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Recurrent somatic mutations of PTPN1 in primary mediastinal B cell lymphoma and Hodgkin lymphoma

Nature Genetics volume 46, pages 329–335 (2014)Cite this article

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Abstract

Classical Hodgkin lymphoma and primary mediastinal B cell lymphoma (PMBCL) are related lymphomas sharing pathological, molecular and clinical characteristics. Here we discovered by whole-genome and whole-transcriptome sequencing recurrent somatic coding-sequence mutations in the PTPN1 gene. Mutations were found in 6 of 30 (20%) Hodgkin lymphoma cases, in 6 of 9 (67%) Hodgkin lymphoma–derived cell lines, in 17 of 77 (22%) PMBCL cases and in 1 of 3 (33%) PMBCL-derived cell lines, consisting of nonsense, missense and frameshift mutations. We demonstrate that PTPN1 mutations lead to reduced phosphatase activity and increased phosphorylation of JAK-STAT pathway members. Moreover, silencing of PTPN1 by RNA interference in Hodgkin lymphoma cell line KM-H2 resulted in hyperphosphorylation and overexpression of downstream oncogenic targets. Our data establish PTPN1 mutations as new drivers in lymphomagenesis.

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Figure 1: Results from whole-genome sequencing of two PMBCL tumors and germline DNA.
Figure 2: Locations of PTPN1 mutations in Hodgkin lymphoma and PMBCL.
Figure 3: Immunohistochemical analysis of PTP1B expression in lymph node biopsy samples from Hodgkin lymphoma (n = 215) and PMBCL (n = 143).
Figure 4: Expression of PTP1B mutants in HEK 293–STAT6 cells.
Figure 5: Activation of JAK-STAT in a PTPN1-silenced Hodgkin lymphoma cell line (KM-H2).

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Acknowledgements

We thank the BC Cancer Foundation and the Canada Foundation for Innovation for their support. We also thank T. Van Tol, M. Drake, R. Tong, the Genome Sciences Centre (GSC) production group and the Center for Translational and Applied Genomics (CTAG) for excellent technical support. This work is supported by a research grant from the Leukemia & Lymphoma Society of Canada (LLSC) and by a Terry Fox Research Institute team grant (1023) to C.S. and a Scholarship award from the Michael Smith Foundation for Health Research (MSFHR) to C.S. R.D.G. is supported by a Canadian Institutes of Health Research (CIHR) grant (178536) and a Terry Fox Foundation program project grant (019001). A.M. is supported by a fellowship award from the Mildred Scheel Cancer Foundation. R.K. is supported by fellowship awards from CIHR, MSFHR and the University of British Columbia.

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Authors and Affiliations

  1. Centre for Lymphoid Cancer, BC Cancer Agency, Vancouver, British Columbia, Canada

    Jay Gunawardana, Fong Chun Chan, Adèle Telenius, Bruce Woolcock, Robert Kridel, King L Tan, Susana Ben-Neriah, Anja Mottok, Raymond S Lim, Merrill Boyle, Kerry J Savage, Joseph M Connors, Randy D Gascoyne & Christian Steidl

  2. Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada

    Jay Gunawardana, Robert Kridel, Sohrab P Shah, Randy D Gascoyne & Christian Steidl

  3. Bioinformatics Training Program, University of British Columbia, Vancouver, British Columbia, Canada

    Fong Chun Chan

  4. Centre for High-Throughput Biology, University of British Columbia, Vancouver, British Columbia, Canada

    Sanja Rogic

  5. Department of Pathology, University of Arizona, Tucson, Arizona, USA

    Lisa M Rimsza

  6. INSERM U955, Créteil, France

    Chrystelle Guiter, Karen Leroy & Philippe Gaulard

  7. Université Paris Est, Créteil, France

    Karen Leroy, Philippe Gaulard & Corinne Haioun

  8. Département de Pathologie–Service d'Hématologie–Plateforme de Ressources Biologiques, Groupe Hospitalier Henri-MONDOR, Assistance Publique–Hôpitaux de Paris, Créteil, France,

    Karen Leroy, Philippe Gaulard & Corinne Haioun

  9. Genome Sciences Centre, BC Cancer Agency, Vancouver, British Columbia, Canada

    Marco A Marra

  10. Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada

    Marco A Marra

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  1. Jay Gunawardana
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Contributions

J.G. designed and performed the research, analyzed and interpreted data and wrote the manuscript. A.T., B.W., K.L.T., S.B.-N., A.M., M.B., R.K. and C.G. performed experiments and interpreted data. F.C.C., R.S.L. and S.R. analyzed data from whole-genome sequencing, RNA-seq and amplicon sequencing. C.H., K.L., L.M.R. and P.G. provided study material and interpreted results. K.J.S., M.A.M. and S.P.S. interpreted data. J.M.C. and R.D.G. curated the lymphoma database, interpreted data and reviewed the manuscript. C.S. designed the research, analyzed and interpreted data and wrote the manuscript.

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Correspondence to Christian Steidl.

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Integrated supplementary information

Supplementary Figure 1 PTP1B expression in PMBCL (n = 143) and in HL (n = 215) clinical specimens was analyzed by immunohistochemistry.

For PMBCL (a) and HL (b) cases with known PTPN1 mutational status, the percentage of positive tumor cells is shown. The overall distribution of PTP1B-positive tumor cells is shown in c,d.

Supplementary Figure 2 PTPN1 mutations and survival outcomes in PMBCL patients.

The Kaplan-Meier graphs show overall survival (a) and progression-free survival (b) in 77 PMBCL patients (60 PTPN1 WT and 17 mutated).

Supplementary Figure 3 PTPN1 mutations and survival outcomes in HL patients.

The Kaplan-Meier graphs show freedom from treatment failure (a) and disease-specific survival (b) in 30 HL patients (24 PTPN1 WT and 6 mutated).

Supplementary Figure 4 PTPN1 allelic imbalances in PMBCL and HL cell lines were analyzed by FISH.

The BAC clone for PTPN1 20q13.3 (CTD-2582P13) is labeled in spectrum orange, and the BAC clone for telomere 20p13 is labeled in spectrum green (control). Cell lines with normal PTPN1 copy numbers are not shown.

Supplementary Figure 5 PTP1B expression and PTPN1 transcript levels in PMBCL and HL cell lines were analyzed by protein blotting and qRT-PCR.

25 μg of extracted protein was incubated with anti-PTP1B. An EBV-transformed lymphoblastoid cell line (LCL) was used as a positive control, and an anti–β-actin antibody was used as a loading control. A representative experiment is shown (a). 5 ng of extracted RNA was used to detect PTPN1 mRNA using TaqMan gene expression assay probes. GAPDH was run as an internal control. Each sample was run in triplicate. Error bars represent s.d. (b).

Supplementary Figure 6 Determination of the allelic configuration in MedB-1.

cDNA from MedB-1 was cloned into a vector (pCR 2.1 TOPO TA cloning, Invitrogen). Sanger sequencing of subclones revealed PTPN1 mutations in a trans-allelic configuration. All clones screened had mutations in either exon 5 or 8.

Supplementary Figure 7 Gene set enrichment analysis.

Differentially expressed genes in PTPN1-silenced cells were analysed using GSEA software and the Molecular Signatures Database (Broad Institute).

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Gunawardana, J., Chan, F., Telenius, A. et al. Recurrent somatic mutations of PTPN1 in primary mediastinal B cell lymphoma and Hodgkin lymphoma. Nat Genet 46, 329–335 (2014). https://doi.org/10.1038/ng.2900

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