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Inherited GATA3 variants are associated with Ph-like childhood acute lymphoblastic leukemia and risk of relapse

Nature Genetics volume 45, pages 1494–1498 (2013)Cite this article

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Abstract

Recent genomic profiling of childhood acute lymphoblastic leukemia (ALL) identified a high-risk subtype with an expression signature resembling that of Philadelphia chromosome–positive ALL and poor prognosis (Ph-like ALL). However, the role of inherited genetic variation in Ph-like ALL pathogenesis remains unknown. In a genome-wide association study (GWAS) of 511 ALL cases and 6,661 non-ALL controls, we identified a susceptibility locus for Ph-like ALL (GATA3, rs3824662; P = 2.17 × 10−14, odds ratio (OR) = 3.85 for Ph-like ALL versus non-ALL; P = 1.05 × 10−8, OR = 3.25 for Ph-like ALL versus non-Ph-like ALL), with independent validation. The rs3824662 risk allele was associated with somatic lesions underlying Ph-like ALL (CRLF2 rearrangement, JAK gene mutation and IKZF1 deletion) and with variation in GATA3 expression. Finally, genotype at the GATA3 SNP was also associated with early treatment response and risk of ALL relapse. Our results provide insights into interactions between inherited and somatic variants and their role in ALL pathogenesis and prognosis.

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Figure 1: Genome-wide association study of Ph-like ALL.
Figure 2: rs3824662 genotype is associated with variation in GATA3 expression.
Figure 3: Association of GATA3 rs3824662 risk allele frequency with the constellation of multiple Ph-like ALL–related genomic lesions.
Figure 4: Association of genotype at GATA3 rs3824662 with ALL treatment response.

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References

  1. Pui, C.H. & Evans, W.E. Treatment of acute lymphoblastic leukemia. N. Engl. J. Med. 354, 166–178 (2006).

    Article  CAS  PubMed  Google Scholar 

  2. Pui, C.H., Mullighan, C.G., Evans, W.E. & Relling, M.V. Pediatric acute lymphoblastic leukemia: where are we going and how do we get there? Blood 120, 1165–1174 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Hunger, S.P. et al. Improved survival for children and adolescents with acute lymphoblastic leukemia between 1990 and 2005: a report from the Children's Oncology Group. J. Clin. Oncol. 30, 1663–1669 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Stanulla, M. et al. Integrating molecular information into treatment of childhood acute lymphoblastic leukemia—a perspective from the BFM Study Group. Blood Cells Mol. Dis. 39, 160–163 (2007).

    Article  PubMed  Google Scholar 

  5. Biondi, A. et al. Imatinib after induction for treatment of children and adolescents with Philadelphia-chromosome-positive acute lymphoblastic leukaemia (EsPhALL): a randomised, open-label, intergroup study. Lancet Oncol. 13, 936–945 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Den Boer, M.L. et al. A subtype of childhood acute lymphoblastic leukaemia with poor treatment outcome: a genome-wide classification study. Lancet Oncol. 10, 125–134 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Roberts, K.G. et al. Genetic alterations activating kinase and cytokine receptor signaling in high-risk acute lymphoblastic leukemia. Cancer Cell 22, 153–166 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Harvey, R.C. et al. Identification of novel cluster groups in pediatric high-risk B-precursor acute lymphoblastic leukemia with gene expression profiling: correlation with genome-wide DNA copy number alterations, clinical characteristics, and outcome. Blood 116, 4874–4884 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. 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 

  10. Harvey, R.C. et al. Rearrangement of CRLF2 is associated with mutation of JAK kinases, alteration of IKZF1, Hispanic/Latino ethnicity, and a poor outcome in pediatric B-progenitor acute lymphoblastic leukemia. Blood 115, 5312–5321 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Loh, M.L. et al. Tyrosine kinome sequencing of pediatric acute lymphoblastic leukemia: a report from the Children's Oncology Group TARGET Project. Blood 121, 485–488 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Papaemmanuil, E. et al. Loci on 7p12.2, 10q21.2 and 14q11.2 are associated with risk of childhood acute lymphoblastic leukemia. Nat. Genet. 41, 1006–1010 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Sherborne, A.L. et al. Variation in CDKN2A at 9p21.3 influences childhood acute lymphoblastic leukemia risk. Nat. Genet. 42, 492–494 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Treviño, L.R. et al. Germline genomic variants associated with childhood acute lymphoblastic leukemia. Nat. Genet. 41, 1001–1005 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Xu, H. et al. Novel susceptibility variants at 10p12.31-12.2 for childhood acute lymphoblastic leukemia in ethnically diverse populations. J. Natl. Cancer Inst. 105, 733–742 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Xu, H. et al. ARID5B genetic polymorphisms contribute to racial disparities in the incidence and treatment outcome of childhood acute lymphoblastic leukemia. J. Clin. Oncol. 30, 751–757 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Paulsson, K. et al. Genetic landscape of high hyperdiploid childhood acute lymphoblastic leukemia. Proc. Natl. Acad. Sci. USA 107, 21719–21724 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Jones, A.V. et al. JAK2 haplotype is a major risk factor for the development of myeloproliferative neoplasms. Nat. Genet. 41, 446–449 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Olcaydu, D. et al. A common JAK2 haplotype confers susceptibility to myeloproliferative neoplasms. Nat. Genet. 41, 450–454 (2009).

    Article  CAS  PubMed  Google Scholar 

  20. Kilpivaara, O. et al. A germline JAK2 SNP is associated with predisposition to the development of JAK2V617F-positive myeloproliferative neoplasms. Nat. Genet. 41, 455–459 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Yang, J.J. et al. Ancestry and pharmacogenomics of relapse in acute lymphoblastic leukemia. Nat. Genet. 43, 237–241 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Fujiwara, T. et al. Discovering hematopoietic mechanisms through genome-wide analysis of GATA factor chromatin occupancy. Mol. Cell 36, 667–681 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Wei, G. et al. Genome-wide analyses of transcription factor GATA3-mediated gene regulation in distinct T cell types. Immunity 35, 299–311 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Yagi, R., Zhu, J. & Paul, W.E. An updated view on transcription factor GATA3-mediated regulation of Th1 and Th2 cell differentiation. Int. Immunol. 23, 415–420 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Zhang, J. et al. The genetic basis of early T-cell precursor acute lymphoblastic leukaemia. Nature 481, 157–163 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Enciso-Mora, V. et al. A genome-wide association study of Hodgkin's lymphoma identifies new susceptibility loci at 2p16.1 (REL), 8q24.21 and 10p14 (GATA3). Nat. Genet. 42, 1126–1130 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Pasquet, M. et al. High frequency of GATA2 mutations in patients with mild chronic neutropenia evolving to MonoMac syndrome, myelodysplasia, and acute myeloid leukemia. Blood 121, 822–829 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Hahn, C.N. et al. Heritable GATA2 mutations associated with familial myelodysplastic syndrome and acute myeloid leukemia. Nat. Genet. 43, 1012–1017 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Davies, S.M. et al. Pharmacogenetics of minimal residual disease response in children with B-precursor acute lymphoblastic leukemia: a report from the Children's Oncology Group. Blood 111, 2984–2990 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Huang, R.S. et al. A genome-wide approach to identify genetic variants that contribute to etoposide-induced cytotoxicity. Proc. Natl. Acad. Sci. USA 104, 9758–9763 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Degner, J.F. et al. DNase I sensitivity QTLs are a major determinant of human expression variation. Nature 482, 390–394 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Borowitz, M.J. et al. Clinical significance of minimal residual disease in childhood acute lymphoblastic leukemia and its relationship to other prognostic factors: a Children's Oncology Group study. Blood 111, 5477–5485 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Shi, J. et al. Common variants on chromosome 6p22.1 are associated with schizophrenia. Nature 460, 753–757 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Purcell, S.M. et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752 (2009).

    Article  CAS  PubMed  Google Scholar 

  35. Troyer, J.L. et al. Genome-wide association study implicates PARD3B-based AIDS restriction. J. Infect. Dis. 203, 1491–1502 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Burchard, E.G. et al. Lower bronchodilator responsiveness in Puerto Rican than in Mexican subjects with asthma. Am. J. Respir. Crit. Care Med. 169, 386–392 (2004).

    Article  PubMed  Google Scholar 

  37. Korn, J.M. et al. Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs. Nat. Genet. 40, 1253–1260 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Pritchard, J.K., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Mao, X. et al. A genomewide admixture mapping panel for Hispanic/Latino populations. Am. J. Hum. Genet. 80, 1171–1178 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Tibshirani, R., Hastie, T., Narasimhan, B. & Chu, G. Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc. Natl. Acad. Sci. USA 99, 6567–6572 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Liu, E.Y., Li, M., Wang, W. & Li, Y. MaCH-admix: genotype imputation for admixed populations. Genet. Epidemiol. 37, 25–37 (2013).

    Article  CAS  PubMed  Google Scholar 

  42. Pruim, R.J. et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics 26, 2336–2337 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Chen, I.M. et al. Outcome modeling with CRLF2, IKZF1, JAK, and minimal residual disease in pediatric acute lymphoblastic leukemia: a Children's Oncology Group study. Blood 119, 3512–3522 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Andersen, P.K. & Perme, M.P. Pseudo-observations in survival analysis. Stat. Methods Med. Res. 19, 71–99 (2010).

    Article  PubMed  Google Scholar 

  45. Duan, S. et al. Genetic architecture of transcript-level variation in humans. Am. J. Hum. Genet. 82, 1101–1113 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Spielman, R.S. et al. Common genetic variants account for differences in gene expression among ethnic groups. Nat. Genet. 39, 226–231 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Ernst, J. et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 473, 43–49 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Zhou, X. et al. The Human Epigenome Browser at Washington University. Nat. Methods 8, 989–990 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank the patients and parents who participated in the COG protocols included in this study, the clinicians and research staff at COG institutions and J. Pullen (University of Mississippi at Jackson) for assistance in the classification of patients with ALL. Genome-wide genotyping of COG P9905 samples was performed by the Center for Molecular Medicine with generous financial support from the Jeffrey Pride Foundation and the National Childhood Cancer Foundation. V.P.-A. is supported by a Spanish Ministry of Education Fellowship Grant and by a St. Jude Children's Research Hospital Academic Programs Special Fellowship. J.J.Y. is supported by an American Society of Hematology Scholar Award, an Alex Lemonade Stand Foundation for Childhood Cancer Young Investigator Grant and by the Order of St. Francis Foundation. K.G.R. is supported by a National Health and Medical Research Council (Australia) Overseas Training Fellowship and by a Haematology Society of Australia and New Zealand Novartis New Investigator Scholarship. C.G.M. is a Pew Scholar in the Biomedical Sciences and a St. Baldrick's Scholar. We thank M. Shriver (Pennsylvania State University) for sharing SNP genotype data for the Native American references, J. Pritchard and J. Degner (University of Chicago) for sharing DNase I hypersensitivity data for HapMap YRI cell lines, R.C. Ribeiro (St. Jude Children's Research Hospital) and P. De Alarcon (University of Illinois College of Medicine at Peoria) for coordinating collaborations in Guatemala and S. Naron for her editorial assistance. This work was supported by the US National Institutes of Health (grant numbers CA156449, CA21765, CA36401, CA98543, CA114766, CA98413, CA140729 and GM92666), in part by the intramural Program of the National Cancer Institute and by the American Lebanese Syrian Associated Charities (ALSAC). Study sponsors were not directly involved in the design of the study, the collection, analysis and interpretation of data, the writing of the manuscript or the decision to submit the manuscript. Detailed acknowledgments for the dbGaP data sets are provided in the Supplementary Note.

Author information

Authors and Affiliations

  1. Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA

    Virginia Perez-Andreu, Wenjian Yang, Heng Xu, Shuyu E, Joshua Yew-Suang Lim, Colton Smith, William E Evans, Mary V Relling & Jun J Yang

  2. Department of Pathology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA

    Kathryn G Roberts & Charles G Mullighan

  3. Cancer Center, University of New Mexico, Albuquerque, New Mexico, USA

    Richard C Harvey, I-Ming Chen & Cheryl L Willman

  4. Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, Tennessee, USA

    Cheng Cheng & Deqing Pei

  5. Department of Pathology and Laboratory Medicine, Nationwide Children's Hospital, Columbus, Ohio, USA

    Julie Gastier-Foster

  6. Department of Pediatrics, Ohio State University School of Medicine, Columbus, Ohio, USA

    Julie Gastier-Foster

  7. Department of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore

    Joshua Yew-Suang Lim

  8. Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA

    Yiping Fan

  9. Department of Epidemiology and Health Policy Research, University of Florida, Gainesville, Florida, USA

    Meenakshi Devidas

  10. Johns Hopkins Medical Institute, Baltimore, Maryland, USA

    Michael J Borowitz

  11. Hartwell Center for Bioinformatics & Biotechnology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA

    Geoffrey Neale

  12. Department of Bioengineering & Therapeutic Science and Medicine, University of California, San Francisco, San Francisco, California, USA

    Esteban G Burchard & Dara G Torgerson

  13. Unidad Nacional de Oncología Pediátrica, Guatemala City, Guatemala

    Federico Antillon Klussmann & Cesar Rolando Najera Villagran

  14. Department of Pediatric Hematology/Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA

    Naomi J Winick

  15. Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA

    Bruce M Camitta

  16. New York University Cancer Institute, New York, New York, USA

    Elizabeth Raetz & William L Carroll

  17. Department of Laboratory Medicine, University of Washington, Seattle, Washington, USA

    Brent Wood

  18. Department of Biochemistry and Molecular Biology, Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA

    Feng Yue

  19. Maine Children's Cancer Program, Scarborough, Maine, USA

    Eric Larsen

  20. Department of Hematology and Oncology, Cook Children's Medical Center, Fort Worth, Texas, USA

    W Paul Bowman

  21. Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA

    Mignon L Loh

  22. Laboratory of Experimental Immunology, National Cancer Institute, Frederick, Maryland, USA

    Michael Dean

  23. Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA

    Deepa Bhojwani & Ching-Hon Pui

  24. Department of Hematology and Oncology, Children's Hospital Colorado, University of Colorado, Aurora, Colorado, USA

    Stephen P Hunger

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  1. Virginia Perez-Andreu
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Contributions

J.J.Y. supervised the research. V.P.-A., S.P.H., C.L.W., C.G.M. and J.J.Y. conceived and designed the experiments. V.P.-A., K.G.R., R.C.H., J.G.-F., S.E., I.-M.C., G.N., E.G.B., D.G.T. and C.R.N.V. performed the experiments. V.P.-A., J.J.Y., R.C.H., W.Y., C.C., D.P., Y.F., M. Devidas, C.S. and G.N. performed statistical analysis. V.P.-A., K.G.R., R.C.H., W.Y., H.X., S.E., J.Y.-S.L., I.-M.C., Y.F., M.J.B., C.S., G.N., E.G.B., D.G.T., F.A.K., C.R.N.V., M.L.L., M. Devidas, D.B., C.-H.P., W.E.E., M.V.R., S.P.H., C.L.W. and C.G.M. analyzed the data. R.C.H., J.G.-F., J.Y.-S.L., Y.F., E.G.B., F.A.K., C.R.N.V., N.J.W., B.M.C., E.R., B.W., F.Y., W.L.C., E.L., W.P.B., M.L.L., M. Dean, S.P.H., C.L.W. and C.G.M. contributed reagents, materials and/or analysis tools. V.P.-A. and J.J.Y. wrote the manuscript.

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Correspondence to Jun J Yang.

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Perez-Andreu, V., Roberts, K., Harvey, R. et al. Inherited GATA3 variants are associated with Ph-like childhood acute lymphoblastic leukemia and risk of relapse. Nat Genet 45, 1494–1498 (2013). https://doi.org/10.1038/ng.2803

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