Oncogenic Nras has bimodal effects on stem cells that sustainably increase competitiveness (original) (raw)

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Gene expression data have been deposited to the Gene Expression Omnibus with accession code number GSE45194.

References

  1. Rossi, D. J., Jamieson, C. H. & Weissman, I. L. Stems cells and the pathways to aging and cancer. Cell 132, 681–696 (2008)
    Article CAS Google Scholar
  2. Ward, A. F., Braun, B. S. & Shannon, K. M. Targeting oncogenic Ras signaling in hematologic malignancies. Blood 120, 3397–3406 (2012)
    Article CAS Google Scholar
  3. Essers, M. A. et al. IFNα activates dormant haematopoietic stem cells in vivo. Nature 458, 904–908 (2009)
    Article ADS CAS Google Scholar
  4. Foudi, A. et al. Analysis of histone 2B–GFP retention reveals slowly cycling hematopoietic stem cells. Nature Biotechnol. 27, 84–90 (2009)
    Article CAS Google Scholar
  5. Wilson, A. et al. Hematopoietic stem cells reversibly switch from dormancy to self-renewal during homeostasis and repair. Cell 135, 1118–1129 (2008)
    Article CAS Google Scholar
  6. Rossi, L. et al. Less is more: unveiling the functional core of hematopoietic stem cells through knockout mice. Cell Stem Cell 11, 302–317 (2012)
    Article CAS Google Scholar
  7. Kamminga, L. M. et al. The Polycomb group gene Ezh2 prevents hematopoietic stem cell exhaustion. Blood 107, 2170–2179 (2006)
    Article CAS Google Scholar
  8. Liu, F. et al. Csf3r mutations in mice confer a strong clonal HSC advantage via activation of Stat5. J. Clin. Invest. 118, 946–955 (2008)
    CAS PubMed PubMed Central Google Scholar
  9. Yuan, Y., Shen, H., Franklin, D. S., Scadden, D. T. & Cheng, T. In vivo self-renewing divisions of haematopoietic stem cells are increased in the absence of the early G1-phase inhibitor, p18INK4C. Nature Cell Biol. 6, 436–442 (2004)
    Article CAS Google Scholar
  10. Moran-Crusio, K. et al. Tet2 loss leads to increased hematopoietic stem cell self-renewal and myeloid transformation. Cancer Cell 20, 11–24 (2011)
    Article CAS Google Scholar
  11. Challen, G. A. et al. Dnmt3a is essential for hematopoietic stem cell differentiation. Nature Genet. 44, 23–31 (2012)
    Article CAS Google Scholar
  12. Takizawa, H. et al. Enhanced engraftment of hematopoietic stem/progenitor cells by the transient inhibition of an adaptor protein, Lnk. Blood 107, 2968–2975 (2006)
    Article CAS Google Scholar
  13. Buza-Vidas, N. et al. Cytokines regulate postnatal hematopoietic stem cell expansion: opposing roles of thrombopoietin and LNK. Genes Dev. 20, 2018–2023 (2006)
    Article CAS Google Scholar
  14. Braun, B. S. et al. Somatic activation of oncogenic Kras in hematopoietic cells initiates a rapidly fatal myeloproliferative disorder. Proc. Natl Acad. Sci. USA 101, 597–602 (2004)
    Article ADS CAS Google Scholar
  15. Sabnis, A. J. et al. Oncogenic Kras initiates leukemia in hematopoietic stem cells. PLoS Biol. 7, e59 (2009)
    Article Google Scholar
  16. Li, Q. et al. Hematopoiesis and leukemogenesis in mice expressing oncogenic Nras G12D from the endogenous locus. Blood 117, 2022–2032 (2011)
    Article CAS Google Scholar
  17. Wang, J. et al. Endogenous oncogenic Nras mutation promotes aberrant GM-CSF signaling in granulocytic/monocytic precursors in a murine model of chronic myelomonocytic leukemia. Blood 116, 5991–6002 (2010)
    Article CAS Google Scholar
  18. Zhang, Y., Taylor, B. R., Shannon, K. & Clapp, D. W. Quantitative effects of Nf1 inactivation on in vivo hematopoiesis. J. Clin. Invest. 108, 709–715 (2001)
    Article CAS Google Scholar
  19. Wang, J. et al. Nras G12D/+ promotes leukemogenesis by aberrantly regulating hematopoietic stem cell functions. Blood 121, 5203–5207 (2013)
    Article CAS Google Scholar
  20. Haigis, K. M. et al. Differential effects of oncogenic K-Ras and N-Ras on proliferation, differentiation and tumor progression in the colon. Nature Genet. 40, 600–608 (2008)
    Article CAS Google Scholar
  21. Kiel, M. J., Yilmaz, O. H., Iwashita, T., Terhorst, C. & Morrison, S. J. SLAM family receptors distinguish hematopoietic stem and progenitor cells and reveal endothelial niches for stem cells. Cell 121, 1109–1121 (2005)
    Article CAS Google Scholar
  22. Oguro, H., Ding, L. & Morrison, S. J. SLAM family markers resolve functionally distinct subpopulations of hematopoietic stem cells and multipotent progenitors. Cell Stem Cell 13, 102–116 (2013)
    Article CAS Google Scholar
  23. Krebs, D. L. & Hilton, D. J. SOCS proteins: negative regulators of cytokine signaling. Stem Cells 19, 378–387 (2001)
    Article CAS Google Scholar
  24. Li, L. X., Goetz, C. A., Katerndahl, C. D., Sakaguchi, N. & Farrar, M. A. A. Flt3- and Ras-dependent pathway primes B cell development by inducing a state of IL-7 responsiveness. J. Immunol. 184, 1728–1736 (2010)
    Article CAS Google Scholar
  25. Cui, Y. et al. Inactivation of Stat5 in mouse mammary epithelium during pregnancy reveals distinct functions in cell proliferation, survival, and differentiation. Mol. Cell. Biol. 24, 8037–8047 (2004)
    Article CAS Google Scholar
  26. Itzykson, R. et al. Clonal architecture of chronic myelomonocytic leukemias. Blood 121, 2186–2198 (2013)
    Article CAS Google Scholar
  27. Kotecha, N. et al. Single-cell profiling identifies aberrant STAT5 activation in myeloid malignancies with specific clinical and biologic correlates. Cancer Cell 14, 335–343 (2008)
    Article CAS Google Scholar
  28. Matsuda, K. et al. Spontaneous improvement of hematologic abnormalities in patients having juvenile myelomonocytic leukemia with specific RAS mutations. Blood 109, 5477–5480 (2007)
    Article CAS Google Scholar
  29. De Filippi, P. et al. Germ-line mutation of the NRAS gene may be responsible for the development of juvenile myelomonocytic leukaemia. Br. J. Haematol. 147, 706–709 (2009)
    Article CAS Google Scholar
  30. Kraoua, L. et al. Constitutional NRAS mutations are rare among patients with Noonan syndrome or juvenile myelomonocytic leukemia. Am. J. Med. Genet. A. 158A, 2407–2411 (2012)
    Article Google Scholar
  31. R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org (2009)
  32. Gentleman, R. C. et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 5, R80 (2004)
    Article Google Scholar
  33. Smyth, G. K. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 3, Article3 (2004)
    Article MathSciNet Google Scholar
  34. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005)
    Article ADS CAS Google Scholar

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Acknowledgements

S.J.M. is a Howard Hughes Medical Institute Investigator and the Mary McDermott Cook Chair in Pediatric Genetics. This work was supported by the Cancer Prevention and Research Institute of Texas. Q.L. was supported by NIH K08-CA-134649 and V Foundation V Scholar award. Thanks to L. Hennighausen, K. Haigis and H. Hock for generously providing Stat5ab fl, Nras G12D and Col1A1-H2B-GFP; Rosa26-M2-rtTA mice. Thanks to M. Heeren and K. Rajan for help with genotyping and to R. Coolon and N. Vanderveen for mouse colony management.

Author information

Author notes

  1. Natacha Bohin and Tiffany Wen: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Medicine, University of Michigan, Ann Arbor, 48109, Michigan, USA
    Qing Li, Natacha Bohin, Tiffany Wen & Victor Ng
  2. Department of Pediatrics, Howard Hughes Medical Institute, and Children's Research Institute, University of Texas Southwestern Medical Center, Dallas, 75390, Texas, USA
    Jeffrey Magee & Sean J. Morrison
  3. Department of Pathology, St Jude Children’s Research Hospital, Memphis, 38105, Tennessee, USA
    Shann-Ching Chen
  4. Department of Pediatrics, University of California San Francisco, San Francisco, 94158, California, USA
    Kevin Shannon

Authors

  1. Qing Li
  2. Natacha Bohin
  3. Tiffany Wen
  4. Victor Ng
  5. Jeffrey Magee
  6. Shann-Ching Chen
  7. Kevin Shannon
  8. Sean J. Morrison

Contributions

Q.L. performed most of the experiments. N.B., T.W. and V.N. performed some of the experiments with help from Q.L. J.M. performed the western blot analysis of Pten mutant cells. S.C. performed statistical analysis of microarrays. Q.L., K.S., and S.J.M. conceived the project, designed experiments, interpreted results and wrote the manuscript.

Corresponding authors

Correspondence toQing Li or Sean J. Morrison.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Nras G12D/+ increased HSC proliferation

a, The Nras G12D allele was recombined in all HSCs after 3 doses (every other day) of pIpC. Two weeks after the last dose of pIpC was administered to Mx1-cre; Nras G12D/+ mice, the mice were killed and individual CD150+CD48−LSK HSCs were sorted into methylcellulose cultures in 96-well plates. The cells were cultured for 14 days then DNA was extracted from individual colonies and genotyped by PCR. The size of the recombined Nras G12D allele (G12D) was 550 base pairs (bp) and the Nras+ allele (wild-type, WT) was 500 bp. Nras recombination was observed in 22 out of 22 HSC colonies examined. Blot is representative of three independent experiments. b, Cell cycle analysis of HSCs by pyronin Y and DAPI staining. CD150+CD48−LSK HSCs were sorted from Mx1-cre; Nras G12D/+ mice and littermate controls into 100% ethanol and stained with pyronin Y and DAPI to identify cells in G0 (left lower quadrant), G1 (left upper quadrant) and S/G2/M (right upper and lower quadrants). Data represent mean ± s.d. Statistical analysis was performed with a two-way ANOVA (P < 0.01, n = 4) followed by pairwise post hoc _t_-tests.

Extended Data Figure 2 HSC competitiveness is increased in Vav1-cre; Nras G12D/+ mice.

a, Frequencies of CD150+CD48−LSK HSCs, CD150−CD48−LSK MPPs, and LSK cells in the bone marrow (BM, top) and spleen (SP, bottom) of Vav1-cre; Nras G12D/+ (G12D/+) or littermate control mice (n = 4) at 6–10-weeks of age. b, Donor bone marrow cells (5 × 105) from Vav1-cre; Nras G12D/+ (G12D/+) or littermate control mice at 6–10-weeks of age were transplanted into irradiated recipient mice along with 5 × 105 recipient bone marrow cells (3 donors per genotype were each transplanted into 4 recipients per donor). c, Secondary transplantation of 3 × 106 bone marrow cells from primary recipient mice in Extended Data Fig. 2b at 20 weeks after transplantation (2 primary recipients per genotype were each transplanted into 4 secondary recipients per primary recipient). Data represent mean ± s.d. Two-tailed Student’s _t_-tests were used to assess statistical significance. *P < 0.05, **P < 0.01, ***P < 0.001.

Extended Data Figure 3 HSCs from Mx1-cre; Nras G12D/+ mice were not immortalized.

A fifth round of serial transplantation of 3 × 106 bone marrow cells from the quaternary recipients of Nras G12D/+ (G12D/+) bone marrow cells shown in Fig. 2c showed that the Nras G12D/+ HSCs eventually exhausted all of their HSCs and MPPs and were able to only give low levels of lymphoid reconstitution. Four donor mice from Fig. 2c were transplanted 20 weeks after the fourth round of transplantation into 4 recipients per quaternary donor. The data represent mean ± s.d. for donor blood cells in the myeloid (Gr-1+ or Mac-1+ cells), B (B220+), and T (CD3+) cell lineages.

Extended Data Figure 4 Nras G12D (G12D/+) expression increased the reconstituting potential of CD150−CD48−LSK MPPs but did not affect the reconstituting potential of CD150+CD48+LSK, or CD150−CD48+LSK progenitors in irradiated mice.

a–c, Ten donor MPPs (a), 25 CD150+CD48+LSK progenitors (b), or 100 CD150-CD48+LSK progenitors (c) from Mx1-cre; Nras G12D/+ (G12D/+) or littermate control mice at 2 weeks after pIpC treatment were transplanted into irradiated recipient mice along with 3 × 105 recipient bone marrow cells. Data represent mean ± s.d. for donor blood cells in the myeloid (Gr-1+ or Mac-1+ cells), B (B220+) and T (CD3+) cell lineages. Two-tailed Student’s _t_-tests were used to assess statistical significance. None of the time points were significantly different between treatments. The data represent two independent experiments with 4 recipient mice per donor.

Extended Data Figure 5 Nras _G12D_-induced changes in HSC function were not associated with the development of leukaemia.

ad, White blood counts (WBC), hemoglobulin (Hb) levels, platelet counts and spleen masses for recipient mice from primary transplants (a, from Fig. 1d), secondary transplants (b, from Fig. 2a), tertiary transplants (c, from Fig. 2b) and quaternary transplants (d, from Fig. 2c). In all cases, these blood cell counts were collected from mice after the analysis of blood cell reconstitution was complete (at least 20 weeks after transplantation). The transplanted mice were observed for a median time of 260 (162–315) days for primary recipient mice, 194 (122–264) days for secondary recipient mice, 224 (176–336) days for tertiary recipient mice, and 280 (279–280) days for quaternary recipient mice. We never observed evidence of leukaemia or MPN by histology in these mice. Across all of the experiments, only two recipients of Nras G12D/+ cells and two recipients of control cells died spontaneously. Data represent mean ± s.d. Two-tailed Student’s _t_-tests were used to assess statistical significance and none of the comparisons showed significant difference.

Extended Data Figure 6 Nras G12D/+ had a bimodal effect on HSC cycling but increased the rate at which MPPs divide.

a, Flow cytometric analysis of GFP expression in whole bone marrow cells from Nras G12D/+ or littermate control mice after 12 weeks of chase without doxycycline. b, Median GFP fluorescence intensity of H2B–GFP−, H2B–GFPlo and H2B–GFPhi HSCs from wild type and Nras G12D/+ mice (n = 8 mice per genotype). GFP levels in control HSCs were set to one for comparison to relative levels in Nras G12D/+ HSCs. c, Nras G12D increased the rate of division by MPPs. Flow cytometric analysis of GFP expression in CD150−CD48−LSK MPPs from Mx1-cre; Nras G12D/+ ; Col1A1-H2B–GFP; Rosa26-M2-rtTA mice (G12D/+) and littermate controls (con) after 12 weeks of chase (n = 8 mice per genotype). Relative to control MPPs, Nras G12D/+ MPPs included significantly more H2B–GFP− frequently cycling cells and significantly fewer H2B–GFPlo MPPs (P < 0.05 by two-way ANOVA and post hoc pairwise _t_-tests). d, We continuously administered BrdU to Mx1-cre; Nras G12D/+ versus control mice for 1 to 30 days and determined the frequency of BrdU+ HSCs (1 day BrdU data are from Fig. 1a). Data represent mean ± s.d. Two-tailed Student’s _t_-tests were used to assess statistical significance unless stated otherwise. *P < 0.05, **P < 0.01, ***P < 0.001.

Extended Data Figure 7 Gene expression profiling demonstrates different transcriptional responses to Nras activation in quiescent as compared to frequently dividing HSCs.

a, CD150+CD48−LSK HSCs and CD150−CD48−LSK MPPs were isolated from three pairs of Mx1-cre; Nras G12D/+ and littermate controls and gene expression profiling was performed with Affymetrix mouse genome 430 2.0 microarrays. The Venn diagram shows the number of genes that were differentially expressed between Nras G12D/+ and controls cells within each cell population (fold change ≥ 2). b, Venn diagram of genes that were differentially expressed between Nras G12D/+ and control GFP− HSCs and GFPhi HSCs isolated from 3 pairs of Mx1-cre; Nras G12D/+; Col1A1-H2B–GFP; Rosa26-M2-rtTA mice and littermate controls (fold change ≥ and P value ≤ 0.05). c, Genes that were consistently increased or decreased in expression in response to Nras activation in HSCs, MPPs, GFP− HSCs and GFPhi HSCs (fold change ≥ 2 and P ≤ 0.05 in each cell population). d–f, Gene set enrichment analysis (GSEA) of cell cycle genes (d), DNA replication genes (e) and RNA polymerase genes (f).

Extended Data Figure 8 Nras activation increases STAT5 phosphorylation.

a, Western blot for phosphorylated ERK (pERK) in LSK stem/progenitor cells, Lin−c-kit+Sca1− progenitor cells, or whole bone marrow (WBM) cells from Mx1-cre; Nras G12D/+ (G12D/+) mice, Mx1-cre; Nras G12D/G12D (G12D/G12D) mice, or littermate controls 2 weeks after pIpC treatment. b, Western blot of pERK and total ERK in 106 uncultured splenocytes from Mx1-cre; Nras G12D/+ (G12D/+) or control mice after 8 days of treatment with PD0325901 MEK inhibitor or vehicle (blot is representative of four independent experiments). c, The frequency of BrdU+ CD150+CD48−LSK HSCs after a 24-h pulse of BrdU to Mx1-cre; Nras G12D/+ (G12D/+) or control mice after 7 days of PD0325901 MEK inhibitor or vehicle (mean ± s.d. from four experiments). d, Western blot of pERK and total ERK in 106 uncultured bone marrow cells from Mx1-cre; Nras G12D/+ (G12D/+) or control mice after 8 days of AZD6244 MEK inhibitor or vehicle (blot is representative of four independent experiments). e, The frequency of BrdU+ CD150+CD48−LSK HSCs after a 24-h pulse of BrdU to Mx1-cre; Nras G12D/+ (G12D/+) or control mice after 7 days of AZD6244 MEK inhibitor or vehicle (mean ± s.d. from four experiments). f, Western blot for phosphorylated Akt (pAkt) in CD48−LSK HSCs and MPPs, CD48+LSK progenitors, or WBM cells from Mx1-cre; Nras G12D/+ (G12D/+) mice, Mx1-cre; Pten fl/fl (Pten −/−) mice, or littermate controls 2 weeks after pIpC treatment. g, Socs2 transcript levels in HSCs and MPPs from Mx1-cre; Nras G12D/+ (G12D/+) or control mice by microarray analysis (top, n = 3) and qRT–PCR (bottom, n = 7). h, i, Socs2 transcript levels in GFP− and GFPhi HSCs from Mx1-cre; Nras G12D/+ ; Col1A1-H2B–GFP; Rosa26-M2-rtTA mice and littermate controls by microarray (h, n = 3) and qRT–PCR (i, n = 3). j, Western blotting showed that pSTAT5 levels were significantly increased in CD48−LSK HSCs and MPPs from Mx1-cre; Nras G12D/+ mice as compared to control mice. Left panel shows western blots of pSTAT5 and total STAT5 from two independent experiments. Right panel shows quantification of pSTAT5 levels from western blots from three independent experiments (signals were quantitated using NIH ImageJ software). Blot 1 was shown in Fig. 4e. k, Western blot showing that STAT5 levels were reduced in CD48-LSK HSCs/MPPs from Mx1-cre; Stat5ab −/+ or Mx1-cre; Nras G12D/+ ; Stat5a -−/+ mice as compared to control and Mx1-cre; Nras G12D/+ mice (blot is representative of four independent experiments). l, BrdU incorporation into common myeloid progenitors (CMPs; Lin−Sca1−c-kit+CD34+CD16/32−), granulocyte macrophage progenitors (GMPs; Lin−Sca1−c-kit+CD34+CD16/32+), and megakaryocyte erythroid progenitors (MEPs; Lin−Sca1−c-kit+CD34−CD16/32−) from control, Mx1-cre; Stat5a −/+, Mx1-cre; Nras G12D/+, or Mx1-cre; Nras G12D/+ ; Stat5ab −/+ mice after a 2.5-h pulse of BrdU (n = 4 mice per treatment). Data represent mean ± s.d. Two-tailed Student’s _t_-tests were used to assess statistical significance.

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Li, Q., Bohin, N., Wen, T. et al. Oncogenic Nras has bimodal effects on stem cells that sustainably increase competitiveness.Nature 504, 143–147 (2013). https://doi.org/10.1038/nature12830

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