Published Ahead of Print on March 18, 2016, as doi:10.3324/haematol.2015.138701. Copyright 2016 Ferrata Storti Foundation.
Immunohistochemical detection of Inhibitor of DNA binding 3 mutational variants in mature aggressive B-cell lymphoma by Monika Szczepanowski, Neus Masqué-Soler, Matthias Schlesner, Andrea Haake, Julia Richter, Rabea Wagener, Birgit Burkhardt, Markus Kreuz, Reiner Siebert, ICGC MMML-Seq Consortium ICGC MMML-Seq Consortium, and Wolfram Klapper Haematologica 2016 [Epub ahead of print] Citation: Szczepanowski M, Masqué-Soler N, Schlesner M, Haake A, Richter J, Wagener R, Burkhardt B, Kreuz M, Siebert R, ICGC MMML-Seq Consortium ICGC MMML-Seq Consortium, and Klapper W. Immunohistochemical detection of Inhibitor of DNA binding 3 mutational variants in mature aggressive B-cell lymphoma. Haematologica. 2016; 101:xxx doi:10.3324/haematol.2015.138701 Publisher's Disclaimer. E-publishing ahead of print is increasingly important for the rapid dissemination of science. Haematologica is, therefore, E-publishing PDF files of an early version of manuscripts that have completed a regular peer review and have been accepted for publication. E-publishing of this PDF file has been approved by the authors. After having E-published Ahead of Print, manuscripts will then undergo technical and English editing, typesetting, proof correction and be presented for the authors' final approval; the final version of the manuscript will then appear in print on a regular issue of the journal. All legal disclaimers that apply to the journal also pertain to this production process.
Letter to the Editor Immunohistochemical detection of Inhibitor of DNA binding 3 mutational variants in mature aggressive B-cell lymphoma Monika Szczepanowski1*, Neus Masqué-Soler1, Matthias Schlesner2, Andrea Haake3, Julia Richter3, Rabea Wagener3, Birgit Burkhardt4, Markus Kreuz5, Reiner Siebert3, ICGC MMML-Seq Consortium #, and Wolfram Klapper1 *
1
Institute of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital
Schleswig-Holstein Campus Kiel, Christian-Albrechts University Kiel, Kiel, Germany 2
Division Theoretical Bioinformatics, Deutsches Krebsforschungszentrum Heidelberg (DKFZ),
Heidelberg, Germany 3
Institute of Human Genetics, University Hospital Schleswig-Holstein, Campus Kiel, Christian-
Albrechts University Kiel, Kiel, Germany 4
NHL-BFM Study Center and Department of Pediatric Hematology and Oncology, University
Children’s Hospital, Muenster, Germany 5
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
#
A full list of all authors and affiliations appears in the Supplemental Data.
Running heads: Immunohistochemical detection of ID3 mutations
*Correspondence:
[email protected]
and
[email protected]
kiel.de
Key words: molecular Burkitt lymphoma, diffuse large B cell lymphoma, anti-ID3 antibody, mutation, immunohistochemistry. Abbreviations: BL, Burkitt lymphoma; BNHL, B-cell non-Hodgkin lymphoma; BLU, B-cell lymphoma, unclassifiable, with features intermediate between DLBCL and BL;
1
DLBCL, diffuse large B-cell lymphoma; ID3, Inhibitor of DNA binding 3; ihc, immunohistochemistry; wt, wild-type.
Supplemental Data: a list of network members, material and methods, cell line and case details are described in the Supplemental Data, which are available with the online version of this article.
Acknowledgments: the research was supported by Deutsche Krebshilfe in the framework of the joint project Molecular Mechanisms in Malignant Lymphoma (MMML, 70-3173-Tr3) and the German Ministry for Education and Science (BMBF) in the framework of the International Cancer Genome Consortium MMML by Sequencing (ICGC MMML-Seq, 01KU1002A-J). RS and WK were supported by the BMBF within the framework of e:Bio Molecular Mechanisms in Malignant Lymphoma with MYC Deregulation project (MMML-MYC-SYS, 0316166B) and the BMBF within the framework of e:Med Molecular Mechanisms in Malignant Lymphoma – Demonstrator of the Personalized Medicine (MMML Demonstrator, 031A428D). RS and WK were supported by the KinderKrebsInitiative (KKI), Buchholz, HolmSeppensen e.V. RW is a recipient of a Christoph-Schubert-Award of the KKI, Buchholz, Holm-Seppensen. JR is supported by the Dr. Werner Jackstädt Foundation in the framework of a Junior Excellence Research Group (S134 10.100). The authors gratefully acknowledge O. Batic, C. Botz-von Drathen, T. Engel, C. Becher, and U. Schnaidt for their excellent technical assistance.
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Inhibitor of DNA 3 (ID3) mutations are frequent in Burkitt but rare or absent in other aggressive B-cell lymphomas. We tested the specificity of six anti-ID3 antibodies for the detection of ID3 mutational variants in a total of 89 aggressive B-cell lymphomas. Only one antibody was specific for ID3 in both immunohistochemistry and Western blot analyses. This antibody detected ID3 wild-type and ID3 protein with pointmutations, but lacked reactivity in lymphoma cells with structural genetic aberrations leading to loss of its C-terminal domains. In addition to the hallmark translocations involving the MYC oncogene and immunoglobulin loci (IG) 1, Burkitt lymphomas (BL) frequently carry mutations in the Inhibitor of DNA binding 3 (ID3) gene.2,3 Genetic aberrations of ID3 in BL comprise a spectrum of mono- and biallelic structural and point mutations.3 ID3 acts as negative transcriptional regulator by sequestering transcription factors with basic helix-loophelix (bHLH) motifs. Mutated ID3 attenuates this regulatory interaction.4,5 ID3 and its interaction partner TCF3 are involved in controlling cell cycle progression and survival pathways through tonic B-cell signalling. 6,7 ID3 mutations occur in 34-68% of BL but are rare in diffuse large B-cell lymphomas (DLBCL).2,3,7 Interestingly, the incidence of ID3 mutations has been reported to be higher in B-cell lymphomas, unclassifiable, with features intermediate between DLBCL and BL (BLU)
8
than in DLBCL. However, in the quoted study a molecular
diagnosis was not available and the diagnosis of an “intermediate” lymphoma was based on histopathological features only. 8,9 Mutation-specific immunohistochemistry represents a valuable diagnostic tool.10 Thus, we here tested six anti-ID3 antibodies for their ability to detect ID3 mutational variants in molecularly defined BL (mBL), intermediate and non-mBL lymphomas
11
by immunohistochemistry (Supplemental Table 1). 3
First, we tested all six antibodies on formalin-fixed and paraffin-embedded (FFPE) tonsil tissue by immunohistochemistry. ID3 has been reported to be strongly expressed in the dark zone and less intensive in the light zone of germinal centers.12 The expected staining pattern was only observed with clone 17-3 (BioCheck Inc., Foster City, USA) (Figure 1), but not for the other antibodies tested (Supplemental Figure 1). To evaluate if the clone 17-3 might show a mutation-specific staining pattern, selected wild-type (wt) and point-mutated ID3 cell lines and lymphoma specimens were tested by immunohistochemistry (Supplemental Figure 1) and by Western blot (Supplemental Figure 2). As expected, clone 17-3 showed no reactivity in BL cell lines and/or mBL biopsies with homozygous loss of ID3 (Figure 1; Supplemental Figure 1–2; Supplemental Table 2). The other five antibodies positively stained cell lines and/or biopsies by immunohistochemistry despite a homozygous deletion of the ID3 locus and were therefore not further used (Supplemental Figure 1; Supplemental Table 2). Mutation-sensitive ID3 immunohistochemistry using clone 17-3 was performed on 89 FFPE lymphoma biopsies. The conventionally assigned diagnoses based on histomorphologic and immunophenotypic features according to the current WHO classification
8
were as follows: BL (23/89), Burkitt leukaemia (1/89), atypical BL
(15/89), DLBCL (27/89), high-grade B-cell non-Hodgkin lymphoma (B-NHL, high) (3/89), BLU (2/89), follicular lymphoma grade 1-3a (10/89), transformed follicular lymphoma grade 3a/b/DLBCL (4/89), primary mediastinal B-cell lymphoma (2/89), primary
central
nervous
system
DLBCL
(1/89),
and
post-transplant
lymphoproliferative disease with features of DLBCL (1/89) (Supplemental Table 3). All cases were molecularly studied in either the MMML (n=41) or ICGC MMML-Seq (n=43) or both (n=5) projects. Thus, the molecular classification based on gene 4
expression analysis as well as the ID3 mutation status based on whole genome and/or Sanger sequencing were available.3,11,13,14 In detail, according to a defined gene expression signature, the so called molecular Burkitt (mBL) signature index, which reflects a probability of a case to resemble a Burkitt lymphoma, all cases were assigned their specific molecular diagnosis. In accordance to Hummel et al.11 cases with a mBL signature index score higher than 0.95 were assigned as molecular Burkitt lymphoma (mBL, 38/89), cases with an intermediate mBL signature index score between 0.05 and 0.95 as intermediates (14/89), cases with a mBL signature index score lower than 0.05 as non-molecular Burkitt lymphoma (non-mBL, 36/89), and 1 nodal manifestation of BL leukaemia without molecular diagnosis assignment (Supplemental Table 3; Supplemental Methods). ID3 expression in mBL showed a biphasic pattern. Almost all BL displayed either high ID3 expression scores (>50% positive lymphoma cells) or no expression (Figure 1h and Supplemental Table 3). mBL with wt, monoallelic point or monoallelic structural ID3 mutations (deletions, insertions or frameshifts) displayed ID3 immunoreactivity by immunohistochemistry (27/27, 100%, 2 mBL failed interpretable staining). All mBL in our series with lack of ID3 immunoreactivity (10/10, 100%) harboured complex biallelic structural ID3 mutations (e.g. biallelic frameshifts). Sequence analyses predicted a loss of the C-terminal ID3 epitope of clone 17-3 (Figure 1; Supplemental Table 3). We detected a broad spectrum of ID3 immunoreactivity in non-mBL ranging from no expression to high expression (Figure 1h and Supplemental Table 3). However, a high ID3 expression level (>50% positive lymphoma cells) was rare in non-mBL (6/36, 17%). ID3 expression in non-mBL seems to be independent of the mutational status, since none of the ID3-negative non-mBL harboured biallelic structural ID3 5
variants (0/8, 0%). Monoallelic mutations of ID3 were detected in only two non-mBL (2/36, 6%) and both lymphomas did not show ID3 immunoreactivity (Supplemental Table 3). Similar to non-mBL, molecularly defined intermediate lymphomas presented with a broad spectrum of ID3 expression (Figure 1 and Supplemental Table 3). High ID3 immunoreactivity (>50% positive lymphoma cells) was as frequent as in mBL (9/14, 64% vs. 27/37, 73%, respectively) and more frequent than in non-mBL (6/36, 17%). Complete lack of ID3 immunoreactivity was observed in only 2/14 intermediates which both harboured ID3 structural mutations. One was a paediatric case with a biallelic ID3 frameshift insertion and a splice site alteration. Unfortunately, we were not able to assess whether the lesion is biallelic in the second case (Supplemental Table 3). Interestingly, none of the four double- or triple hit lymphomas with MYC and either BCL2 and/or BCL6 translocations in our series had mutated ID3 nor lacked ID3 immunoreactivity (Supplemental Table 3). We describe an anti-ID3 antibody which was the only one of 6 antibodies tested showing a high specificity for ID3 in immunohistochemistry and Western blots. Clone 17-3 showed highly specific immunoreactivity for wt and point-mutated ID3 in mature aggressive B-cell lymphomas. We show that ID3 is highly expressed in mBL and the intermediate group of lymphomas, whereas non-mBL show either a moderate or a lack of ID3 expression. Furthermore, mBL and intermediates are both characterized by a high mutation frequency of ID3 whereas non-mBL do not. Furthermore, mBL and intermediates
11
, resembling mainly Burkitt lymphomas, atypical Burkitt
lymphomas and BLU 8, show a complete lack of ID3 staining only when biallelic structural aberrations causing a loss of C-terminal domains of ID3 are present. In contrast, none of the non-mBL cases in this study, mainly resembling DLBCL, 6
harboured biallelic structural ID3 mutations. ID3-negative non-mBL had either wt ID3 or harboured monoallelic ID3 locus deletions, thus the lack of ID3 expression was not associated with a genetic loss of ID3 domains but probably due to transcriptional regulation. Thus, lack of ID3 staining in a mature aggressive B-cell lymphoma with features of BL can be regarded as an indicator of biallelic loss of ID3. Since lack of ID3 immunoreactivity also occurs in a small subset of non-mBL with wt or monoallelic structural ID3 aberrations, the staining for ID3 seems currently to be of limited value in the differential diagnosis of lymphoma. A potential use in combination with other bio-marker needs to be determined in future studies.
7
References 1. Dalla-Favera R, Bregni M, Erikson J, Patterson D, Gallo RC, Croce CM. Human c-myc onc gene is located on the region of chromosome 8 that is translocated in Burkitt lymphoma cells. Proc Natl Acad Sci U S A. 1982;79(24):7824–7827. 2. Schmitz R, Young RM, Ceribelli M, et al. Burkitt lymphoma pathogenesis and therapeutic targets from structural and functional genomics. Nature. 2012;490(7418):116–120. 3. Richter J, Schlesner M, Hoffmann S, et al. Recurrent mutation of the ID3 gene in Burkitt lymphoma identified by integrated genome, exome and transcriptome sequencing. Nat Genet. 2012;44(12):1316–1320. 4. Murre C, McCaw PS, Vaessin H, et al. Interactions between heterologous helix-loophelix proteins generate complexes that bind specifically to a common DNA sequence. Cell. 1989;58(3):537–544. 5. Benezra R, Davis RL, Lassar A, et al. Id: a negative regulator of helix-loop-helix DNA binding proteins. Control of terminal myogenic differentiation. Ann N Y Acad Sci. 1990;599:1–11. 6. Dave SS, Fu K, Wright GW, et al. Molecular diagnosis of Burkitt's lymphoma. N Engl J Med. 2006;354(23):2431–2442. 7. Love C, Sun Z, Jima D, et al. The genetic landscape of mutations in Burkitt lymphoma. Nat Genet. 2012;44(12):1321–1325. 8. Swerdlow SH. WHO classification of tumours of haematopoietic and lymphoid tissues. 4th ed. World Health Organization classification of tumours. Lyon, France: International Agency for Research on Cancer; 2008. 9. Momose S, Weißbach S, Pischimarov J, et al. The diagnostic gray zone between Burkitt lymphoma and diffuse large B-cell lymphoma is also a gray zone of the mutational spectrum. Leukemia. 2015;29(8):1789–1791. 10. Capper D, Preusser M, Habel A, et al. Assessment of BRAF V600E mutation status by immunohistochemistry with a mutation-specific monoclonal antibody. Acta Neuropathol. 2011;122(1):11–19. 11. Hummel M, Bentink S, Berger H, et al. A biologic definition of Burkitt's lymphoma from transcriptional and genomic profiling. N Eng J Med. 2006;354(23):2419–2430. 12. Schmitz R, Ceribelli M, Pittaluga S, Wright G, Staudt LM. Oncogenic mechanisms in Burkitt lymphoma. Cold Spring Harb Perspect Med. 2014;4(2). 13. Alexandrov LB, Nik-Zainal S, Wedge DC, et al. Signatures of mutational processes in human cancer. Nature. 2013;500(7463):415–421. 14. Kretzmer H, Bernhart SH, Wang W, et al. DNA methylome analysis in Burkitt and follicular lymphomas identifies differentially methylated regions linked to somatic mutation and transcriptional control. Nat Genet. 2015;47(11):1316–1325.
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Figure 1. Immunohistochemistry for ID3 and ID3 mutation distribution among mBL, intermediates, and non-mBL. a-g. ID3 immunohistochemistry of tonsil, BL and BL cell line FFPE sections, original magnification of tonsil 50x, inlet 400x, cell lines 400x, cases 100x, inlets 400x. a-g. were stained with clone 17-3. a. reactive tonsil, pronounced ID3 distribution in the dark zone of germinal centres; b. BL cell line EB-1, wt ID3; c. BL cell line BL-41, biallelic stop gain, loss of ID3 amino acids (aa) 69-109; d. case 34, mBL, wt ID3; e. case 17; mBL, 2 ID3 point mutations; f. case 2, mBL, homozygous loss of ID3 C-terminal domains; g. case 15, mBL, stop gain and splice site mutation, the latter without structural consequences; h. Scatter plot of the ID3 immunohistochemical scoring based on percentages of ID3 positive tumor cells: 0=0%, 1=1-25%, 2=26-50%, 3=51-75%, and 4=76-100%. Each point is a case and the colour codes illustrate the mutational status of ID3. Two cases failed interpretable ID3 staining and were not included in the plot. BL, Burkitt lymphoma; FFPE, formalinfixed and paraffin embedded; int, intermediate. mBL, molecular Burkitt lymphoma; non-mBL, non-molecular Burkitt lymphoma; wt, wilde-type.
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Supplemental Data
Letter to the Editor Immunohistochemical detection of Inhibitor of DNA binding 3 mutational variants in mature aggressive B-cell lymphoma Monika Szczepanowski1*, Neus Masqué-Soler1, Matthias Schlesner2, Andrea Haake3, Julia Richter3, Rabea Wagener3, Birgit Burkhardt4, Markus Kreuz5, Reiner Siebert3, ICGC MMML-Seq Consortium #, and Wolfram Klapper1 * 1
Institute of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital
Schleswig-Holstein Campus Kiel, Christian-Albrechts University Kiel, Kiel, Germany 2
Division Theoretical Bioinformatics, Deutsches Krebsforschungszentrum Heidelberg (DKFZ),
Heidelberg, Germany 3
Institute of Human Genetics, University Hospital Schleswig-Holstein, Campus Kiel, Christian-
Albrechts University Kiel, Kiel, Germany 4
NHL-BFM Study Center and Department of Pediatric Hematology and Oncology, University
Children’s Hospital, Muenster, Germany 5
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
1
Table of Contents
I Members of the Network Project of the Deutsche Krebshilfe “Molecular Mechanisms in Malignant Lymphomas” (MMML) ............................................................................................................................. 3 II Members of the International Cancer Genome Consortium “Molecular Mechanisms in Malignant Lymphomas by Sequencing” (ICGC MMML-Seq) ................................................................................... 4 III Supplemental Materials and Methods ................................................................................................. 5 Lymphoma sample selection, pathology review and description of the cohort ................................... 5 Ethics, consent and permissions ......................................................................................................... 5 Cell culture ........................................................................................................................................... 5 Cell line FFPE blocks .......................................................................................................................... 5 Immunohistochemistry......................................................................................................................... 6 Protein extraction ................................................................................................................................. 6 Western blots ....................................................................................................................................... 6 ID3 mutational analysis ....................................................................................................................... 7 Molecular diagnosis ............................................................................................................................. 7 Availability of data sets ........................................................................................................................ 7 IV References .......................................................................................................................................... 8 V Supplemental Figures ........................................................................................................................ 10 VI Supplemental Tables ........................................................................................................................ 12
2
I Members of the Network Project of the Deutsche Krebshilfe “Molecular Mechanisms in Malignant Lymphomas” (MMML) Pathology group: Thomas F.E. Barth1, Heinz-Wolfram Bernd2, Sergio B. Cogliatti3, Alfred C. Feller2, Martin L. Hansmann4, Michael Hummel5, Wolfram Klapper6, Dido Lenze5, Peter Möller1, Hans-Konrad Müller-Hermelink7, Ilske Oschlies6, German Ott20, Andreas Rosenwald7, Harald Stein5, Monika Szczepanowski6, Genetics group: Thomas F.E. Barth1, Petra Behrmann8, Peter Daniel9, Judith Dierlamm8, Stefan Gesk,10 Eugenia Haralambieva7, Lana Harder10, Paul-Martin Holterhus11, Ralf Küppers12, Dieter Kube13, Peter Lichter14, Jose I. Martín-Subero10, Peter Möller1, Eva M. MurgaPeñas8, German Ott20, Shoji Pellissery10, Claudia Philipp12, Christiane Pott15, Armin Pscherer14, Julia Richter10, Andreas Rosenwald7, Itziar Salaverria10,Carsten Schwaenen16, Reiner Siebert10, Heiko Trautmann15, Martina Vockerodt17, Swen Wessendorf16, Bioinformatics group: Stefan Bentink18, Hilmar Berger19, Christian W Kohler18, Dirk Hasenclever19, Markus Kreuz19, Markus Loeffler19, Maciej Rosolowski19, Rainer Spang18. Clinical group for pediatric lymphoma: Birgit Burkhardt21, Alfred Reiter21, Willhelm Woessmann21 Project coordination: Benjamin Stürzenhofecker13, Lorenz Trümper13, Maren Wehner13. Steering committee: Markus Loeffler19, Reiner Siebert10, Harald Stein5, Lorenz Trümper13. 1Institute
of Pathology, University Hospital of Ulm, Germany, 2Institute of Pathology, University Hospital Schleswig-Holstein Campus Lübeck, Germany, 3Institute of Pathology, Kantonsspital St. Gallen, Switzerland, 4Institute of Pathology, University Hospital of Frankfurt, Germany, 5Institute of Pathology, Campus Benjamin Franklin, Charité–Universitätsmedizin Berlin, Germany, 6Department of Pathology, Hematopathology Section, University Hospital Schleswig-Holstein Campus Kiel/ Christian-Albrechts University Kiel, Germany, 7Institute of Pathology, University of Würzburg, Germany, 8University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 9Department of Hematology, Oncology and Tumor Immunology, University Medical Center Charité, Germany, 10Institute of Human Genetics, University Hospital Schleswig-Holstein Campus Kiel/Christian-Albrechts University Kiel, Germany, 11Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, University Hospital Schleswig-Holstein Campus Kiel / Christian-Albrechts University Kiel, Germany, 12Institute for Cell Biology (Tumor Research), University of Duisburg-Essen, Germany, 13Department of Hematology and Oncology, Georg-August University of Göttingen, Germany, 14German Cancer Research Center (DKFZ), Heidelberg, Germany, 15Second Medical Department, University Hospital Schleswig-Holstein Campus Kiel/ ChristianAlbrechts University Kiel, Germany, 16Cytogenetic and Molecular Diagnostics, Internal Medicine III, University Hospital of Ulm, Germany, 17Department of Pediatrics I, Georg-August University of Göttingen, Germany, 18Institute of Functional Genomics, University of Regensburg, Germany, 19Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Germany 20Institute of Clinical Pathology, Robert-BoschKrankenhaus, Stuttgart, Germany, 21 NHL-BFM Study Center Department of Pediatric Hematology and Oncology, Justus-Liebig-University. Giessen, Germany
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II Members of the International Cancer Genome Consortium “Molecular Mechanisms in Malignant Lymphomas by Sequencing” (ICGC MMML-Seq) Coordination (C1): Gesine Richter1, Reiner Siebert1, Susanne Wagner1, Andrea Haake1, Julia Richter1 Data Center (C2): Roland Eils2,3, Chris Lawerenz2, Sylwester Radomski2, Ingrid Scholz2 Clinical Centers (WP1): Christoph Borst4, Birgit Burkhardt5,6, Alexander Claviez7, Martin Dreyling8, Sonja Eberth9, Hermann Einsele10, Norbert Frickhofen11, Siegfried Haas4, MartinLeo Hansmann12, Dennis Karsch13, Michael Kneba13, Jasmin Lisfeld 6, Luisa Mantovani Löffler14, Marius Rohde5, Christina Stadler9, Peter Staib15, Stephan Stilgenbauer16, German Ott17, Lorenz Trümper9 , Thorsen Zenz35 Normal Cells (WPN): Martin-Leo Hansmann12, Dieter Kube9, Ralf Küppers18, Marc Weniger18 Pathology and Analyte Preparation (WP2-3): Siegfried Haas4, Michael Hummel19, Wolfram Klapper20, Ulrike Kostezka21, Dido Lenze19, Peter Möller22, Andreas Rosenwald23, Monika Szczepanowski20 Sequencing and genomics (WP4-7): Ole Ammerpohl1, Sietse Aukema1, Vera Binder24, Arndt Borkhardt24, Andrea Haake1, Kebria Hezaveh24, Jessica Hoell24; Ellen Leich23, Peter Lichter2, Christina Lopez1, Inga Nagel1, Jordan Pischimariov23, Bernhard Radlwimmer2, Julia Richter1, Philip Rosenstiel25, Andreas Rosenwald23, Markus Schilhabel25, Stefan Schreiber26, Inga Vater1, Rabea Wagener1, Reiner Siebert1 Bioinformatics (WP8-9): Stephan H. Bernhart27-29, Hans Binder28, Benedikt Brors2, Gero Doose27-29, Jürgen Eils2, Roland Eils2,3, Steve Hoffmann27-29, Lydia Hopp28, Helene Kretzmer27-29, Markus Kreuz30, Jan Korbel31, David Langenberger27-29, Markus Loeffler30, Sylwester Radomski2, Maciej Rosolowski30, Matthias Schlesner2 , Peter F. Stadler27-29,32-34, Stefanie Sungalee31 1
Institute of Human Genetics, University Hospital Schleswig-Holstein Campus Kiel/ Christian-Albrechts University Kiel, Kiel, Germany; 2 Division of Theoretical Bioinformatics (B080), German Cancer Research Center (DKFZ), Heidelberg, Germany 3 Department for Bioinformatics and Functional Genomics, Institute for Pharmacy and Molecular Biotechnology and Bioquant, University of Heidelberg, Heidelberg, Germany; 4 Friedrich-Ebert Hospital Neumünster, Clinics for Hematology, Oncology and Nephrology, Neumünster, Germany; 5 Department of Pediatric Hematology and Oncology, University Hospital Münster, Münster, Germany; 6 Department of Pediatric Hematology and Oncology University Hospital Giessen, Giessen, Germany; 7 Department of Pediatrics, University Hospital Schleswig-Holstein, Campus Kiel, Germany; 8 Department of Medicine III - Campus Grosshadern, University Hospital Munich, Munich, Germany; 9 Department of Hematology and Oncology, Georg-AugustUniversity of Göttingen, Göttingen, Germany; 10 University Hospital Würzburg, Department of Medicine and Poliklinik II, University of Würzburg, Würzburg, Germany; 11 Department of Medicine III, Hematology and Oncology, Dr. Horst-Schmidt-Kliniken of Wiesbaden, Wiesbaden, Germany; 12 Senckenberg Institute of Pathology, University of Frankfurt Medical School, Frankfurt am Main, Germany; 13 Department of Internal Medicine II: Hematology and Oncology, University Medical Centre, Campus Kiel, Kiel, Germany; 14 Hospital of Internal Medicine II, Hematology and Oncology, St-Georg Hospital Leipzig, Leipzig, Germany; 15 University Hospital Aachen, St.-Antonius Hospital, Department of Oncology, Hematology and stem cell transplantation, University of Aachen, Aachen, Germany; 16 Department of Internal Medicine III, University of Ulm, Ulm, Germany; 17 Robert-Bosch Hospital Stuttgart, Department of Pathology, Stuttgart, Germany; 18 Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany; 19 Institute of Pathology, Charité – University Medicine Berlin, Berlin, Germany; 20 Hematopathology Section, University Hospital Schleswig-Holstein Campus Kiel/ Christian-Albrechts University Kiel, Kiel, Germany; 21 Comprehensive Cancer Center Ulm (CCCU), University Hospital Ulm, Ulm, Germany; 22 Institute of Pathology, Medical Faculty of the Ulm University, Ulm, Germany; 23 Institute of Pathology, University of Würzburg, Würzburg, Germany; 24 Department of Pediatric Oncology, Hematology and Clinical Immunology, Heinrich-Heine-University, Düsseldorf, Germany; 25 Institute of Clinical Molecular Biology, University Hospital Schleswig-Holstein Campus Kiel/ Christian-Albrechts University Kiel,, Kiel, Germany; 26 Department of General Internal Medicine, University Hospital Schleswig-Holstein Campus Kiel/ ChristianAlbrechts University Kiel, Kiel, Germany; 27 Transcriptome Bioinformatics Group, LIFE Research Center for Civilization Diseases, Leipzig, Germany; 28 Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany; 29 Bioinformatics Group, Department of Computer, University of Leipzig, Leipzig, Germany 30 Institute for Medical Informatics Statistics and Epidemiology, Leipzig, Germany; 31 EMBL Heidelberg, Genome Biology, Heidelberg, Germany; 32 RNomics Group, Fraunhofer Institute for Cell Therapy and Immunology IZI, Leipzig, Germany 33 Santa Fe Institute, Santa Fe, New Mexico, United States of America 34 Max-Planck-Institute for Mathematics in Sciences, Leipzig, Germany 35 Department of Medicine V, University of Heidelberg, Heidelberg, Germany
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III Supplemental Materials and Methods
Lymphoma sample selection, pathology review and description of the cohort Eighty nine primary formalin-fixed and paraffin-embedded (FFPE) biopsies of 38 molecular Burkitt lymphomas (mBL), 14 intermediate lymphomas, 36 non-mBL with molecular diagnoses according to [1] and 1 nodal manifestation of BL leukemia without molecular diagnosis due to lacking molecular classification algorithms were extensively characterized in terms of histopathological diagnosis, immunophenotype, molecular diagnosis, molecular subtype and genomic aberrations (refer to Additional File 5). Forty one cases were diagnosed and molecularly characterized within the framework of the MMML joint project by expert reference pathology, standard immunohistochemistry (CD20, CD10, BCL2, BCL6, Mum-1, Ki-67), standard clonality IGH-PCR, fluorescence in situ hybridisation (FISH), array comparative genome hybridisation (array-CGH), single nucleotide polymorphism (SNP) array hybridisation and gene expression profiling by mRNA hybridisation as described [1]. Forty three cases were diagnosed and characterized within the German ICGC MMML-Seq subproject by expert reference pathology, standard immunohistochemistry (CD20, CD10, BCL2, BCL6, Mum-1, Ki-67), FISH, whole genome, exome and transcriptome sequencing [2,3]. Five additional cases (ID 15, 31, 50, 81, and 88) were characterized and analysed in both joint projects.
Ethics, consent and permissions The protocols of the MMML network have been approved by central (University of Göttingen) and local ethic review boards (Institutional Review Board of the Medical Faculty of the University of Kiel, D403/05). The ICGC MMML-Seq study has been approved by Ethics Committee of the Medical Faculty of the University of Kiel (A150/10) and of the recruiting centres. All cases within the frameworks of the projects were studied with informed consent of the respective parents and patients (if above 14 years old).
Cell culture The dimethyl sulfoxide (DMSO)-preserved cell lines BL-2, BL-41, BL-70, BLUE-1, DAUDI, EB-1, RAJI, SU-DHL-10, CA-46, DG-75, NAMALWA, RAMOS, U-689-M, MC-116, HT, SU-DHL-5 and SU-DHL-6 were obtained from the German Collection of Microorganisms and Cell Cultures (DSMZ, Braunschweig, Germany) and controlled for authenticity by STR analysis using the StemElite ID System (Promega, Mannheim, Germany) [2]. Cell lines were thawed and cultured in RPMI 1640 medium with 2 mM L-glutamine (Life Technologies, Germany), supplemented with 10-20% FCS and 1x penicillin/streptomycin (Life Technologies, Germany) in 5,5% CO2 at 37°C. Cells were grown until nearly reaching the log phase and harvested for protein extraction (5x106 cells per extraction) and FFPE block production (5-10x106 cells). Cell line FFPE blocks Freshly grown 5-10x106 cells were centrifuged at 800 rpm for 10 min and washed once in 1,5 ml 1x PBS buffer. After centrifugation at 800 rpm for 5 min cells were re-suspended in 4,5% PBS-buffered formalin and incubated for 20 min at room temperature. After centrifugation at 800 rpm for 5 min the cell pellet was washed in 3-5 ml 1x PBS, centrifuged again and re-suspended in 2 ml 96% isopropyl
5
and 3 droplets of premade chicken egg white/glycerol solution (Waldeck GmbH & Co. KG, Muenster, Germany). After 5 min centrifugation at 800 rpm the pellet was wrapped into a filter paper, placed in a metal capsule and incubated overnight in 96% isopropyl. The fixed cell pellet was further routinely processed for paraffin embedding.
Immunohistochemistry FFPE blocks of cell lines and patient tumor biopsies were cut (3-5 µm) onto glass slides, dried over night at 37°C and attributed to immunohistochemical stainings according to standard protocols described previously [1]. The anti-ID3 antibody test and experimental stainings were performed as described in Additional File 1. ID3 IHC scoring was performed by WK according to the percentage of positive tumor cells within the lymphoma biopsy or cell line FFPE section from 0 to 4 (0=0%; 1=1-25%; 2=26-50%; 3=51-75%; 4=76-100%). ID3 staining results for cell lines and cases are shown in Figure 1, Additional File 2, 4, and 5. Protein extraction Freshly grown 5-10x106 cells were harvested by centrifugation as described above. The supernatant was completely removed. The cell pellet was immediately snap-frozen in liquid nitrogen, transferred to -80°C freezer and stored until extraction. For protein extraction from BL-2, BL-41, BL-70, BLUE-1, DAUDI, EB-1, RAJI, and SU-DHL-10, frozen pellets of 5x106 cells were re-suspended in 500 µl ice-cold lysis buffer (1x PBS, 2% Triton, 1 mM EDTA), freshly supplemented with 75 µl 25x protease blocker (Roche, Germany) and incubated for 30 min on ice. For protein extraction from CA-46, DG-75, NAMALWA, RAMOS, U-698-M, MC-116, HT, SU-DHL-5 and SU-DHL-6 1 ml DMSO-stabilized 5x106 cells were rapidly thawed in a water bath at 37°C, briefly mixed with 10 ml warmed RPMI 1640 medium and pelleted at 800 rpm for 10 min at room temperature. After removal of supernatant, cells were lysed as described above. After 10 min centrifugation at 14 000 rpm at 4°C the protein extract was aliquoted, snap-frozen in liquid nitrogen and stored at -80°C until usage. 5 µl aliquots were taken prior to freezing to measure the protein concentration using the Qubit 2.0 Fluorometer (Life Technologies, Darmstadt, Germany).
Western blots An equivalent volume of protein extract containing 30 µg of protein was supplemented with an appropriate volume of 6x loading buffer (0.35 M Tris-HCl, 10.28% SDS, 36% glycerol, 5% 2mercaptoethanol, 0.012% bromophenol blue), mixed and incubated at 95°C for 5 min to denature proteins. The protein extracts were loaded onto the precast NuPAGE 4-12% Bis-Tris gels (Life Technologies, Darmstadt, Germany) which were pre-run for 20 min at 40V and run with the 1x NuPAGE MES-SDS Running Buffer (Life Technologies, Darmstadt, Germany) at 100V for 1.5 h. Protein transfer was done in 1,44 % glycine, 0,3% TRIZMA, and 20% methanol according to manufacturer’s instructions using the Hybond-P PVDF membrane (Amersham Biosciences / GE Healthcare, Buckinghamshire, UK). After blocking the membrane in 1x TBST buffer (0.242 % TRIZMA, 0.8 % NaCl, 0.01% Tween-20, pH 7,6) with 5% non-fat dry-milk for 1 h (BioRad Laboratories GmbH, Germany) and washing it for 5 min in 1x TBST, the rabbit monoclonal anti-mouse/human ID3 antibody clone 17-3 (BioCheck Inc., USA) in blocking buffer was applied to the membrane at 1:2500 dilution for 2 h at room temperature. After washing 3x for 15 min in 1x TBST a HRP-conjugated goat anti-rabbit antibody (DAKO Deutschland GmbH, Hamburg, Germany) at 1:10000 dilution was incubated with the membrane for 45 min, the latter washed again thrice in 1x TBST and developed with the ECL Western Blotting Detection Reagent (Amersham Biosciences / GE Healthcare, UK). The chemiluminescence was recorded using the ChemiDocMP System (BioRad Laboratories GmbH, München, Germany).
6
Blot stripping was performed by incubating the membrane in 1x stripping buffer according to manufacturer’s recommendation for 30 min at 50°C (ECL Western Blotting Detection Reagent booklet, Amersham Biosciences / GE Healthcare, UK). Loading control Western blots were performed analogously to the anti-ID3 procedure using the monoclonal mouse anti-human β-tubulin antibody (#T-
4026, Sigma-Aldrich Chemie, Taufkirchen, Germany) at 1:5000 dilution in TBST for 1 h at room temperature. The secondary antibody was a HRP linked sheep ECL anti-mouse IgG (#NA931V, Amersham Biosciences). ID3 mutational analysis DNA and RNA were isolated as previously described [1,2]. ID3 mutational analyses for both the MMML cohort and the cell lines used in this study were performed previously as described [2]. The ID3 mutational status for the ICGC MMML-Seq cohort was obtained from whole-genome sequencing data by using the following methods: (i) an in-house analysis pipeline based on SAMtools mpileup and bcftools was used to detect single nucleotide variants (SNVs) [4] (ii) Indels were called with Platypus [5] on the tumor BAM file and control BAM file and custom scripts were used to extract highconfidence somatic variants. SNVs and Indels were annotated using Annovar [6] and in-housedeveloped scripts. The ID3 mutational status was verified by manual inspection using the Integrative Genomics Viewer [7].
Molecular diagnosis Molecular diagnoses of the MMML cases were assigned as previously described [1]. DLBCL subtypes of the MMML cohort were assigned according to Wright et al. [8] with adaptations for the HGU133A Affymetrix GeneChip, which were previously described [1] and according to Hans et al., [9] based on immunohistochemistry. Further algorithm adaptation was performed to obtain molecular diagnoses and DLBCL subtypes from RNAseq data for the ICGC MMML-Seq cohort In short: RNAseq data of exemplar regions of the Affymetrix probesets included in the classifiers was analysed. Initial classification was derived by pathological review for BL/DLBCL classification and by unsupervised hierarchical clustering for DLBCL subtypes. For each probeset the distribution of the subtype-specific expression was estimated using initial classification. The final classification was determined by comparison of the expression of all probesets of a sample with the respective estimated probability distributions (Kreuz et al., manuscript in preparation). Availability of data sets MMML data sets are available at the GEO database (http://www.ncbi.nlm.nih.gov/geo/) under GEO accessions: GSE4475, GSE10172, GSE22470, GSE48184, GSE57612 [1,10-13]. For review purposes of the ICGC MMML-Seq cohort, please contact the data access committee (DAC; http://www.icgc.org/daco) of the International Cancer Genome Consortium (ICGC, http://www.icgc.org/) to get access to the data, which will be made public upon publication of submitted and/or revised current manuscripts for the ICGC MMML-Seq.
7
IV References
1.
Hummel M, Bentink S, Berger H, Klapper W, Wessendorf S, Barth, Thomas F E, Bernd H, Cogliatti SB, Dierlamm J, Feller AC, Hansmann M, Haralambieva E, Harder L, Hasenclever D, Kühn M, Lenze D, Lichter P, Martin-Subero JI, Möller P, Müller-Hermelink H, Ott G, Parwaresch RM, Pott C, Rosenwald A, Rosolowski M, Schwaenen C, Stürzenhofecker B, Szczepanowski M, Trautmann H, Wacker H, et al.: A biologic definition of Burkitt's lymphoma from transcriptional and genomic profiling. The New England journal of medicine 2006, 354(23):2419–2430. doi: 10.1056/NEJMoa055351. 2. Richter J, Schlesner M, Hoffmann S, Kreuz M, Leich E, Burkhardt B, Rosolowski M, Ammerpohl O, Wagener R, Bernhart SH, Lenze D, Szczepanowski M, Paulsen M, Lipinski S, Russell RB, Adam-Klages S, Apic G, Claviez A, Hasenclever D, Hovestadt V, Hornig N, Korbel JO, Kube D, Langenberger D, Lawerenz C, Lisfeld J, Meyer K, Picelli S, Pischimarov J, Radlwimmer B, et al.: Recurrent mutation of the ID3 gene in Burkitt lymphoma identified by integrated genome, exome and transcriptome sequencing. Nature genetics 2012, 44(12):1316–1320. doi: 10.1038/ng.2469. 3. Alexandrov LB, Nik-Zainal S, Wedge DC, Campbell PJ, Stratton MR: Deciphering signatures of mutational processes operative in human cancer. Cell reports 2013, 3(1):246–259. doi: 10.1016/j.celrep.2012.12.008. 4. Jones, David T W, Hutter B, Jäger N, Korshunov A, Kool M, Warnatz H, Zichner T, Lambert SR, Ryzhova M, Quang, Dong Anh Khuong, Fontebasso AM, Stütz AM, Hutter S, Zuckermann M, Sturm D, Gronych J, Lasitschka B, Schmidt S, Seker-Cin H, Witt H, Sultan M, Ralser M, Northcott PA, Hovestadt V, Bender S, Pfaff E, Stark S, Faury D, Schwartzentruber J, Majewski J, et al.: Recurrent somatic alterations of FGFR1 and NTRK2 in pilocytic astrocytoma. Nature genetics 2013, 45(8):927–932. doi: 10.1038/ng.2682. 5. Rimmer A, Phan H, Mathieson I, Iqbal Z, Twigg, Stephen R F, Wilkie, Andrew O M, McVean G, Lunter G: Integrating mapping-, assembly- and haplotype-based approaches for calling variants in clinical sequencing applications. Nature genetics 2014, 46(8):912–918. doi: 10.1038/ng.3036. 6. Wang K, Li M, Hakonarson H: ANNOVAR: functional annotation of genetic variants from highthroughput sequencing data. Nucleic acids research 2010, 38(16):e164. doi: 10.1093/nar/gkq603. 7. Robinson JT, Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G, Mesirov JP: Integrative genomics viewer. Nature biotechnology 2011, 29(1):24–26. doi: 10.1038/nbt.1754. 8. Wright G, Tan B, Rosenwald A, Hurt EH, Wiestner A, Staudt LM: A gene expression-based method to diagnose clinically distinct subgroups of diffuse large B cell lymphoma. Proceedings of the National Academy of Sciences of the United States of America 2003, 100(17):9991–9996. doi: 10.1073/pnas.1732008100. 9. Hans CP, Weisenburger DD, Greiner TC, Gascoyne RD, Delabie J, Ott G, Müller-Hermelink HK, Campo E, Braziel RM, Jaffe ES, Pan Z, Farinha P, Smith LM, Falini B, Banham AH, Rosenwald A, Staudt LM, Connors JM, Armitage JO, Chan WC: Confirmation of the molecular classification of diffuse large B-cell lymphoma by immunohistochemistry using a tissue microarray. Blood 2004, 103(1):275–282. doi: 10.1182/blood-2003-05-1545. 10. Klapper W, Szczepanowski M, Burkhardt B, Berger H, Rosolowski M, Bentink S, Schwaenen C, Wessendorf S, Spang R, Möller P, Hansmann ML, Bernd H, Ott G, Hummel M, Stein H, Loeffler M, Trümper L, Zimmermann M, Reiter A, Siebert R: Molecular profiling of pediatric mature B-cell lymphoma treated in population-based prospective clinical trials. Blood 2008, 112(4):1374–1381. doi: 10.1182/blood-2008-01-136465. 11. Salaverria I, Philipp C, Oschlies I, Kohler CW, Kreuz M, Szczepanowski M, Burkhardt B, Trautmann H, Gesk S, Andrusiewicz M, Berger H, Fey M, Harder L, Hasenclever D, Hummel M, Loeffler M, Mahn F, Martin-Guerrero I, Pellissery S, Pott C, Pfreundschuh M, Reiter A, Richter J, Rosolowski M, Schwaenen C, Stein H, Trümper L, Wessendorf S, Spang R, Küppers R, et al.: Translocations activating IRF4 identify a subtype of germinal center-derived B-cell lymphoma affecting predominantly children and young adults. Blood 2011, 118(1):139–147. doi: 10.1182/blood-2011-01-330795.
8
12. Masqué-Soler N, Szczepanowski M, Kohler CW, Spang R, Klapper W: Molecular classification of mature aggressive B-cell lymphoma using digital multiplexed gene expression on formalin-fixed paraffin-embedded biopsy specimens. Blood 2013, 122(11):1985–1986. doi: 10.1182/blood-201306-508937. 13. Scholtysik R, Kreuz M, Hummel M, Rosolowski M, Szczepanowski M, Klapper W, Loeffler M, Trümper L, Siebert R, Küppers R: Characterization of genomic imbalances in diffuse large B-cell lymphoma by detailed SNP-chip analysis. International journal of cancer. Journal international du cancer 2015, 136(5):1033–1042. doi: 10.1002/ijc.29072.
9
V Supplemental Figures
Supplemental Figure 1. ID3 immunohistochemistry of tonsils, FFPE cell lines, and FFPE mBL. Upper panel, a-e. FFPE sections of tonsils were stained with various antibodies and protocols to obtain best possible results. Representative examples are shown (original magnification 50x). Inlets represent high magnifications (400x) from the boundary between the germinal center and the mantle zone; f. Immunohistochemical staining of FFPE cell line sections with clone 17-3 and ab41834. Cell lines and their ID3 mutational status are indicated. Clone ab41834 showed an artificially positive staining for ID3 in BL-41 and BL-70 with both cell lines harbouring biallelic losses of the ID3 Cterminus.; g-i. Case 6, mBL, homozygous deletion in 1p.36 (including the ID3 locus); g. Clone 17-3, expectedly negative ID3 staining; h. ab41834 and i. sc-490, non-specific positive ID3 staining. For details on the mutations and the immunohistochemical score refer to Supplemental Table 3.
10
Supplemental Figure 2. ID3 expression in BL and DLBCL cell lines. Western blots were performed using the anti-ID3 antibody clone 17-3. 20 µg protein were used per cell line. (A) Cell lines BL-41 and BL-70 with homozygous loss of ID3 C-terminal domains expectedly show no ID3 expression indicating specificity of the antibody for ID3. In (A) and (B) further cell lines with wt and monoallelic mutations of ID3 stain positively for ID3. For details regarding the ID3 mutational status of cell lines refer to [3] and to the Supplementary Table 2. Size standard: SeeBlue Plus 2 (Novex #LC5925). Abbreviations: BL, Burkitt lymphoma; BNHL, B-cell nonHodgkin lymphoma; DLBCL, diffuse large B-cell lymphoma; fs, frameshift mutation; pm, point mutation; stop, nonsense mutation; ss, splice site mutation; wt, wild type.
11
VI Supplemental Tables
Supplemental Table 1. Antibodies and staining protocols. Antibody Clone catalogue no.
Manufacturer Epitope
Species
Dilution
Antigene Retrival
ab41834
n.a.
abcam
C-terminal
rabbit poly
1:25, 1:50, 1:100
3 min citrate buffer at pH 6 or 8
ab50876
n.a.
abcam
N-terminal
rabbit poly
1:5, 1:25 and o.n., 1:50, 1:100
3 min citrate buffer at pH 6
sc-490
C20
Santa Cruz Technology
C-terminal
rabbit poly
1:25, 1:50, 1:100
3 min citrate buffer at pH 6 or 8 / 15 min proteinase K at 37° / BOND ER2
GTX84323
8B3
Gene Tex
not specified
mouse mono
1:50, 1:100
3 min citrate buffer at pH 6 or 8
SAB1403958
3E10
Sigma Aldrich
not specified
mouse mono
1:50, 1:100
3 min citrate at pH 6
BCH-4/17-3
17-3
BioCheck Inc.
not specified
rabbit mono
1:500
3 min citrate buffer at pH 9 (manually) / BOND ER2
12
Supplemental Table 2. Cell line data. Sections of 3 µm were cut from cell line FFPE blocks and stained for ID3 with clone 17-3 (BioCheck Inc., Foster City, USA) and ab41834 (abcam, Cambridge, UK), the latter showing the second best immunohistochemistry staining pattern in tonsils (refer to Supplemental Figure 1). Clone ab41834 showed an artificially positive staining for ID3 in BL-41 and BL-70 with both cell lines harbouring biallelic losses of the ID3 C-terminus. Thus, only clone 17-3 was further used to detect ID3 protein expression in protein extracts from snap-frozen B-cell lymphoma cell lines (refer to Supplemental Figure 2). ID3 immunohistochemistry scoring: 0 = 0% ID3+ tumor cells, 1 = 1-25% ID3+ tumor cells, 2 = 26-50% ID3+ tumor cells, 3 = 51-75% ID3+ tumor cells, 4 = 76-100% ID3+ tumor cells. ID3 Western blot scoring: +++ strong expression, ++ slightly reduced expression, + reduced expression, - no expression. # mutational data according to [3].
Cell line
Entity
ID3 status#
ID3 mutation#
ID3 IHC score clone 17-3
Western blot clone 17-3
ID3 IHC score ab41834
BL-2
BL
splice site
c.300G>A (sm), c.300+1G>C
4
+++
4
BL-41
BL
stop gain (biallelic)
c.202G>C; 202G>C, p.Q68*; Q68*
0
-
4
BL-70
BL
frameshift deletion + splice site (biallelic)
c.139_264del, p.C47P*32; c.300+1G>A
0
-
4
BLUE-1
BL
frameshift deletion
c.236_240delACCTG, p.N79Afs*13
4
++
4
DAUDI
BL
nonsyn SNV + stop gain
c.160C>G, p.L54V; c.241C>T, p.Q81*
4
++
4
EB-1
BL
wt
wt
4
+++
4
RAJI
BL
wt
wt
4
+++
n.d.
SU-DHL-10
DLBCL
wt
wt
4
+++
4
CA-46
BL
nonsyn SNV
c.160C>G, p.L54V; c.190C>T, p.L64F
4
+
n.d.
DG-75
BL
wt
wt
4
++
n.d.
NAMALWA
BL
frameshift deletion with stop gain
c.220_360+66del, p.I74V*26
3
+
n.d.
RAMOS
BL
wt
wt
4
+++
n.d.
U-689-M
BL
nonsynSNV
c.166C>T, p.P56S; c.233T>C, p.L78P
4
++
4
MC-116
B-cell lymphoma
splice site
c.300G>A (sm), c.300+1G>A
4
+
n.d.
HT
DLBCL
wt
wt
3
+
4
SU-DHL-5
B-NHL
wt
wt
4
++
n.d.
SU-DHL-6
B-NHL
wt
wt
4
++
n.d.
Abbreviations: wt, wild type; nonsyn SNV, nonsynonymous single nucleotide variant; B-NHL, B-cell non-Hodgkin lymphoma; sm, silent mutation; n.d., not determined .
13
Supplemental Table 3: Case data. All cases were diagnosed by a panel of 5 expert hematopathologists and characterized by means of standard immunohistochemistry as published previously [11]. MYC, IG, BCL2, and BCL6 translocation status was analysed as published previously [3,11] (and hitherto unpublished data). ID3 immunohistochemistry by clone 17-3 was analysed according to the scoring criteria related to the percentage of ID3+ tumor cells: 0=0%, 1=1-25%, 2=26-50%, 3=51-75%, 4=76-100%. ID3 mutational status was partly published [2,3] (and hitherto unpublished data). Molecular diagnosis according to * MMML gene expression profiling [11]; $ according to [8]; & according to [9]. # ID3 mutation status according to [2,3] and hitherto unpublished data (§).
Case Molecular data by Age no.
Gender
Reference Panel Diagnosis
Molecular Diagnosis*
Subtype$
MYC Subtype & (df and bap FISH)
IGH (bap FISH)
BCL2 (bap FISH)
BCL6 (bap FISH)
ID3 mutation type
ID3 mutation
ID3 ihc score
1
ICGC MMML-Seq
13
male
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
frameshift insertion; deletion, biallelic
c.119_120insT,p.L40fs; LOH 1p from pter to 50 MB = ca. del1p36.331p33 (chr1: 1-50700000) (§)
0
2
ICGC MMML-Seq
4
male
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
frameshift deletion; deletion, biallelic
c.205delA, p.I69fs; del 1p36.11-1p36.12 (chr1:23216697-23905176) 0 (§)
3
MMML
12
male
BL, a
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
frameshift deletion; splice site, biallelic
c.137_151del, p.H46Lfs*80; c.220A>T, Q71L; c.300+12delAGTCGC (#)
0
4
MMML
4
male
BL, a
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV; biallelic splice site
c.190C>T, L64F; c.300+1G>A,T (#)
0
5
MMML
17
male
BL, a
mBL
Type III
GCB
IGH-MYC
pos
neg
neg
biallelic splice site
c.300+1G>A; c.300+1G>A (#)
0
6
MMML
63
female
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
homozygous deletion
homozygous deletion in 1p36 (#)
0
7
MMML
10
female
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
homozygous deletion
homozygous deletion in 1p36 (#)
0
8
MMML
7
male
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
inframe insertion; splice site
c.222_227dupCGACTA, p.D75_Y76insDY; c.300+1G>T (#)
0
9
MMML
4
male
DLBCL, cb
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
in-frame duplication
c.207_236dup, p.R72_Q81dup (#)
0
10
ICGC MMML-Seq
4
male
BL leukaemia [BL leukaemia] n.a.
GCB
IGH-MYC
pos
neg
neg
homozygous deletion
del 1p36.11-p36.12 (§)
0
11
MMML
13
female
DLBCL, cb
mBL
GCB
non-GCB
IGH-MYC
pos
neg
neg
syn +nonsyn SNV stop gain SNV
c.189G>A, Q63Q; c.166C>A; P56T; c.202G>T, E68X (#)
1
12
MMML
5
male
BL, a
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
frameshift deletion
c.116delG, p.S39Tfs*6 (#)
3
14
13
MMML
57
male
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
frameshift deletion
c.120_138del, p.L41Cfs*84 (#)
3
14
MMML
10
male
FL grade 3b
mBL
Type III
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV
c.239T>G, L80R (#)
3
15
MMML and ICGC MMML-Seq
10
male
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
stop gain SNV, splice site
c.C241T:p.Q81X; c.301-1G>A (no structural consequence) (#)(§)
4
16
ICGC MMML-Seq
17
male
BL
mBL
GCB
GCB
IGK-MYC
neg
neg
neg
syn SNV
c.G300A:p.Q100Q (§)
4
17
ICGC MMML-Seq
4
male
BL
mBL
Type III
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV
c.C166T:p.P56S; c.A130G:p.M44V (§)
4
18
ICGC MMML-Seq
14
male
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV
c.C190T:p.L64F (§)
4
19
ICGC MMML-Seq
8
male
BL
mBL
Type III
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV
c.C208G:p.L70V; c.C190T:p.L64F (§)
4
20
MMML
9
male
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV
c.164T>C, V55A; c.191T>G, L64R (#)
n.a.
21
MMML
13
male
BL, a
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV
c.166C>T; P56S (#)
4
22
MMML
4
male
BL, a
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
stop gain SNV
c.241C>T, Q81X; c.33C>G, Y11X (#)
4
23
MMML
24
male
BL, a
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
frameshift deletion
c.145_169del, p.Ser 49Profs*27 (#)
4
24
MMML
40
male
BL, a
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
stop gain SNV, frameshift deletion
c.298C>T, Q100X; c.189del G, p.Q63Hfs*20 (#)
4
25
MMML
5
male
BL, a
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV, stop gain c.190C>T, L64F; c.33C>G, Y11X; c.300G>A, SNV, syn SNV Q100Q (#)
26
MMML
5
male
BL, a
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV
c.152T>A, L51H; c.190C>G, L64V; c.248T>G, V83G (#)
27
MMML
12
male
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV, syn SNV
c.164T>A, V55E; c220A>G, I74V; c.267T>C, P89P, 4 c.287A>G, H96R (#)
28
MMML
2
female
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV
c.190C>G, L64V; c.195C>G, S65R (#)
4
29
MMML
28
male
B-NHL, high
mBL
Type III
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV
c.166C>T, P56S; c.166C>G, P56A (#)
4
30
MMML
9
male
B-NHL, high
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV
c.167C>G; P56R (#)
4
31
MMML and ICGC MMML-Seq
12
male
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
wt
wt (#)(§)
4
4 n.a.
15
32
ICGC MMML-Seq
18
female
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
wt
wt (§)
4
33
ICGC MMML-Seq
5
male
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
wt
wt (§)
4
34
ICGC MMML-Seq
2
male
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
wt
wt (§)
4
35
MMML
9
male
BL
mBL
GCB
GCB
IGL-MYC
pos t(8;14) neg
neg
neg
wt
wt (#)
4
36
MMML
5
female
BL
mBL
GCB
GCB
IGH-MYC
pos
neg
neg
wt
wt (#)
4
37
ICGC MMML-Seq
6
male
Intermediate BL/DLBCL
mBL
GCB
GCB
IGL-MYC
neg
neg
neg
wt
wt (§)
4
38
MMML
74
female
B-NHL, high
mBL
GCB
GCB
IGH-MYC
pos
neg
pos
wt
wt (#)
4
39
MMML
74
male
DLBCL, cb-ib
mBL
Type III
GCB
IGH-MYC
pos
pos
neg
wt
wt (#)
4
40
MMML
15
male
BL
intermediate
GCB
GCB
IGH-MYC
pos
neg
neg
frameshift insertion; splice site
c.143_161dupACTCCCGCCTGCGGGAACT, p.V55Lfs*17; c.300+1G>A (#)
0
41
MMML
49
male
DLBCL, cb
intermediate
GCB
GCB
IGH-MYC
pos
neg
neg
frameshift mutation
c.202_250del, p.E68Wfs*37 (#)
0
42
MMML
5
female
BL, a
intermediate
GCB
GCB
IGH-MYC
pos
neg
neg
frameshift deletion, stop gain
c.190_191del, p. L64X (#)
1
43
MMML
68
female
DLBCL, ib
intermediate
GCB
GCB
IGH-MYC
pos
pos
neg
wt
wt (#)
1
44
MMML
70
male
DLBCL, ib
intermediate
GCB
GCB
IGH-MYC
pos
pos
pos
wt
wt (#)
2
45
MMML
51
male
DLBCL, cb
intermediate
GCB
GCB
IGH-MYC
pos
pos
neg
wt
wt (#)
3
46
MMML
15
male
BL, a
intermediate
GCB
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV
c.194G>A; S65N (#)
4
47
MMML
6
female
BL, a
intermediate
GCB
GCB
IGK-MYC
neg
neg
neg
syn SNV
c.174C>T, V58V (#)
4
48
MMML
10
male
BL
intermediate
GCB
GCB
IGH-MYC
pos
neg
neg
nonsyn SNV
c.160C>G, L54V (#)
4
49
MMML
42
female
DLBCL, cb
intermediate
Type III
GCB
IGH-MYC
pos
neg
neg
stop gain, nonsyn SNV
c.169G>T, G57X; c.236A>G, D79G (#)
4
50
MMML and ICGC MMML-Seq
8
male
BL
intermediate
GCB
GCB
neg
neg
neg
neg
wt
wt (#)(§)
4
16
51
MMML
73
male
DLBCL, ib
intermediate
ABC
non-GCB
IGH-MYC
pos
neg
neg
wt
wt (#)
4
52
MMML
n.a.
n.a.
DLBCL, ib
intermediate
GCB
GCB
IGH-MYC
pos
neg
neg
wt
wt (#)
4
53
ICGC MMML-Seq
16
female
BL, a
intermediate
Type III
GCB
IGH-MYC
pos
neg
neg
wt
wt (§)
4
54
ICGC MMML-Seq
72
male
DLBCL, cb
non-mBL
ABC
non-GCB
neg
neg
neg
pos
deletion, monoallelic
copy-neutral LOH in 1p (§)
0
55
ICGC MMML-Seq
46
male
DLBCL, cb
non-mBL
GCB
GCB
neg
pos
neg
neg
deletion, monoallelic
LOH (4 Mbp deletion); might be subclonal (§)
0
56
MMML
64
female
DLBCL, pb
non-mBL
Type III
GCB
IGH-MYC
pos
neg
neg
wt
wt (#)
0
57
ICGC MMML-Seq
75
female
DLBCL cb
non-mBL
GCB
GCB
neg
neg
neg
neg
wt
wt (§)
0
58
ICGC MMML-Seq
57
female
DLBCL, cb
non-mBL
GCB
GCB
neg
pos
pos
neg
wt
wt (§)
0
59
ICGC MMML-Seq
74
female
FL grade 1/2
non-mBL
Type III
GCB
neg
pos
pos
pos
wt
wt (§)
0
60
ICGC MMML-Seq
74
female
FL grade 1
non-mBL
GCB
GCB
neg
neg
neg
neg
wt
wt (§)
0
61
ICGC MMML-Seq
70
male
PTLD, CNS DLBCL
non-mBL
Type III
non-GCB
neg
neg
neg
neg
wt
wt (§)
0
62
MMML
48
male
DLBCL, ana
non-mBL
GCB
n.a.
IGH-MYC
pos
neg
pos
wt
wt (#)
1
63
ICGC MMML-Seq
84
male
B-NHL, high
non-mBL
GCB
GCB
neg
pos
pos
pos
wt
wt (§)
1
664
ICGC MMML-Seq
49
male
DLBCL, cb
non-mBL
ABC
non-GCB
neg
pos
neg
pos
wt
wt (§)
1
65
ICGC MMML-Seq
16
male
DLBCL, cb
non-mBL
Type III
GCB
neg
pos
neg
neg
wt
wt (§)
1
66
ICGC MMML-Seq
64
male
DLBCL, cb
non-mBL
ABC
non-GCB
neg
neg
neg
neg
wt
wt (§)
1
67
ICGC MMML-Seq
47
male
FL grade 3a; DLBCL
non-mBL
GCB
GCB
neg
pos
pos
neg
wt
wt (§)
1
68
ICGC MMML-Seq
85
female
DLBCL, cb
non-mBL
GCB
GCB
neg
pos
pos
neg
wt
wt (§)
1
17
69
ICGC MMML-Seq
40
female
FL grade 1
non-mBL
GCB
GCB
neg
pos
pos
neg
wt
wt (§)
1
70
ICGC MMML-Seq
48
male
FL grade 1
non-mBL
GCB
GCB
neg
pos
pos
neg
wt
wt (§)
1
71
ICGC MMML-Seq
76
male
FL grade 2; FL grade 3a
non-mBL
Type III
GCB
neg
neg
pos
neg
wt
wt (§)
1
72
ICGC MMML-Seq
52
female
FL grade 2; FL grade 3a
non-mBL
GCB
GCB
neg
pos
pos
neg
wt
wt (§)
1
73
ICGC MMML-Seq
67
female
FL grade 1/2
non-mBL
Type III
GCB
neg
pos
pos
neg
wt
wt (§)
1
74
ICGC MMML-Seq
46
male
FL grade 1
non-mBL
GCB
GCB
neg
pos
pos
pos
wt
wt (§)
1
75
ICGC MMML-Seq
62
male
PMBCL
non-mBL
GCB
GCB
neg
pos
neg
pos
wt
wt (§)
1
76
ICGC MMML-Seq
16
male
PMBCL
non-mBL
GCB
GCB
neg
neg
neg
neg
wt
wt (§)
1
77
MMML
10
female
DLBCL, cb
non-mBL
GCB
GCB
IGK-MYC
neg
neg
neg
wt
wt (#)
2
78
ICGC MMML-Seq
66
male
DLBCL, cb
non-mBL
ABC
non-GCB
neg
neg
neg
neg
wt
wt (§)
2
79
ICGC MMML-Seq
73
female
FL grade 3a; DLBCL
non-mBL
Type III
non-GCB
neg
pos
pos
neg
wt
wt (§)
2
80
ICGC MMML-Seq
74
female
DLBCL, cb
non-mBL
ABC
non-GCB
neg
neg
neg
neg
wt
wt (§)
2
81
MMML and ICGC MMML-Seq
41
female
PMBCL
non-mBL
ABC
non-GCB
neg
neg
neg
neg
wt
wt (§)
2
82
ICGC MMML-Seq
70
female
FL grade 3b; DLBCL
non-mBL
Type III
GCB
neg
pos
neg
pos
wt
wt (§)
2
83
ICGC MMML-Seq
68
female
FL grade 3a
non-mBL
ABC
non-GCB
neg
neg
neg
neg
wt
wt (§)
2
84
ICGC MMML-Seq
59
male
DLBCL, cb
non-mBL
GCB
GCB
neg
pos
neg
pos
wt
wt (§)
3
85
ICGC MMML-Seq
70
male
FL grade 3a; DLBCL
non-mBL
Type III
GCB
neg
pos
neg
pos
wt
wt (§)
3
86
ICGC MMML-Seq
61
female
DLBCL, cb
non-mBL
ABC
non-GCB
neg
pos
neg
pos
wt
wt (§)
3
87
ICGC MMML-Seq
52
male
DLBCL, ib
non-mBL
ABC
non-GCB
IGH-MYC
pos
neg
neg
wt
wt (§)
3
18
88
MMML and ICGC MMML-Seq
15
male
DLBCL, ib
non-mBL
Type III
GCB
neg
neg
neg
pos
wt
wt (§)
4
89
ICGC MMML-Seq
75
female
prim. CNS DLBCL
non-mBL
ABC
non-GCB
neg
neg
neg
neg
wt
wt (§)
4
Abbreviations: ana, anaplastic; BL, Burkitt lymphoma; BL a, atypical Burkitt lymphoma; B-NHL, high, high-grade B cell non-Hodgkin lymphoma; bap, break-apart probe; cb, centroblastic; CNS, central nervous system; DLBCL, diffuse large B cell lymphoma; df, dual fusion probe; FISH, fluorescence in situ hybridization; FL, follicular lymphoma; ib, immunoblastic; ihc, immunohistochemistry; mBL, molecular Burkitt lymphoma; n.a., not available; non-mBL, molecularly defined nonBurkitt lymphoma; nonsyn SNV, non-synonymous single nucleotide variant; PTLD, post-transplant lymphoproliferative disease; syn SNV, synonymous single nucleotide variant; wt, wild type.
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