes are involved in regulation of gene expression for subcellular compartmentalization of proteins1. Cis-regulatory motifs that often localize to 3’- and 5’-untranslated regions (UTRs) offer an additional path for posttranscriptional control of gene expression. Alternative cleavage and polyadenylation (APA) affect 3’UTR length thereby influencing the presence or absence of regulatory elements. However, APA has not yet been addressed in the context of neurodevelopmental disorders. Here we used single cell 3’end sequencing to examine changes in 3’UTRs along the differentiation from neural stem cells (NSCs) to neuroblasts within the adult brain. We identified many APA events in genes involved in neurodevelopment, many of them being high confidence ASD risk genes. Further, analysis of 3’UTR lengths in single cells from ASD and healthy individuals detected longer 3’UTRs in ASD patients. Motif analysis of modulated 3’UTRs in the mouse adult neurogenic lineage and ASD-patients revealed enrichment of the cytoplasmic and polyadenylation element (CPE). This motif is bound by CPE binding protein 4 (CPEB4). In human and mouse data sets we observed co-regulation of CPEB4 and the CPEB-binding synaptic adhesion molecule amyloid beta precursor-like protein 1 (APLP1). We show that mice deficient in APLP1 show aberrant regulation of APA, decreased number of neural stem cells, and autistic-like traits. Our findings indicate that APA is used for control of gene expression along neuronal differentiation and is altered in ASD patients.

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Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis

Nature Cell Biology ◽

10.1038/ncb2709 ◽

2013 ◽

Vol 15 (4) ◽

pp. 363-372 ◽

Cited By ~ 197

Author(s):

Victoria Moignard ◽

Iain C. Macaulay ◽

Gemma Swiers ◽

Florian Buettner ◽

Judith Schütte ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Progenitor Cells ◽

High Throughput ◽

Gene Expression Analysis ◽

Transcriptional Networks ◽

Stem And Progenitor Cells ◽

Cell Gene Expression ◽

Cell Gene

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A Comprehensive Analysis of Single-Cell Chromatin Accessibility and Gene Expression Identifies Intra-Tumor Heterogeneity and Molecular Treatment Responses in Relapsed/Refractory Multiple Myeloma

Blood ◽

10.1182/blood-2019-130051 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 575-575

Author(s):

Alexandra M Poos ◽

Jan-Philipp Mallm ◽

Stephan M Tirier ◽

Nicola Casiraghi ◽

Hana Susak ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Board Of Directors ◽

Research Funding ◽

Tumor Heterogeneity ◽

Mek Inhibitor ◽

Chromatin Accessibility ◽

University Research ◽

Sample Processing ◽

Advisory Committees

Introduction: Multiple myeloma (MM) is a heterogeneous malignancy of clonal plasma cells that accumulate in the bone marrow (BM). Despite new treatment approaches, in most patients resistant subclones are selected by therapy, resulting in the development of refractory disease. While the subclonal architecture in newly diagnosed patients has been investigated in great detail, intra-tumor heterogeneity in relapsed/refractory (RR) MM is poorly characterized. Recent technological and computational advances provide the opportunity to systematically analyze tumor samples at single-cell (sc) level with high accuracy and througput. Here, we present a pilot study for an integrative analysis of sc Assay for Transposase-Accessible Chromatin with high-throughput sequencing (scATAC-seq) and scRNA-seq with the aim to comprehensively study the regulatory landscape, gene expression, and evolution of individual subclones in RRMM patients. Methods: We have included 20 RRMM patients with longitudinally collected paired BM samples. scATAC- and scRNA-seq data were generated using the 10X Genomics platform. Pre-processing of the sc-seq data was performed with the CellRanger software (reference genome GRCh38). For downstream analyses the R-packages Seurat and Signac (Satija Lab) as well as Cicero (Trapnell Lab) were used. For all patients bulk whole genome sequencing (WGS) data was available, which we used for confirmatory studies of intra-tumor heterogeneity. Results: A comprehensive study at the sc level requires extensive quality controls (QC). All scATAC-seq files passed the QC, including the detected number of cells, number of fragments in peaks or the ratio of mononucleosomal to nucleosome-free fragments. Yet, unsupervised clustering of the differentially accessible regions resulted in two main clusters, strongly associated with sample processing time. Delay of sample processing by 1-2 days, e.g. due to shipment from participating centers, resulted in global change of chromatin accessibility with more than 10,000 regions showing differences compared to directly processed samples. The corresponding scRNA-seq files also consistently failed QC, including detectable genes per cell and the percentage of mitochondrial RNA. We excluded these samples from the study. Analysing scATAC-seq data, we observed distinct clusters before and after treatment of RRMM, indicating clonal adaptation or selection in all samples. Treatment with carfilzomib resulted in highly increased co-accessibility and >100 genes were differentially accessible upon treatment. These genes are related to the activation of immune cells (including T-, and B-cells), cell-cell adhesion, apoptosis and signaling pathways (e.g. NFκB) and include several chaperone proteins (e.g. HSPH1) which were upregulated in the scRNA-seq data upon proteasome inhibition. The power of our comprehensive approach for detection of individual subclones and their evolution is exemplarily illustrated in a patient who was treated with a MEK inhibitor and achieved complete remission. This patient showed two main clusters in the scATAC-seq data before treatment, suggesting presence of two subclones. Using copy number profiles based on WGS and scRNA-seq data and performing a trajectory analysis based on scATAC-seq data, we could confirm two different subclones. At relapse, a seemingly independent dominant clone emerged. Upon comprehensive integration of the datasets, one of the initial subclones could be identified as the precursor of this dominant clone. We observed increased accessibility for 108 regions (e.g. JUND, HSPA5, EGR1, FOSB, ETS1, FOXP2) upon MEK inhibition. The most significant differentially accessible region in this clone and its precursor included the gene coding for krüppel-like factor 2 (KLF2). scRNA-seq data showed overexpression of KLF2 in the MEK-inhibitor resistant clone, confirming KLF2 scATAC-seq data. KLF2 has been reported to play an essential role together with KDM3A and IRF1 for MM cell survival and adhesion to stromal cells in the BM. Conclusions: Our data strongly suggest to use only immediately processed samples for single cell technologies. Integrating scATAC- and scRNA-seq together with bulk WGS data showed that detection of individual clones and longitudinal changes in the activity of cis-regulatory regions and gene expression is feasible and informative in RRMM. Disclosures Goldschmidt: John-Hopkins University: Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; John-Hopkins University: Research Funding; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Mundipharma: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; MSD: Research Funding; Molecular Partners: Research Funding; Dietmar-Hopp-Stiftung: Research Funding; Janssen: Consultancy, Research Funding; Chugai: Honoraria, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees.

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