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Antagonism of B cell enhancer networks by STAT5 drives leukemia and poor patient survival

Nature Immunology volume 18, pages 694–704 (2017)Cite this article

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Abstract

The transcription factor STAT5 has a critical role in B cell acute lymphoblastic leukemia (B-ALL). How STAT5 mediates this effect is unclear. Here we found that activation of STAT5 worked together with defects in signaling components of the precursor to the B cell antigen receptor (pre-BCR), including defects in BLNK, BTK, PKCβ, NF-κB1 and IKAROS, to initiate B-ALL. STAT5 antagonized the transcription factors NF-κB and IKAROS by opposing regulation of shared target genes. Super-enhancers showed enrichment for STAT5 binding and were associated with an opposing network of transcription factors, including PAX5, EBF1, PU.1, IRF4 and IKAROS. Patients with a high ratio of active STAT5 to NF-κB or IKAROS had more-aggressive disease. Our studies indicate that an imbalance of two opposing transcriptional programs drives B-ALL and suggest that restoring the balance of these pathways might inhibit B-ALL.

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Figure 1: Stat5b-CA drives pre-B leukemia.
Figure 2: Activation of STAT5 acts in synergy with pre-BCR signaling defects to deregulate the expression of NF-κB target genes.
Figure 3: NF-κB1 acts as a tumor suppressor to prevent STAT5b-CA-driven leukemia.
Figure 4: STAT5 antagonizes IKAROS and disrupts B cell super-enhancer networks.
Figure 5: STAT5 binds to several super-enhancers in progenitor B cells and opposes regulation of the Myc locus by IKAROS.
Figure 6: Binding of STAT5 overlaps that of NF-κB and IKAROS and correlates with super-enhancer function in human B lymphoblastoid cells.
Figure 7: Activation of STAT5 paired with loss of IKZF1 or NF-κB correlates with survival in patients with B-ALL.

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References

  1. Pui, C.H., Gajjar, A.J., Kane, J.R., Qaddoumi, I.A. & Pappo, A.S. Challenging issues in pediatric oncology. Nat. Rev. Clin. Oncol. 8, 540–549 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Inaba, H., Greaves, M. & Mullighan, C.G. Acute lymphoblastic leukaemia. Lancet 381, 1943–1955 (2013).

    Article  PubMed  Google Scholar 

  3. Pui, C.H. et al. Treating childhood acute lymphoblastic leukemia without cranial irradiation. N. Engl. J. Med. 360, 2730–2741 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Bhatia, S. et al. Low incidence of second neoplasms among children diagnosed with acute lymphoblastic leukemia after 1983. Blood 99, 4257–4264 (2002).

    Article  CAS  PubMed  Google Scholar 

  5. Downing, J.R. et al. The Pediatric Cancer Genome Project. Nat. Genet. 44, 619–622 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Conter, V. et al. Molecular response to treatment redefines all prognostic factors in children and adolescents with B-cell precursor acute lymphoblastic leukemia: results in 3184 patients of the AIEOP-BFM ALL 2000 study. Blood 115, 3206–3214 (2010).

    Article  CAS  PubMed  Google Scholar 

  7. Heltemes-Harris, L.M. & Farrar, M.A. The role of STAT5 in lymphocyte development and transformation. Curr. Opin. Immunol. 24, 146–152 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Hoelbl, A. et al. Clarifying the role of Stat5 in lymphoid development and Abelson-induced transformation. Blood 107, 4898–4906 (2006).

    Article  CAS  PubMed  Google Scholar 

  9. Hoelbl, A. et al. Stat5 is indispensable for the maintenance of bcr/abl-positive leukaemia. EMBO Mol. Med. 2, 98–110 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Schwaller, J. et al. Stat5 is essential for the myelo- and lymphoproliferative disease induced by TEL/JAK2. Mol. Cell 6, 693–704 (2000).

    Article  CAS  PubMed  Google Scholar 

  11. Malin, S., McManus, S. & Busslinger, M. STAT5 in B cell development and leukemia. Curr. Opin. Immunol. 22, 168–176 (2010).

    Article  CAS  PubMed  Google Scholar 

  12. Malin, S. et al. Role of STAT5 in controlling cell survival and immunoglobulin gene recombination during pro-B cell development. Nat. Immunol. 11, 171–179 (2010).

    Article  CAS  PubMed  Google Scholar 

  13. Nakayama, J. et al. BLNK suppresses pre-B-cell leukemogenesis through inhibition of JAK3. Blood 113, 1483–1492 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Mullighan, C.G. et al. Genome-wide analysis of genetic alterations in acute lymphoblastic leukaemia. Nature 446, 758–764 (2007).

    Article  CAS  PubMed  Google Scholar 

  15. Nutt, S.L. & Kee, B.L. The transcriptional regulation of B cell lineage commitment. Immunity 26, 715–725 (2007).

    Article  CAS  PubMed  Google Scholar 

  16. Heltemes-Harris, L.M. et al. Ebf1 or Pax5 haploinsufficiency synergizes with STAT5 activation to initiate acute lymphoblastic leukemia. J. Exp. Med. 208, 1135–1149 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Burchill, M.A. et al. Distinct effects of STAT5 activation on CD4+ and CD8+ T cell homeostasis: development of CD4+CD25+ regulatory T cells versus CD8+ memory T cells. J. Immunol. 171, 5853–5864 (2003).

    Article  CAS  PubMed  Google Scholar 

  18. Richards, N.G. & Kilberg, M.S. Asparagine synthetase chemotherapy. Annu. Rev. Biochem. 75, 629–654 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Parker, M.J. et al. The pre-B-cell receptor induces silencing of VpreB and λ5 transcription. EMBO J. 24, 3895–3905 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Fang, W. et al. Frequent aberrant immunoglobulin gene rearrangements in pro-B cells revealed by a bcl-xL transgene. Immunity 4, 291–299 (1996).

    Article  CAS  PubMed  Google Scholar 

  21. Goetz, C.A., Harmon, I.R., O'Neil, J.J., Burchill, M.A. & Farrar, M.A. STAT5 activation underlies IL7 receptor-dependent B cell development. J. Immunol. 172, 4770–4778 (2004).

    Article  CAS  PubMed  Google Scholar 

  22. Saijo, K. et al. Essential role of Src-family protein tyrosine kinases in NF-κB activation during B cell development. Nat. Immunol. 4, 274–279 (2003).

    Article  CAS  PubMed  Google Scholar 

  23. McMurray, H.R. et al. Synergistic response to oncogenic mutations defines gene class critical to cancer phenotype. Nature 453, 1112–1116 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Wang, S. et al. Target analysis by integration of transcriptome and ChIP-seq data with BETA. Nat. Protoc. 8, 2502–2515 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Ma, S., Pathak, S., Trinh, L. & Lu, R. Interferon regulatory factors 4 and 8 induce the expression of Ikaros and Aiolos to down-regulate pre-B-cell receptor and promote cell-cycle withdrawal in pre-B-cell development. Blood 111, 1396–1403 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Grumont, R.J. & Gerondakis, S. Rel induces interferon regulatory factor 4 (IRF-4) expression in lymphocytes: modulation of interferon-regulated gene expression by rel/nuclear factor κB. J. Exp. Med. 191, 1281–1292 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Mullighan, C.G. et al. BCR-ABL1 lymphoblastic leukaemia is characterized by the deletion of Ikaros. Nature 453, 110–114 (2008).

    Article  CAS  PubMed  Google Scholar 

  28. Mullighan, C.G. et al. Deletion of IKZF1 and prognosis in acute lymphoblastic leukemia. N. Engl. J. Med. 360, 470–480 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Kuiper, R.P. et al. IKZF1 deletions predict relapse in uniformly treated pediatric precursor B-ALL. Leukemia 24, 1258–1264 (2010).

    Article  CAS  PubMed  Google Scholar 

  30. Ferreiros-Vidal, I. et al. Genome-wide identification of Ikaros targets elucidates its contribution to mouse B-cell lineage specification and pre-B-cell differentiation. Blood 121, 1769–1782 (2013).

    Article  CAS  PubMed  Google Scholar 

  31. Matsumoto, A. et al. CIS, a cytokine inducible SH2 protein, is a target of the JAK-STAT5 pathway and modulates STAT5 activation. Blood 89, 3148–3154 (1997).

    Article  CAS  PubMed  Google Scholar 

  32. Shi, J. et al. Role of SWI/SNF in acute leukemia maintenance and enhancer-mediated Myc regulation. Genes Dev. 27, 2648–2662 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Pfitzner, E., Jahne, R., Wissler, M., Stoecklin, E. & Groner, B. p300/CREB-binding protein enhances the prolactin-mediated transcriptional induction through direct interaction with the transactivation domain of Stat5, but does not participate in the Stat5-mediated suppression of the glucocorticoid response. Mol. Endocrinol. 12, 1582–1593 (1998).

    Article  CAS  PubMed  Google Scholar 

  34. Kim, J. et al. Ikaros DNA-binding proteins direct formation of chromatin remodeling complexes in lymphocytes. Immunity 10, 345–355 (1999).

    Article  CAS  PubMed  Google Scholar 

  35. Heltemes-Harris, L.M. et al. Sleeping Beauty transposon screen identifies signaling modules that cooperate with STAT5 activation to induce B-cell acute lymphoblastic leukemia. Oncogene 35, 3454–3464 (2016).

    Article  CAS  PubMed  Google Scholar 

  36. Schwickert, T.A. et al. Stage-specific control of early B cell development by the transcription factor Ikaros. Nat. Immunol. 15, 283–293 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Revilla, I.D.R. et al. The B-cell identity factor Pax5 regulates distinct transcriptional programmes in early and late B lymphopoiesis. EMBO J. 31, 3130–3146 (2012).

    Article  CAS  Google Scholar 

  38. Vilagos, B. et al. Essential role of EBF1 in the generation and function of distinct mature B cell types. J. Exp. Med. 209, 775–792 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Whyte, W.A. et al. Master transcription factors and mediator establish super-enhancers at key cell identity genes. Cell 153, 307–319 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Loven, J. et al. Selective inhibition of tumor oncogenes by disruption of super-enhancers. Cell 153, 320–334 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Vahedi, G. et al. Super-enhancers delineate disease-associated regulatory nodes in T cells. Nature 520, 558–562 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Rayet, B. & Gelinas, C. Aberrant rel/nfkb genes and activity in human cancer. Oncogene 18, 6938–6947 (1999).

    Article  CAS  PubMed  Google Scholar 

  43. Nagel, D., Vincendeau, M., Eitelhuber, A.C. & Krappmann, D. Mechanisms and consequences of constitutive NF-κB activation in B-cell lymphoid malignancies. Oncogene 33, 5655–5665 (2014).

    Article  CAS  PubMed  Google Scholar 

  44. Kordes, U., Krappmann, D., Heissmeyer, V., Ludwig, W.D. & Scheidereit, C. Transcription factor NF-κB is constitutively activated in acute lymphoblastic leukemia cells. Leukemia 14, 399–402 (2000).

    Article  CAS  PubMed  Google Scholar 

  45. Pinz, S., Unser, S. & Rascle, A. Signal transducer and activator of transcription STAT5 is recruited to c-Myc super-enhancer. BMC Mol. Biol. 17, 10 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Sha, W.C., Liou, H.C., Tuomanen, E.I. & Baltimore, D. Targeted disruption of the p50 subunit of NF-κB leads to multifocal defects in immune responses. Cell 80, 321–330 (1995).

    Article  CAS  PubMed  Google Scholar 

  47. Leitges, M. et al. Immunodeficiency in protein kinase cb-deficient mice. Science 273, 788–791 (1996).

    Article  CAS  PubMed  Google Scholar 

  48. Khan, W.N. et al. Defective B cell development and function in Btk-deficient mice. Immunity 3, 283–299 (1995).

    Article  CAS  PubMed  Google Scholar 

  49. Livak, K.J. & Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(−ΔΔC(T)) method. Methods 25, 402–408 (2001).

    Article  CAS  PubMed  Google Scholar 

  50. Schjerven, H. et al. Selective regulation of lymphopoiesis and leukemogenesis by individual zinc fingers of Ikaros. Nat. Immunol. 14, 1073–1083 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Mahmud, S.A. et al. Costimulation via the tumor-necrosis factor receptor superfamily couples TCR signal strength to the thymic differentiation of regulatory T cells. Nat. Immunol. 15, 473–481 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Kornblau, S.M. et al. Functional proteomic profiling of AML predicts response and survival. Blood 113, 154–164 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank A. Vegoe, R. Agneberg, J. Bednar, C. Anderson, P. Schoettler, L. Swanson, A. Kne, C. Reis, A. Mack and E. Sykes for assistance with mouse breeding; M. Mandal for advice on ChIP-Seq; P. Champoux and N. Shah for cell sorting; the University of Minnesota's Supercomputing Institute for computing resources; R. Woodland (University of Massachusetts medical School) for Xid mice on a C57BL/6 background; S. van Reijmersdal for MLPA analysis support; and L. Manlove and J. Fiege for help and discussions. Supported by the US National Institutes of Health (R21CA209229 for S.F. and H.S.; CA154998, CA151845 and CA185062 to M.A.F.; R01CA137060, R01CA139032, R01CA157644, R01CA169458 and R01CA172558 to M.M.; T32-AI07313 for C.D.S.K. and M.J.L.W.; and Leukemia Spore (P50 PA100632) to S.M.K.), the Cancer Research Institute, the Leukemia and Lymphoma Society, Kindern Krankervrij (KIKA-55 for R.P.K, B.S. and F.N.vL.) and the University of Minnesota (L.B.R.).

Author information

Author notes

  1. Casey D S Katerndahl and Lynn M Heltemes-Harris: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Laboratory Medicine and Pathology, Center for Immunology, Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, USA

    Casey D S Katerndahl, Lynn M Heltemes-Harris, Mark J L Willette, Gregory Hubbard & Michael A Farrar

  2. Supercomputing Institute for Advanced Computational Research, University of Minnesota, Minneapolis, Minnesota, USA

    Christine M Henzler, Rendong Yang & Kevin A T Silverstein

  3. MLRS Department, University of Vermont, Burlington, Vermont, USA

    Seth Frietze

  4. Department of Laboratory Medicine, University of California San Francisco, San Francisco, California, USA

    Hilde Schjerven

  5. Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA

    Laura B Ramsey

  6. Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania and The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA

    Andrew D Wells

  7. Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands

    Roland P Kuiper

  8. Laboratory of Pediatric Oncology Radboud University Medical Center, Radboud Institute for Molecular Life Sciences, Nijmegen, the Netherlands

    Blanca Scheijen & Frank N van Leeuwen

  9. Department of Pathology, Radboud University Medical Center, Radboud Institute for Molecular Life Sciences, Nijmegen, the Netherlands

    Blanca Scheijen

  10. Department of Systems Biology, Beckman Research Institute and City of Hope Comprehensive Cancer Center, Pasadena, California, USA

    Markus Müschen

  11. Department of Leukemia, The University of Texas Maryland Anderson Cancer Center, Houston, Texas, USA

    Steven M Kornblau

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  1. Casey D S Katerndahl
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Contributions

C.D.S.K., L.M.H.-H. and M.J.L.W. designed and performed experiments and analyzed data; C.M.H., S.F., R.Y. and K.A.T.S. analyzed mouse ChIP-Seq data sets; S.F., H.S. and M.M. generated ChIP-Seq data for human IKAROS and, with C.M.H., analyzed STAT5–IKAROS–NF-κB overlap in human lymphoblastoid and leukemia cell lines; L.B.R. set up and ran microarray experiments; G.H. assisted with analysis of mouse leukemia; A.D.W. provided critical reagents and experimental advice; R.P.K., B.S. and F.N.v.L. carried out analysis of IKZF1 by multiplex ligation probe-dependent amplification, for samples from human patients; S.M.K. oversaw leukemia proteomics data and assisted with analyzing correlations among IKZF1, RELA and p-STAT5 ratios in samples from human patients; M.A.F. designed experiments and helped with analysis; C.D.S.K. and M.A.F. wrote the manuscript; and all co-authors edited the paper.

Corresponding authors

Correspondence to Steven M Kornblau or Michael A Farrar.

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Integrated supplementary information

Supplementary Figure 1 Mouse B-ALL-like leukemias most closely resemble large pre-B cells by global mRNA expression pattern and have deregulated expression of several tumor suppressors and oncogenes

(a) Spearman correlation coefficients calculated between expression data from WT pre-B cells (n = 5 samples pooled from 3-8 mice), Xid pre-B cells (n = 3 samples pooled from 3-8 mice), Stat5b-CA pre-B cells (n = 4 samples pooled from 3-8 mice), Stat5b-CA leukemias (n = 6 mice), Stat5b-CA x Blnk+/– leukemias (n = 5 mice), Stat5b-CA x Xid leukemias (n = 5 mice), or Stat5b-CA x Prkcb–/– leukemias (n = 4 mice) and the Hardy fractions of B cell development from immgen.org. (b) Quantitative real-time PCR for Bach2, Ikzf1, Myc, and Socs2 expression in WT pre-B cells or Stat5b-CA x Blnk+/–, Stat5b-CA x Xid, and Stat5b-CA x Prkcb–/– leukemias. Note: Ikzf1 and Myc are known NF-κB target genes. Black lines indicate means (b). *P < 0.05 **P < 0.01 (Unpaired t-test, b). Data are representative of three (WT) or four (Stat5b-CA x Blnk+/–, Stat5b-CA x Xid, and Stat5b-CA x Prkcb–/–) independent experiments (b).

Supplementary Figure 2 STAT5, PAX5, EBF, PU.1, IRF4, and IKAROS bind to many common target genes in progenitor B cell leukemia

(a) STAT5 (left panel), IKAROS (middle panel) and RELA (right panel) ChIP-qPCR at Myc super-enhancer in Stat5b-CA x Blnk+/- leukemias stimulated with (+) or without (-) IL7 at 37°C for 30 minutes. (b) Activating/repressive function prediction of STAT5 by ChIP-BETA. The red and the purple lines represent the upregulated and downregulated genes, respectively. The dashed line indicates the non-differentially expressed genes as background. Genes are cumulated by the rank on the basis of the regulatory potential score from high to low. (c) Occupancy of STAT5, PAX5, EBF, PU.1, IRF4 and IKAROS by ChIP-Seq at Bcl2l1, Igll1, Vpreb1, Pim1, Ccnd3, and Bcl6 loci in Stat5b-CA x Blnk+/- leukemia (STAT5), Rag-/- pro-B cells (PAX5, EBF, PU.1, IRF4) or WT pre-B cells (IKAROS). Progenitor B cell super-enhancers are annotated as “SE”. (d) (Top panel) Occupancy of STAT5 and IKAROS by ChIP-Seq at Socs2 locus in Stat5b-CA x Blnk+/- leukemia and WT pre-B cells, respectively. (Middle panel) Diagram of the Socs2 luciferase constructs. STAT5 binding sites are underlined in red while IKAROS binding sites are underlined in blue. Sites of mutation are indicated with asterisks. Base pair (bp) positions indicate distances relative to the Socs2 transcriptional start site. (Bottom panel) Luciferase assay of WT or mutant Socs2 promoter in Ba/F3 progenitor B cells transfected with Empty, Stat5b-CA, or Stat5b-CA and Ikzf1 retroviruses. (e) STAT5 (left panel) and p300 (right panel) ChIP-qPCR at Pim1 super-enhancer in Stat5b-CA x Blnk+/- leukemias stimulated with (+) or without (-) IL7 at 37°C for 30 minutes. (f) H3K27Ac ChIP-qPCR at Bcl2l1 super-enhancer in Ba/F3 cells transduced with empty (-) or Stat5b-CA (+) retroviruses. (g) STAT5, PAX5, EBF, and IKAROS ChIP-qPCR at the Myc, Bcl2l1, and Igll1 super-enhancers or a negative control locus located downstream of Igll1 in Stat5b-CA x Blnk+/- leukemias. (a,d,e,f,g) Mean ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 n.s. = not significant (one-way ANOVA with Bonferroni’s Multiple Comparison post-test, a,d,e,f). P = 6.3x10-26 (upregulated), P = 5.1x10-18 downregulated (Kolmogorov-Smirnov test, b). *P < 0.05, **P < 0.01, ***P < 0.001 (one-way ANOVA with Dunnett’s Multiple Comparison post-test, g) Data are representative of three (a,d,e,f), one (b, c (STAT5, PAX5, EBF, PU.1, IRF4), two (c, IKAROS), or five (g) independent experiments. Data for PEPII ChIP-Seq experiments in d,c came from30,36-38. Defined super-enhancers in c came from39.

Supplementary Figure 3 Binding of STAT5, PAX5, EBF, PU.1, IRF4, and IKAROS at genes that govern pre-B cell transcriptional networks

(a) Occupancy of STAT5, PAX5, EBF, PU.1, IRF4 and IKAROS by ChIP-Seq at Il7r, Jak1, Stat5b, Stat5a and Socs3 loci in Stat5b-CA x Blnk+/- leukemia (STAT5), Rag-/- pro-B cells (PAX5, EBF, PU.1, IRF4) or WT pre-B cells (IKAROS). Loci are annotated for progenitor B cell super-enhancers (SE). (b) Occupancy of STAT5, PAX5, EBF, PU.1, IRF4 and IKAROS by ChIP-Seq at Pax5, Ebf1, Sfpi, Irf4 and Ikzf1 loci. Loci are annotated for progenitor B cell super-enhancers (SE). Data are representative of one (a, b (STAT5, PAX5, EBF, PU.1, IRF4) or two (a, b, IKAROS) independent experiments. Data for PEPII ChIP-Seq experiments in d,c came from30,36-38. Defined super-enhancers in c came from39.

Supplementary Figure 4 Combined STAT5 activation and IKZF1 deletion status correlate best with survival and remission duration in patients with progenitor B-ALL

(a) Overall survival of B-ALL patients that were stratified based on IKZF1 status alone (Δ = deletion). (b) Overall survival of B-ALL patients that were separated into two equal-sized groups based on low or high pSTAT5 levels. (c,d) Overall survival of B-ALL patients that were stratified by separating them based on IKZF1 status (WT or deleted) and then further subdividing those groups based pSTAT5 levels (low or high). (e) Remission duration of B-ALL patients that were stratified based on IKZF1 status alone (Δ = deletion). (f) Remission duration of B-ALL patients that were separated into two equal-sized groups based on low or high pSTAT5 levels. (g,h) Remission duration of B-ALL patients that were stratified by first separating them based on IKZF1 status (WT or deleted) and then further subdividing those groups based pSTAT5 levels (low or high). (i) Statistical summary of the results shown in panels (a-h). N.D. = not done. P-values in a-h determined by log-rank Mantle-Cox test.

Supplementary Figure 5 Combined STAT5 activation and IKZF1 deletion status correlate best with survival and remission duration in patients with B-NOS progenitor B-ALL

(a) Survival of B-NOS B-ALL patients stratified by pSTAT5 and IKZF1 status. (b) Overall survival of B-NOS B-ALL patients that were stratified based on IKZF1 status alone (Δ = deletion). (c) Overall survival of B-NOS B-ALL patients that were separated into two equal-sized groups based on low or high pSTAT5 levels. (d,e) Overall survival of B-NOS B-ALL patients that were stratified by separating them based on IKZF1 status (WT or deleted) and then further subdividing those groups based pSTAT5 levels (low or high). (f) Remission duration in B-NOS B-ALL patients stratified by pSTAT5 and IKZF1 status. (g) Remission duration of B-NOS B-ALL patients that were stratified based on IKZF1 status alone (Δ = deletion). (h) Remission duration of B-NOS B-ALL patients that were separated into two equal-sized groups based on low or high pSTAT5 levels. (I,j) Remission duration of B-NOS B-ALL patients that were stratified by first separating them based on IKZF1 status (WT or deleted) and then further subdividing those groups based pSTAT5 levels (low or high). (k) Statistical summary of the results shown in panels (b-e) and (g-j). N.D. = not done. P-values determined by log-rank test for trends (a, f) or log-rank Mantle-Cox test (b,c,d,e,g,h,i,j).

Supplementary Figure 6 Combined pSTAT5 / RELA ratio and total pSTAT5 levels correlate best with survival in patients with progenitor B-ALL

(a) Overall survival of B-ALL patients that were stratified based on pSTAT5 / RELA ratio alone. (b) Overall survival of B-ALL patients that were separated into two equal-sized groups based on low or high pSTAT5 levels. (c,d) Overall survival of B-ALL patients that were stratified by separating them based on pSTAT5 / RELA ratio (low or high) and then further subdividing those groups based pSTAT5 levels (low or high). (e) Statistical summary of the results shown in panels (a-d). P-values in a-d determined by log-rank Mantle-Cox test.

Supplementary Figure 7 Combined pSTAT5 / RELA ratio and total pSTAT5 levels correlate best with survival and remission duration in patients with B-NOS progenitor B-ALL

(a) Survival of B-NOS B-ALL patients stratified by pSTAT5 and the ratio of pSTAT5 to RELA. (b) Overall survival of B-NOS B-ALL patients that were stratified based on pSTAT5 / RELA ratio alone. (c) Overall survival of B-NOS B-ALL patients that were separated into two equal-sized groups based on low or high pSTAT5 levels. (d,e) Overall survival of B-NOS B-ALL patients that were stratified by separating them based on pSTAT5 / RELA ratio (low or high) and then further subdividing those groups based pSTAT5 levels (low or high). (f) Remission duration of B-NOS B-ALL patients stratified by pSTAT5 and the ratio of pSTAT5 to RELA. (g) Remission duration of B-NOS B-ALL patients that were stratified based on pSTAT5 / RELA ratio alone: low or high. (h) Remission duration of B-NOS B-ALL patients that were separated into two equal-sized groups based on low or high pSTAT5 levels. (I,j) Remission duration of B-NOS B-ALL patients that were stratified by separating them based on pSTAT5 / RELA ratio (low or high) and then further subdividing those groups based pSTAT5 levels (low or high). (k) Statistical summary of the results shown in panels (b-e) and (g-j). N.D. = not done. P-values determined by log-rank test for trends (a, f) or log-rank Mantle-Cox test (b,c,d,e,g,h,i,j).

Supplementary Figure 8 Signaling pathways in progenitor B cells

The ratio of STAT5 to IKAROS regulates the expression of genes involved in survival, proliferation and differentiation. An imbalance of these pathways can lead to leukemia.

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Katerndahl, C., Heltemes-Harris, L., Willette, M. et al. Antagonism of B cell enhancer networks by STAT5 drives leukemia and poor patient survival. Nat Immunol 18, 694–704 (2017). https://doi.org/10.1038/ni.3716

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