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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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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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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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The authors declare no competing financial interests.

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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