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Dual targeting of p53 and c-MYC selectively eliminates leukaemic stem cells

Nature volume 534, pages 341–346 (2016)Cite this article

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Abstract

Chronic myeloid leukaemia (CML) arises after transformation of a haemopoietic stem cell (HSC) by the protein-tyrosine kinase BCR–ABL. Direct inhibition of BCR–ABL kinase has revolutionized disease management, but fails to eradicate leukaemic stem cells (LSCs), which maintain CML. LSCs are independent of BCR–ABL for survival, providing a rationale for identifying and targeting kinase-independent pathways. Here we show—using proteomics, transcriptomics and network analyses—that in human LSCs, aberrantly expressed proteins, in both imatinib-responder and non-responder patients, are modulated in concert with p53 (also known as TP53) and c-MYC regulation. Perturbation of both p53 and c-MYC, and not BCR–ABL itself, leads to synergistic cell kill, differentiation, and near elimination of transplantable human LSCs in mice, while sparing normal HSCs. This unbiased systems approach targeting connected nodes exemplifies a novel precision medicine strategy providing evidence that LSCs can be eradicated.

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Figure 1: p53 and c-MYC network in CML regulation.
Figure 2: Validation of proteomic network.
Figure 3: Modulation of p53 and c-MYC demonstrates CML sensitivity.
Figure 4: p53 and c-MYC abrogation in normal and primitive CML cells.
Figure 5: Mechanism and clinical relevance of treatment.
Figure 6: Targeting p53 and c-MYC in CML elicits synergistic kill in BCR–ABL+ LSCs.

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Primary accessions

European Nucleotide Archive

Gene Expression Omnibus

Data deposits

The CML and normal CD34+ mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001502, PXD001503, PXD001504; SCOPE3/SCOPE4 data are also available using PXD001505 and PXD002782 respectively. Transcriptomic data are publicly available via the accession codes E-MTAB-2581, E-MTAB-2508, E-MIMR-17 at ArrayExpress (https://www.ebi.ac.uk/arrayexpress/) and GSE47927, GSE5550, GSE24739, GSE14671 at GEO (http://www.ncbi.nlm.nih.gov/geo/). RNA-seq data (fastq) have been deposited in the European Nucleotide Archive under accession number PRJEB9942.

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Acknowledgements

We thank all CML patients and UK haematology departments who contributed samples; A. Hair for sample processing; J. Cassels for cell sorting; A. Michie and V. Helgason for assisting with the in vivo research and providing cord blood samples; C. Wells, P. Bailey and J. Cole for discussions regarding the RNA-seq analysis. We acknowledge the Cancer Research UK (CR-UK) Glasgow Centre (C596/A18076) and the CR-UK Beatson Institute (C596/A17196) for providing animal care and housing facilities. We acknowledge Constellation Pharmaceuticals for providing CPI-203, CPI-0610 and part funding M.E.D., Roche for providing RG7112, RG7388 and part funding M.E.D. and the SPIRIT Trials Management Group for access to CML samples. This study was supported by the Glasgow and Manchester Experimental Cancer Medicine Centres (ECMC), which are funded by CR-UK and the Chief Scientist’s Office (Scotland). We acknowledge the funders who have contributed to this work: MRC stratified medicine infrastructure award (A.D.W.), CR-UK C11074/A11008 (F.P., L.E.M.H., T.L.H., A.D.W.); LLR08071 (S.A.A., E.C.); LLR11017 (M.C.); SCD/04 (M.C.); LLR13035 (S.A.A., K.D., A.D.W. and A.P.); LLR14005 (M.T.S., D.V.); KKL690 (L.E.P.); KKL698 (P.B.); LLR08004 (A.D.W., A.P. and A.J.W.); MRC CiC (M.E.D.); The Howat Foundation (fluorescence-activated cell sorting (FACS) support); Friends of Paul O’Gorman (K.D. and FACS support); ELF 67954 (S.A.A.); British Society for Haematology start-up fund (S.A.A.); MR/K014854/1 (K.D.).

Author information

Author notes

  1. Sheela A. Abraham, Lisa E. M. Hopcroft and Anthony D. Whetton: These authors contributed equally to this work.

Authors and Affiliations

  1. Paul O’Gorman Leukaemia Research Centre, Institute of Cancer Sciences, University of Glasgow, Gartnavel General Hospital, 1053 Great Western Road, Glasgow, G12 0YN, UK

    Sheela A. Abraham, Lisa E. M. Hopcroft, Mark E. Drotar, Karen Dunn, Koorosh Korfi, Laura E. Park, Mary T. Scott, Francesca Pellicano, Mhairi Copland & Tessa L. Holyoake

  2. Stem Cell and Leukaemia Proteomics laboratory, University of Manchester, Manchester, M20 3LJ, UK

    Emma Carrick, Andrew J. K. Williamson, Andrew Pierce & Anthony D. Whetton

  3. Manchester Precision Medicine Institute, University of Manchester, Manchester, M20 3LJ, UK

    Emma Carrick, Andrew J. K. Williamson, Andrew Pierce & Anthony D. Whetton

  4. Institute of Cancer Sciences, University of Glasgow, Garscube Estate, G61 1QH, Glasgow, UK

    Koorosh Korfi, Pablo Baquero, Craig Nourse & David Vetrie

  5. University of Melbourne Centre for Cancer Research, University of Melbourne, Victoria, 3010,, Australia

    Sean M. Grimmond

  6. Stoller Biomarker Discovery Centre, University of Manchester, Manchester, M20 3LJ, UK

    Anthony D. Whetton

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  1. Sheela A. Abraham
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Contributions

A.D.W. and T.L.H. supervised the entire study and research. S.A.A., L.E.M.H., A.D.W. and T.L.H. designed the research, analysed and interpreted data, and wrote the manuscript. S.A.A. conceived the hypothesis, supervised in vivo research, prepared samples for proteomic and RNA-seq, performed all in vitro work including western blotting, immunofluorescence, cloning and knockdown studies, clonogenic studies, flow cytometry and all mouse in vivo studies including tissue processing-FISH preparation and slide interpretation, engraftment determination and analysis of primitive stem cell subsets. L.E.M.H. designed and performed all in silico work including global omics handling, integration and analysis (MS, RNA-seq and microarray data); network analyses; correlation/MI calculations; functional enrichment analyses and permutation experiments for calculation of P values. E.C. performed proteomic work. A.J.K.W. performed proteomic work and generated relative proteomic quantification. M.E.D. performed virus preparation, prepared drugs for in vivo work and assisted with in vivo studies. K.D. provided maintenance and care for all mouse colonies and assisted with in vivo work. P.B. and L.E.P. provided assistance with in vivo studies and D-FISH preparation. F.P. and M.T.S. provided assistance with in vivo studies. D.V. provided analysed datasets and analysed/interpreted RNA-seq data. S.M.G. supervised and interpreted RNA-seq. C.N. performed RNA-seq experiments. K.K. and M.C. provided analysed datasets. A.P. supervised proteomic studies. All authors reviewed/edited the manuscript.

Corresponding author

Correspondence to Tessa L. Holyoake.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 BCR–ABL drives a proteomic signature mediated by p53 and c-MYC.

a, b, Equivalent to Fig. 1b, c with additional information regarding the correlations calculated from the complete list of 58 candidate proteins (rc) in addition to the correlations for the candidate network (rn) and the background (r0). Also shown is the gain in r2 obtained for the candidate network as compared to the r2 obtained for the candidate list as a whole (r2Δ). FDR calculated from 10,000 re-samplings. c, Expression changes of the network components (shown as bar plots) in the context of quiescent and primitive CML cells; data shown in each panel (left to right) are (1) CD34+ protein log2 ratios (n = 3 patient samples, n = 2 normal samples); (2) CD34+HstloPylo transcript logFC (ArrayExpress accession E-MTAB-2508); (3) CD34+HstloPylo transcript logFC (GEO accession GSE24739); (4) CD34+CD38− logFC (ArrayExpress accession E-MTAB-2581); and (5) Lin−CD34+CD38−CD90+ logFC (GEO accession GSE47927). Down-/upregulation is indicated by turquoise/red, respectively. Where multiple probesets were found for individual genes, the probeset corresponding to the maximal log ratio was selected. d, e, Correlation of the candidate network in progenitor (CD34+) CML cells: CD34+CD38+ progenitor (top); common myeloid progenitor Lin−CD34+CD38+CD123+CD45RA− (middle); and CD34+ cells (bottom). As in a, b, correlations for the background (r0), candidate list (58 proteins, rc) and candidate network (Fig. 1a, rn) are shown. Also shown is the gain in r2 obtained for the candidate network as compared to the r2 obtained for the candidate list as a whole (r2Δ). FDR calculated from 10,000 re-samplings; MI statistics corresponding to FDRs < 0.05 are coloured red, FDRs < 0.10 are coloured grey. f, A Venn diagram showing the overlap in protein identification of the three MS instruments: ABSciex Q-STAR Elite (Elite), Thermo LTQ Orbitrap Velos (Orbi) and ABSciex TripleTOF 5600 (5600).

Source data

Extended Data Figure 2 Validation of network candidates.

a, HDM2 and c-MYC knockdown using shRNA constructs. Western blots of c-MYC, HDM2, p53 and HSP90 in HeLa cells transduced with lentiviral constructs specific for either c-MYC (2 constructs), HDM2 (2 constructs) or scrambled control (1 construct). KD, knockdown. b, c, CML CD34+ cells were transduced with either lentiviral (GFP) shRNA constructs to HDM2 (constructs 1, 2), c-MYC (constructs 1, 2) or scramble control (1 construct). b, Transduced viable GFP+ cells (assessed as annexin-V−/DAPI−/GFP+ percentages multiplied by the absolute cell count) are presented as a percentage of CML CD34+ cells transduced with scramble control (n = 3 patient samples). c, Early apoptosis levels (assessed as annexin-V+/DAPI−/GFP+) after transduction of CML CD34+ cells (n = 3 patient samples) as described in b. Statistical significance was calculated by a two-tailed Student’s t-test and error bars represent the s.e.m.

Source data

Extended Data Figure 3 RITA and CPI-203 synergize to eliminate CML CD34+ cells.

a, b, Western blots of CML CD34+ cells untreated or treated with 50 nM RITA; 1 μM CPI-203; or the combination of 50 nM RITA and 1 μM CPI-203 or 150 nM Das for 8 h (a) and 48 h (b). c, p53 (red, nucleus in blue) 24 h after treatment in CML CD34+ cells. d, RITA, CPI-203 and combination drug treatment eliminates CD34+ CML cells through mechanisms probably dependent on apoptosis; after 72 h of drug treatment apoptosis levels were assessed (annexin V/DAPI) using flow cytometry techniques. e, RITA or Nut cannot induce death of K562 cells that lack p53. K562 cells were treated with either 50 μM RITA or 10 μM Nut and after 72 h of drug treatment, apoptosis levels were assessed (annexin V/DAPI) using flow cytometry techniques.

Extended Data Figure 4 RITA and CPI-203 synergize to eliminate CML cells.

a, CD34+ CML cells were treated with Nut and CPI-203 for 72 h with apoptosis levels assessed (annexin V/DAPI) using flow cytometry techniques. b, Treatment of CD34+ CML cells with Nut results in the elimination of early and late progenitor cells as assessed by the functional colony-forming capacity of drug-treated CML cells. c, Sequential drug treatments (n = 3 patient samples; drug one for 24 h, then both for 48 h). d, Sequential knockdown treatments (n = 3 patient samples; knockdown one for 24 h, then both for 48 h), mean ± s.e.m. (P values: two-tailed Student’s t-test; *P < 0.05, **P < 0.01, ***P < 0.001). e, CML CD34+ primary samples were pre-treated or not with imatinib mesylate (1 μM) for 8 h followed by RITA (50 nM), CPI-203 (1 μM) or the combined treatment (RITA plus CPI-203) for 72 h (right three columns). Cell counts were obtained using trypan blue exclusion.

Source data

Extended Data Figure 5 RITA and CPI-203 selectively eliminate LSCs.

a, b, Viable cell counts (n = 3 patient samples) (a); apoptosis in normal CD34+ cells (n = 3 patient samples) in response to RITA and/or CPI-203 (b). c, Gated CML CD34+CD38− cells 72 h after treatment (n = 4 patient samples). d, Ex vivo protocol for CML/cord blood CD34+ cells in NSG mice (n = 5 mice per arm). e, f, Targeting p53 and c-MYC in CML eliminates NSG repopulating leukaemic stem cells. CML CD34+ cells were treated with RITA (70 nM) and/or CPI-203 (1 μM) or Das (150 nM) for 48 h and recovered cells were injected intravenously into 8–12-week-old, sublethally irradiated (2.5 Gy) NSG mice (2–4 mice per arm). e, Percentage of human CD45+ cell levels in peripheral blood (PB) at 8, 12 and 16 weeks. f, Percentages of human CD45+, CD34+, CD33+, CD11b+, CD19+ and CD14+ cells in the bone marrow at 16 weeks. g, CML bone marrow analyses of CD33, CD11b, CD19 and CD14 from a CML sample determined to engraft both BCR–ABL-positive and -negative cells. h, D-FISH analyses of bone marrow human engraftment studies shown in g performed twice (2 patient samples) with a minimum of n = 6 mice per arm; mean ± s.e.m. (P values: two-tailed Student’s t-test; *P < 0.05, **P < 0.01, ***P < 0.001).

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Extended Data Figure 6 Mechanism of LSC elimination and clinical scope.

a, Enrichment of p53 (top); apoptosis (second from top); c-MYC (second from bottom); and differentiation MSigDB signatures (bottom) in the four treatment arms (n = 3 CML patient samples per arm) (columns named as per b). Equivalent to Fig. 5b, but with named MSigDB signatures. b, Enrichment of PANTHER pathways in the four treatment arms. Pathway enrichment calculated from the top 1,500 genes, as ranked by increasing P value (top); only those genes exhibiting an absolute FC of >0.5 in each arm (bottom left); only those genes exhibiting a P < 0.05 each arm (bottom right). c, Assessing molecular synergy of the combined RITA plus CPI-203 treatment, as compared to the individual RITA and CPI-203 arms of the RNA-seq experiments in the three in silico functional signatures: p53/apoptosis (left); c-MYC (middle); and differentiation (right). Mean expression is shown as a solid line.

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Extended Data Figure 7 Mechanism of LSC elimination and clinical scope continued.

a, Gene expression patterns (logFC, n = 3 patient samples per arm) shown for the members of the three broad signatures identified in silico: p53/apoptosis (left); c-MYC (middle); and differentiation (right) (*q < 0.05); data are ordered by increasing logFC in response to combination treatment, from downregulation at the top to upregulation at the bottom. Corresponding expression data are provided in Supplementary Tables 5–7. b, Differential expression of CD34 and CD133 (markers of stemness) in the four arms of the RNA-seq experiment. c, Apoptosis levels assessed (annexin V+/DAPI) using flow cytometry on a TKI-NR CD34+ sample after 72 h treatment with RITA and CPI-203 as indicated.

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Extended Data Figure 8 RG7112 and CPI-0610 as a combination decrease BCR–ABL+ cells.

a, b, DTG mice in vivo treatment (a): neutrophils normalized to control (dotted line) (b). c, Bone marrow cells stained for CD45.1/2. Drug treatment arms (minimum of n = 7 mice) mean ± s.e.m. (P values: two-tailed Student’s t-test; *P < 0.05, **P < 0.01, ***P < 0.001).

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Supplementary information

Supplementary Information

This file contains the raw data for Figure 2a and Extended Data Figures 2a, 3a, 3b, Supplementary Tables 1, 3, 4, 8 and legends for Supplementary Tables 2, 5, 6 and 7 (see separate excel files). (PDF 672 kb)

Supplementary Table 2

This file contains the candidate network statistics (see Supplementary Information file for legend). (XLSX 11 kb)

Supplementary Table 5

This file shows the molecular deregulation of P53/apoptosis-related signatures and pathways (see Supplementary Information file for legend). (XLSX 35 kb)

Supplementary Table 6

This file shows the molecular deregulation of MYC-related signatures and pathways (see Supplementary Information file for legend). (XLSX 13 kb)

Supplementary Table 7

This file shows the molecular deregulation of differentiation-related signatures and pathways (see Supplementary Information file for legend). (XLSX 11 kb)

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Abraham, S., Hopcroft, L., Carrick, E. et al. Dual targeting of p53 and c-MYC selectively eliminates leukaemic stem cells. Nature 534, 341–346 (2016). https://doi.org/10.1038/nature18288

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