Prognostic Studies in Multiple Myeloma with

Prognostic Studies in Multiple Myeloma with Emphasis on Genetic Tumor Lesions by Niels Emil Ulrich Hermansen, MD Myeloma Research Laboratory Department of Hematology Rigshospitalet

This PhD thesis was submitted to the Graduate School of Health and Medical Sciences University of Copenhagen 1 May 2016

Supervisors Peter Gimsing, Associate Professor, MD, DMSc (Main) Department of Clinical Medicine, University of Copenhagen Department of Hematology, Rigshospitalet, Copenhagen Mette Klarskov Andersen, MD, DMSc Department of Clinical Genetics, Rigshospitalet, Copenhagen Rehannah Borup Helweg-Larsen, MSc, PhD Center for Genomic Medicine, Rigshospitalet, Copenhagen Finn Cilius Nielsen, Professor, MD, DMSc Center for Genomic Medicine, Rigshospitalet, Copenhagen

Assessment Committee Lena Specht, Professor, MD, DMSc (Chair) Department of Clinical Medicine, University of Copenhagen Niels Abildgaard, Professor, MD, DMSc Department of Hematology, Odense University Hospital, Odense Markus Hansson, Associate Professor, MD, PhD Department of Hematology, Skåne University Hospital, Lund, Sweden

Thesis process Submission: 17 July 2015 (first) and 1 May 2016 (revised) Recommendation for public defense: 24 June 2016 Defense: 5 September 2016 at 13:00 at Rigshospitalet (Auditorium 2)

Correspondence Niels Emil Ulrich Hermansen Address: Skydebanegade 9, 3.th. / DK-1709 Copenhagen Email: [email protected] Telephone: +45 60 61 63 69 Twitter: @neuherman

Prognostic Studies in Multiple Myeloma with Emphasis on Genetic Tumor Lesions

PhD thesis © 2016 Niels Emil Ulrich Hermansen Cover photo: Myeloma cells on MGG-stained cytospin (by Lene Dissing Sjö). Epigraph by John Donne in Devotions upon Emergent Occasions (1624). Figures and tables were created by the author unless otherwise stated. American English spellings are used throughout. Typeset in LATEX memoir. Printed by VIAH (viah.dk).

No Man is an Iland, intire of it selfe; euery man is a peece of the Continent

Acknowledgements An overwhelming amount of people helped me get this far. First of all, the patients who donated a piece of themselves for a bigger cause— thank you. Thank you, Peter Gimsing and Lene Meldgaard Knudsen, for conceiving the project and introducing me to the international myeloma research community. I also thank you, Peter, for your calm optimism, clear-sightedness, and tenacity. Thank you, Mette Rønne, for being my main cell separation responsible in the Hematology Lab. Thank you, Mette Klarlund Andersen and Inge-Lise Frost Andersen, for your good-spirited guidance and assistance in the Chromosome Lab. Thank you, Rehannah Borup, Susanne Smed, and Finn Cilius Nielsen, for carrying through the gene expression analyses and deciphering the numbers. Thank you, Annette Vangsted, Nielsaage Tøffner Clausen, Dan Kristensen, and Michael Pedersen, for making this a multicenter study. Thank you, Hervé Avet-Loiseau, Audrey Ruau, Laurence Lodé, and the rest of the staff, for the good times in Nantes when you taught me how to ‘separate and FISH’. Thank you, Birgitte Preiss and staff in Odense, for teaching me cIg-FISH and helping us out when we needed extra eyes. Thank you, fellow doctors, research nurses, biopsy teams, and secretaries at Rigshospitalet and the hospitals in Herlev, Roskilde, and Næstved for recruiting the patients and collecting the samples. Thank you, Christina Dünweber, Birgitte Jørgensen, Trine Løw Holm, Rikke Bo Svensgaard, and Steen Hylgaard Jørgensen. Thank you, Lone Bach, Anne-Margrethe Svendsen, Steen Mortensen, Merete Tardrup, Lone Bredo Pedersen, Michael Bernard in the Hematology Lab, for handling blood and bone marrow samples. Thank you, Anette Grand, Vivian Jensen, Anette From, and Morten Tolstrup Andersen in the Chromosome Lab. Thank you, Birgitte Ravn Juhl, Kristina Sjöholm, and Lene Dissing Sjö in the Department of Pathology. Thank you, Jonas Vikeså at Center for Genomic Medicine. Thank you, Annette Jans, Hanadi Baajour, and Svend Høime Hansen in the Department iii

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Acknowledgements

of Biochemistry. Thank you, Anne Kærsgaard Mylin, Rasmus Sørrig, Christoffer Hother, Fie Juhl Vojdemann, Kostas Dimopoulos, Alexandra Søgaard, Anders Blaabjerg Nielsen, Andreas Glenthøj, Anja Pedersen, Anne Bjørlig, Bo Kok Mortensen, Brian Kornblit, Cecilie Nandrup-Bus, Christen Lykkegaard Andersen, Christian Geisler, Corinna Pedersen, Ditte Reker, Dorte Tholstrup, Eirik Tjønnfjord, Elisabeth Cramer, Fazila Asmar, Ida Schjødt, Jack Cowland, Katrine Bukan, Kirsten Grønbæk, Maria Torp-Larsen, Marianne Treppendahl, Peter Brændstrup, Sara Rørvig, Simon Husby, Stine Clemmensen, Tania Masmas, Ulrik Ralfkiær, and the late Jesper Jurlander, in the Hematology and Granulocyte Research Labs, for inspiration, collaboration, and good company. Thank you, Niels Borregaard and Lars Kjeldsen, for providing the necessary lab facilities at Rigshospitalet. Thank you, Lillian Keller, for excellent secretarial assistance. The project was secured by a PhD grant from the Research Foundation at Rigshospitalet and by “Funds bequeathed to the Department of Hematology at Rigshospitalet by Henning Christen Hansen, Silkeborg, for the advancement of myeloma research towards improved patient care”, Fabrikant Einar Willumsens Mindelegat, Danish Cancer Research Foundation, Janssen-Cilag, Agnes og Poul Friis Fond, Fonden til Lægevidenskabens Fremme, Dagmar Marshalls Fond, Købmand Sven Hansen og hustru Ina Hansens Fond, Reinholdt W Jorck og hustrus Fond, Eva og Henry Frænkels Mindefond, Karen A Tolstrups fond, Meta og Håkon Baggers Fond, Krista og Viggo Petersens Fond, Danish Medical Association Research Fund (Højmosegård-Legatet), Grosserer M Brogaard og Hustrus Mindefond, Elna og Jørgen Fagerholt Pedersens Kræftforskningsfond, Carl og Ellen Hertzs Legat til Dansk Læge- og Naturvidenskab, and Direktør Jacob Madsen og hustru Olga Madsens Fond. Thank you all. Thank you, family and friends. Thank you, Sara, Elsa, and Mia, for your immense support. You are my true base.

Niels Emil Ulrich Hermansen Copenhagen, 1 May 2016

Preface From March 2007 to February 2012, I was a research fellow in the Myeloma Research Laboratory in the Department of Hematology at Rigshospitalet. I entered the PhD programme at the University of Copenhagen in January 2008. From March 2012 to May 2016, I worked on the project alongside my specialty training in internal medicine and hematology at the hospitals of Næstved, Roskilde, and Herlev. This thesis sums up my work. It is based on the following papers: 1. Niels Emil Ulrich Hermansen & Peter Gimsing. Patient heterogeneity in phase II studies of refractory disease in multiple myeloma—the “spell” of the time to first relapse. British Journal of Haematology 2008 Jan;140(1):115-6. DOI: 10.1111/j.13652141.2007.06854.x 2. Niels Emil Ulrich Hermansen, Rehannah Borup, Mette Klarskov Andersen, Annette Juul Vangsted, Nielsaage Tøffner Clausen, Dan Lennart Kristensen, Finn Cilius Nielsen, Peter Gimsing. Gene expression risk signatures maintain prognostic power in multiple myeloma despite microarray probe set translation. International Journal of Laboratory Hematology 2016;38(3):298-307. DOI: 10.1111/ijlh.12486 3. Niels Emil Ulrich Hermansen, Rehannah Borup, Mette Klarskov Andersen, Annette Juul Vangsted, Nielsaage Tøffner Clausen, Dan Lennart Kristensen, Finn Cilius Nielsen, Peter Gimsing. Survival-related gene expression profiling of cytogenetic highrisk multiple myeloma. Manuscript in revision. The papers are added as Appendices 1-3 (p. 91ff.). My levels of contribution are presented in Appendix 4: Declarations of co-authorship. v

Contents Acknowledgements

iii

Preface

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Abbreviations

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Summary

xiii

Resumé (Summary in Danish)

xv

Chapter 1 Introduction 1.1 Multiple myeloma . . . . . . . . . 1.2 Prognostic factors . . . . . . . . . . 1.3 General myeloma genetics . . . . . 1.4 Prognostic cytogenetic aberrations 1.5 Prognostic GEP signatures . . . . . 1.6 Integrated risk stratification . . . . 1.7 Relapsed patients . . . . . . . . . . 1.8 Project background and aims . . .

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Chapter 2 Methods 2.1 Pilot study . . . . . . . . . . . . . 2.2 Main study design . . . . . . . . 2.3 Ethical measures and disclosures 2.4 Recruitment . . . . . . . . . . . . 2.5 Tissue sampling . . . . . . . . . . 2.6 Bone marrow separation . . . . . 2.7 Fluorescence in situ hybridization 2.8 Gene expression analysis . . . . . 2.9 Database and tools . . . . . . . .

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Contents

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Chapter 3 Results 3.1 Paper 1: The “spell” of the time to first relapse . . . 3.2 Baseline results of the main study . . . . . . . . . . 3.3 Survival results of the main study . . . . . . . . . . 3.4 Paper 2: Translated GEP risk signatures . . . . . . . 3.5 Paper 3: GEP & survival in FISH high-risk myeloma

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Chapter 4 Discussion 4.1 Main results . . . . 4.2 Limitations . . . . 4.3 Conclusion . . . . 4.4 Future perspectives

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References

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List of appendices

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Appendix 1: Paper 1

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Appendix 2: Paper 2

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Appendix 3: Paper 3

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Appendix 4: Declarations of co-authorship

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Appendix 5: Information for patients

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Appendix 6: Information for healthy controls

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Appendix 7: Consent form

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Appendix 8: Auxiliary biobank document

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Appendix 9: High-dose induction regimens

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Appendix 10: Cell separation protocol

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Appendix 11: cIg-FISH protocol

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Abbreviations FGFR3 fibroblast growth factor receptor 3 gene, HGNC:3690 IGH the immunoglobulin heavy locus at 14q32.33 MAF v-maf avian musculoaponeurotic fibrosarcoma oncogene homolog, synonym: c-MAF; HGNC:6776 WHSC1 Wolf-Hirschhorn Syndrome Candidate 1, synonym: MMSET (multiple myeloma SET domain); HGNC:12766 AMCA 7-aminocoumarin ASCS autologous stem cell support b2m beta-2-microglobulin BJP Bence Jones protein BSA bovine serum albumin BTZ bortezomib (Velcade®) CD138 syndecan 1 CD138+ CD138 positive cDNA complementary DNA cIg cytoplasmic immunoglobulin CR complete response CRP C-reactive protein ix

x

Abbreviations

CS-MN cytospins of mononuclear cells CS-PC cytospins of plasma cells CyDex cyclophosphamide and dexamethasone del(13q) deletion of 13q14 or monosomy 13 del(17p) deletion of 17p13 DMSO dimethyl sulfoxide DNA deoxyribonucleic acid DSS Durie-Salmon staging system EDTA ethylenediaminetetraacetic acid EFS event-free survival eGFR estimated glomeral filtration rate EMN European Myeloma Network FISH fluorescence in situ hybridization FLC free light chain gain(1q21) amplification or gain at the proximal 1q21 region GEP gene expression profiling Hb hemoglobin HDT high-dose therapy HLA human leukocyte antigen ICD-O International Classification of Diseases for Oncology (web: http://codes.iarc.fr/codegroup/2 IFN interferon-↵ Ig immunoglobulin

Abbreviations

xi

IMiDs Immunomodulatory drugs. IMiDs® is a registered trademark of Celgene Corporation for their drugs in the ATC class L04AX (other immunosuppressants): thalidomide, lenalidomide (DK: Revlimid®), and pomalidomide (DK: Imnovid®). IMWG International Myeloma Working Group ISS International Staging System ISS-iFISH 2012 IMWG revision of the International Staging System that includes FISH risk status. LDH lactate dehydrogenase M-protein monoclonal immunoglobulin (or fragment hereof) MDE myeloma-defining events MGUS monoclonal gammopathy of undetermined significance miRNA microRNA MRI magnetic resonance imaging mRNA messenger RNA mSMART Mayo Stratification of Myeloma and Risk-Adapted Therapy. Consensus guidelines regarding the risk stratification and treatment of myeloma patients developed by the Mayo Clinic, US. N’ NDMM patients that completed HDT NDMM newly diagnosed, symptomatic myeloma NGS next-generation sequencing NP-40 NP-40 nonylphenol ethoxylate detergent OS overall survival PBMC peripheral blood mononuclear cells PBS phosphate-buffered saline

xii

Abbreviations

PCR polymerase chain reaction PD progressive disease PDMM progressive myeloma PET positron emission tomography PFS progression-free survival PR partial remission R-ISS Revised International Staging System. 2015 IMWG consensus guidelines for risk stratification of newly diagnosed myeloma patients. R1 PDMM at first PD R2+ PDMM at second PD or later RH Copenhagen University Hospital Rigshospitalet RNA ribonucleic acid ROC receiver operating characteristic ROTI related organ tissue injury SNP single nucleotide polymorphism SSC saline sodium citrate t(11;14) translocation t(11;14)(q13;q32) t(14;16) translocation t(14;16)(q32;q23) t(4;14) translocation t(4;14)(p16;q32) TBS Tris-buffered saline TNT Tris-NaCl-Tween® trizol TRIzol® reagent TTP time to progression VAD vincristine (V), doxorubicin (Adriamycin®, A), dexamethasone (D)

Summary Multiple myeloma is a hematological cancer with approximately 300 new cases per year in Denmark, typically people aged above 65-70 years. Above all, the prognosis depends on the ability to tolerate highdose therapy (HDT) involving autologous stem cell support. Patients fit for HDT can expect median overall survival of about 6-8 years. Expectations are half that or less among patients who only tolerate gentler regimens. Genetic lesions in the myeloma cells provide additional prognostic information. However, it remains disputed exactly which genetic markers one should choose for optimal prognostication in different patient subgroups. Thus, the purpose of this project was to identify genetic tumor lesions by fluorescence in situ hybridization (FISH) and gene expression profiling (GEP) and compare their prognostic value with clinical risk markers among newly diagnosed patients eligible for HDT and patients relapsing after previous HDT. And to search for GEP patterns correlated with survival among FISH high-risk patients. From March 2008 to September 2010 we built a biobank at Rigshospitalet, Copenhagen, consisting of blood and bone marrow samples donated by a prospective cohort of 124 myeloma patients treated at four Danish centers. At a median follow-up time of 5.5 years we found GEP risk markers to hold significant prognostic value among newly diagnosed and relapsed HDT patients. The prognostic values of FISH risk markers and the International Staging System depended on relapse status: the former decreased, whereas the latter increased with every relapse. The time to first relapse was significantly correlated with survival. This was corroborated in an independent data set. We searched in vain for GEP patterns able to distinguish between FISH high-risk short-term and long-term survivors. In conclusion, this study suggests a differentiated use of prognostic markers in myeloma. The biobank enables additional prognostic and genetic studies.

xiii

Resumé (Summary in Danish) Myelomatose (knoglemarvskræft) er en hæmatologisk neoplasi med ca. 300 nye tilfælde årligt i Danmark, typisk ældre over 65-70 år. Fremfor alt afhænger prognosen af, hvor meget behandling man kan klare. Patienter, som tåler højdosisbehandling med autolog stamcellestøtte kan forvente en median overlevelse på 6-8 år. Forventningerne er kun halvt så store blandt patienter, som kun kan klare mildere behandling. Genetiske forandringer i myelomcellerne kan bruges til at præcisere prognosen yderligere. Men det er uklart, præcis hvilke genetiske markører, der har størst prognostisk værdi i de forskellige patientundergrupper. Formålet med dette projekt var således at udpege genforandringer i myelomceller med fluorescens-in situ-hybridisering (FISH) og genekspressionsprofilering (GEP) og sammenligne deres prognostiske værdi med kliniske risikomarkører blandt nydiagnosticerede patienter, som var kandidater til højdosisbehandling, og blandt tidligere højdosisbehandlede relapspatienter. Samt at lede efter GEP-mønstre korreleret til overlevelse blandt FISH-højrisikopatienter. Fra marts 2008 til september 2010 opbyggede vi en biobank af blodog knoglemarvsprøver på Rigshospitalet fra 124 myelomatosepatienter behandlet på fire hæmatologiske afdelinger i Østdanmark. Efter en median opfølgning på 5,5 år fandt vi GEP-risikomarkører korreleret med overlevelse blandt højdosisbehandlede patienter, også ved første relaps. Den prognostiske værdi af FISH-risikomarkører og International Staging System (ISS) afhang af relapsstatus: førstnævnte aftog og sidstnævnte tiltog for hvert relaps. Vi fandt tiden til første relaps signifikant korreleret med overlevelse og kunne bekræfte dette i et uafhængigt datasæt. Vi ledte forgæves efter GEP-mønstre, som blandt FISH-højrisikopatienter kunne skelne mellem kort- og langtidsoverlevere. Dette studie foreslår således en differentieret anvendelse af prognostiske markører ved myelomatose. Biobanken muliggør supplerende prognostiske og genetiske studier. xv

Chapter 1

Introduction 1.1

Multiple myeloma

Pathology Multiple myeloma (plasma cell myeloma, ICD-O code 9732/3) is a neoplasm characterized by malignant bone marrow plasma cells (myeloma cells) as shown in the cover photo. They produce a monoclonal immunoglobulin (or fragment hereof) (M-protein)—also known as M-component—that is measurable in the peripheral blood or urine in 97% of cases. The free light chain (FLC) component of the Mprotein is also known as Bence Jones protein (BJP). The remainder are either non-secretory (2.5%), i.e. produce an M-protein that is not secreted, or non-producer myeloma (0.5%), i.e. produce no Mprotein at all. Most cases gradually evolve from subclinical stages, first monoclonal gammopathy of undetermined significance (MGUS) then asymptomatic (smoldering) myeloma, that become symptomatic the moment the patient has 60% clonal bone marrow plasma cells or develops myeloma-defining events (MDE), formerly known as myelomarelated organ tissue injury (ROTI) or CRAB criteria: hyperCalcemia, Renal failure, Anemia, and/or Bone lesions.[1–3] The diagnostic criteria are presented in Table 1.1. Comprising 10-15% of hematopoietic neoplasms and about one percent of all malignancies, myeloma is the second most common hematological malignancy, only surpassed by the non-Hodgkin lymphomas. In Denmark, the incidence of myeloma is around 300 patients per year (5 per 100,000). Median age at diagnosis is 70 years. Female:male ratio is about 1:1.5.[4, 5] 1

2

Introduction

Table 1.1: Overview of 2014 IMWG criteria for MGUS and multiple myeloma. In each column the criteria of each box must be fulfilled. FLC: free light chain. MDE: myeloma defining event (exact criteria omitted for clarity). MRI: magnetic resonance imaging. MGUS criteria have been simplified and IgM-MGUS exempted. Plasmacytoma can be either biopsy-proven bony or extramedullary.[3] MGUS Serum monoclonal protein (non-IgM) 5.0 mo.s, n=3) R2+_PFS: R2+ short-term PFS (≤4.4 mo.s, n=3) vs. long-term PFS (>4.4 mo.s, n=3)

GEP & survival in FISH high-risk myeloma: Online Supplementary Information

4

In addition, we created two group pairs consisting of all short-term vs. all long-term survivors, excluding R1 samples from the two patients that also provided N samples in order to keep the groups perfectly independent: Short_long_OS: Short-term OS (≤26.8 mo.s, n=9) vs. long-term OS (>26.8 mo.s, n=13) Short_long_PFS: Short-term PFS (range 0.4-10.1 mo.s, n=9) vs. long-term PFS (range 4.5-49.1 mo.s, n=13). Figure 1B and 1D support these pairings in that the patient groups did not differ significantly in terms of OS, and only slightly in terms of PFS.

To complete the pairings we also compared the FISH high-risk patient groups directly: N_R1: N (n=9) vs. R1 (n=7, again excluding the R1 samples from the two patients that also provided N samples) R1_R2+: R1 (n=9) vs. R2+ patients (n=6) N_R2+: N (n=9) vs. R2+ patients (n=6)

References 1.

Rajkumar SV, Harousseau J-L, Durie B, et al. Consensus recommendations for the uniform reporting of clinical trials: report of the International Myeloma Workshop Consensus Panel 1. Blood. 2011;117(18):4691–5.

2.

Breit S, Nees M, Schaefer U, et al. Impact of pre-analytical handling on bone marrow mRNA gene expression. Br J Haematol. 2004;126(2):231–43.

3.

Jourdan M, Ferlin M, Legouffe E, et al. The myeloma cell antigen syndecan-1 is lost by apoptotic myeloma cells. Br J Haematol. 1998;100(4):637–46.

4.

Lin P, Owens R, Tricot G, Wilson CS. Flow Cytometric Immunophenotypic Analysis of 306 Cases of Multiple Myeloma. Am J Clin Pathol. 2004;121:482–8.

5.

Ross FM, Avet-Loiseau H, Ameye G, et al. Report from the European Myeloma Network on interphase FISH in multiple myeloma and related disorders. Haematologica. 2012;97(8):1272–7.

6.

Leek JT, Scharpf RB, Bravo HC, et al. Tackling the widespread and critical impact of batch effects in high-throughput data. Nat Rev Genet. 2010;11(10):733–9.

GEP & survival in FISH high-risk myeloma: Online Supplementary Information (Figures)

Figure 1S: Flowchart of patient samples and analyses

N: newly diagnosed symptomatic multiple myeloma patients eligible for high-dose therapy. R: patients with progressive disease after previous high-dose therapy. FISH: Fluorescence in situ hybridization. GEP: gene expression profiling.*FISH and GEP results (n=63), **FISH results only (n=44), ***GEP results only (n=4), °neither FISH nor GEP results (n=15). Made with Gliffy online software (Gliffy, Inc., San Francisco, Ca., USA)

GEP & survival in FISH high-risk myeloma: Online Supplementary Information (Figures)

Figure 2S. Sample outcome as per successfull FISH and GEP results

N: Newly diagnosed symptomatic multiple myeloma patient and candidate for high-dose therapy. R1: Previously high-dose treated patient experiencing first-time progressive disease. R2+: As R1, but second-time or later progressive disease. Made with PowerPoint for Mac 2011 software (Microsoft Corporation, Redmond, Wa., USA)

GEP & survival in FISH high-risk myeloma: Supplementary Online Material (Figures) Figure 3S. Survival in relation to FISH high-risk status in the different patient groups

Kaplan-Meier plots, log rank p. Censored cases marked by ★ N: Newly diagnosed symptomatic multiple myeloma eligible for high-dose therapy. R1: Previously high-dose treated myeloma patient experiencing first-time progressive disease. R2+: As R1, but second-time or later progressive disease. OS: Overall survival. PFS: progression-free survival.

GEP & survival in FISH high-risk myeloma: Supplementary Online Information (Tables)

Table 1S. FISH results. (Legend at the bottom of the table)

Table 2S. FISH characteristics of FISH high-risk patients with available GEP data. Legend at the bottom of the table.

GEP & survival in FISH high-risk myeloma: Online Supplementary Information (Tables) ! Table 3S. Enriched gene sets in long-term PFS R2+ patients compared with shortterm PFS R2+ patients

Only enriched gene sets at q
Appendix 9: High-dose induction regimens List of given HDT induction regimens in our study population: CyMP: cyclophosphamide, melphalan, prednisolone CyDex: cyclophosphamide, dexamethasone CyLenDex: cyclophosphamide, lenalidomide, dexamethasone CyThalDex: cyclophosphamide, thalidomide, dexamethasone CyVelDex: cyclophosphamide, Velcade®(bortezomib), dexamethasone LenDex: lenalidomide, dexamethasone M2 (=VBCMP): vincristine, BCNU (carmustine), cyclophosphamide, melphalan, prednisolone MP: melphalan, prednisolone ThalDex: thalidomide, dexamethasone VAD: vincristine, Adriamycin®(doxorubicin), dexamethasone Vel: Velcade®(bortezomib) VelDex: Velcade®(bortezomib), dexamethasone VRD: Velcade®(bortezomib), Revlimid®(lenalidomide), dexamethasone VTD: Velcade®(bortezomib), thalidomide, dexamethasone VTDC: Velcade®(bortezomib), thalidomide, dexamethasone, cyclophosphamide 183

Appendix 10: Cell separation protocol Peripheral blood separation Peripheral blood was sampled in K2 EDTA-coated tubes and two tubes (both BD Vacutainer® , Becton Dickinson, Franklin Lakes, NJ, US). The samples were spun at 1590 g for 5 min. Plasma (EDTA tubes) and serum (serum tubes) supernatants were transferred to 1.8 ml cryogenic vials (Thermo Fisher Scientific Nunc® CryoTubes® , cat. no. 363401, Thermo Fisher Scientific, Waltham, MA, US) and stored at 80°C. The buffy coats from the EDTA tubes were pooled in a 14 ml tube (BD Falcon® , cat. no. 352057) and resuspended in 12 ml red cell lysis buffer (155 mM NH4 Cl, 10 mM NaHCO3 , 0.1 mM Na-EDTA; pH 7.3) for 10 min at +5°C, then spun at 400 g for 5 min. The resulting supernatant was discarded. If the pellet (PBMC) was still red, the lysis buffer step was repeated. PBMC was resuspended in 12 ml phosphatebuffered saline (PBS) (137 mM NaCl, 10 mM Na2 HPO4 , 2.7 KCl, 1.8 KH2 PO4 ; pH 7.8) containing 0.1% w/v bovine serum albumin (BSA) (Sigma-Aldrich, cat. no. A2153, Sigma-Aldrich, St. Louis, MO, US) and spun at 400 g for 5 min before discarding the supernatant. PBMC was resuspended in 2 ml PBS-BSA buffer and aliquoted to two 1.8 ml cryogenic vials that were spun at 400 g for 5 min. The supernatants were discarded and the vials were stored at 80°C.

Bone marrow separation Bone marrow was sampled in K2 EDTA-coated tubes (BD Vacutainer® ) or sterile plastic tubes (Thermo Fisher Scientific Nunc® , cat. no. 347856) with 1,000 IU heparin. The ensuing separation was carried out in three steps: 185

186

Appendix 10: Cell separation protocol

1. Isolation of mononuclear cells by density gradient centrifugation 2. Plasma cell separation by automated CD138+ immunomagnetic separation 3. Distribution of bone marrow fractions in various repositories and aliquots depending on the amount of tissue and on the separation yield 4. Preparation of cytospins ready for FISH analysis and purity evaluation Figure 1 (p. 187) shows the whole process from fresh sample to vials in the freezers. Unless otherwise specified, we performed the procedure at room temperature using disposable, non-sterile Pasteur pipettes for liquid tissue transfer.

Isolation of mononuclear cells The fresh bone marrow was spun at 700 g for 10 min. Bone marrow plasma emerged as the resulting supernatant and was transferred to 1.8 ml cryogenic vials (Thermo Fisher Scientific Nunc® CryoTubes® , cat. no. 363401) and stored at 80°C. The remaining cells were resuspended in RPMI (RPMI-1640 Medium R2405, SigmaAldrich AQmedia® ) to a total volume of 10 ml with intermediate filtering through a 30 µm nylon filter (MACS® Pre-Separation filter, Miltenyi Biotec, Bergisch Gladbach, Germany). Using a sterile 10 ml pipette, the suspension was laid on top of 4 ml density gradient medium (Lymphoprep® , Axis-Shield Diagnostics, Dundee, UK, or Ficoll-Paque® PREMIUM, GE Healthcare, Little Chalfont, UK) at room temperature and spun at 450 g for 25 min with the brake off. The resulting mononuclear layer was resuspended in RPMI to a total volume of 10 ml, intermediately filtered as described above. From this suspension, we draw two volumes: i) 10 µl for manual cell counting in a Neubauer hemocytometer thus revealing the total number of mononuclear cells in the bone marrow sample and forming the basis for calculating: ii) A volume containing cells for 10 or 12 cytospins of mononuclear cells (CS-MN) of 2.00 ⇥ 104 cells each intended for FISH analysis.

Appendix 10: Cell separation protocol

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Figure 1: Bone marrow separation. BM: bone marrow aspirate; CS-MN: cytospins of mononuclear cells; CS-PC: cytospins of plasma cells; dimethyl sulfoxide (DMSO): cold freeze medium containing 10% dimethyl sulfoxide; DP: dry pellet; DP-SRGN: dry pellet prepared for serglycin analysis; FIX: fixative of methanol and glacial acetic acid; MN: mononuclear cells; NEG: remaining cells after CD138+ separation (negative fraction); PC: plasma cells; RPMI: RPMI-1640 Medium; RSB: RoboSep® buffer; TRZ: trizol; : centrifugate; D.S.: centrifugate and discard supernatant.

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Appendix 10: Cell separation protocol

Plasma cell separation The mononuclear suspension was spun at 170 g for 10 min. The supernatant was discarded and the pellet was resuspended in RPMI to a concentration of 1.00 ⇥ 108 cells/ml, but at a volume no less than 250 µl regardless of concentration, according to the specifications of the RoboSep® automat (StemCell Technologies, Vancouver, BC, Canada) that we used for the immunomagnetic separation of CD138+ cells. Apart from the sample tube (or tubes), the machine was loaded with a disposable tip rack, distilled and Millipore® filtered water, RS buffer (RoboSep® buffer, StemCell Technologies, cat. no. 20104), EasySep® Human CD138 Positive Selection Cocktail and Magnetic Nanoparticles (StemCell Technologies, cat. no. 18357), and—per bone marrow sample—a set of a 14 ml Falcon tube (BD Falcon® , cat. no. 352057) for the separated cells (separation tube) and two 50 ml tubes (Thermo Fisher Scientific, cat. no. 373660): one for the remaining cells (NEG tube, i.e. mostly CD138 negative cells) and one for discarded wash diluent (waste). According to the number of mononuclear cells in the sample tube, we chose either the Bone Marrow (BM) or the High Recovery (HR) separation protocol: BM for samples with 15.0 ⇥ 106 cells or more, HR for samples with less than 15.0 ⇥ 106 cells. The resulting CD138+ cells were resuspended in RS buffer to 1000 µl and 7-10 µl was drawn for manual counting as described under Isolation of mononuclear cells.

Distribution of bone marrow fractions We apportioned the CD138+ cells in the following order of priority: I. Cells for CS-PC for microscopic evaluation of separation purity and for FISH: ideally, 2.00 ⇥ 104 cells per CS-PC. II. Cells for dry pellets for SNP analyses (DP) and trizol suspension for GEP analyses (TRZ) (ranked equally): ideally, 5.00 ⇥ 105 cells per vial. III. 5.0 ⇥ 103 cells for a single dry pellet intended for single gene analysis (originally scheduled for serglycin analysis) (DP-SRGN). IV. Cells for fixative (FIX) suspensions in the event of confirmatory FISH analyses; 1.00 ⇥ 106 cells per vial.

Appendix 10: Cell separation protocol

189

V. Cells for cold freeze medium suspensions (10% DMSO) in the event of analyses on fresh frozen live myeloma cells; 1.00-2.00 ⇥ 107 cells per vial. The amount of slides and vials per fraction was decided according to the number of CD138+ cells as shown in Table 1. Cytospins were prepared as explained in p. 190. CD138+ cells (total amount separated in millions) Below 0.020 0.020-0.039 0.040-0.059 0.060-0.079 0.080-0.199 0.200-0.499 0.50-1.99 2.00-2.99 3.00-3.99 4.00-4.99 5.00-5.99 6.00-6.99 7.00-7.99 8.00-8.99 9.00-9.99 10.0-29.9 30.0-49.9 50.0-69.9

Cytospins (CS-PC) 1 2 3 4 4 8 10 10 10 10 10 10 10 10 10 10 10 10

No. of vials DP

TRZ

DP-SRGN

FIX

DMSO

0 0 0 0 1 1 2 3 3 4 5 5 6 6 6 6 6 6

0 0 0 0 1 1 2 3 3 4 5 5 6 6 6 6 6 6

0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1

0 0 0 0 0 0 0 0 1 1 1 2 2 3 4 4 4 4

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 3

Table 1: CD138+ cell distribution schedule. CS-PC: cytospins of CD138+ plasma cells; DP: dry pellet; TRZ: trizol suspension; DPSRGN: 5.00 ⇥ 103 dry pellet cells; FIX: fixative suspension; DMSO: DMSO suspension. CD138+ cells were split between up to three tubes: a) DP, DP-SRGN, and TRZ (handled together, DP+TRZ), b) FIX, and c) DMSO, and resuspended to 1.00 ml each. NEG tube cells were resuspended to 10 ml. All tubes were spun at 170 g for 10 min. The supernatants was discarded and the resulting pellets resuspended to volumes corresponding to 500 µl per vial. A volume containing 5.0 ⇥ 103 cells

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Appendix 10: Cell separation protocol

for DP-SRGN taken from the DP+TRZ tube was resuspended to 500 µl. CD138 negative cells (NEG tube) were scheduled for aliquots of 2.0 ⇥ 107 cells per vial. We aliquoted said volumes to 1.5 ml Eppendorf tubes (DP, TRZ, DP-SRGN, and FIX) and 1.8 ml cryogenic tubes (DMSO and NEG) that were spun at 250 g for 10 min before discarding the supernatants. Next, DP, DP-SRGN, and TRZ cells were stored at 80°C, the latter after resuspension in 800-1000 ml trizol (TRIzol® reagent, Invitrogen, Life Technologies, Paisley, UK). FIX cells were suspended in 1.0 ml Carnoy fixative (100% methanol and 100% acetic acid; 3:1 v/v), refrigerated at +5°C for 15 min, spun again at 250 g for 10 min, resuspended in fixative and stored at 20°C. DMSO and NEG cells were placed on ice (0°C), resuspended in 10% DMSO (RPMI, fetal bovine serum, and DMSO; 6:3:1 v/v) and kept for 24-48 hours at 80°C prior to storage at 196°C.

Preparation of cytospins Each of the volumes drawn for CS-MN and CS-PC were resuspended to total volumes of 500 µl per cytospin. The resulting suspensions were spun onto glass adhesion slides (SuperFrost® Plus, Menzel-Gläser, Braunschweig, Germany) at 112 g for 5 min in a Shandon Cytospin® 2 cytocentrifuge (Thermo Fisher Scientific) equipped with original cytoclips and disposable single white funnels. The cytospins were marked with pencil, left to air-dry on the bench and stored at 20°C.

Appendix 11: cIg-FISH protocol Cytoplasmic light chain staining

Upon thawing and air-drying on the bench the CS-MN or bone marrow imprint slides were submerged in 4% formaldehyde (“Lilly’s solution”; pH 7.0) for 5 min and washed twice for 2 min in Tris-buffered saline (TBS) (50 mM Tris-HCl, 150 mM NaCl; pH 7.4). The slides were transferred to a jar with 10 mM citrate buffer (pH 6.0) at +95°C. After 10 min the jar was removed from the water bath and left to cool to room temperature for 30 min. The slides were washed for 2 min in TBS and for 2 min in Tris-NaCl-Tween® (TNT) (100 mM Tris-HCl, 150 mM NaCl; 0.05% w/v Tween®20; pH 7.56). We applied 200 µl anti solution (1:15 v/v 7-aminocoumarin (AMCA) Anti-Human Kappa chain solution, cat. no. CI-3060, Vector Laboratories, Burlingame, CA, US, in Antibody Diluent, Dako REAL®, cat. no. S2022, Dako, Glostrup, Denmark) or anti- solution (same as anti-, but with Anti-Human Lambda instead, cat. no. CI-3070) to the cell areas and left the slides to incubate in the dark for 60 min. We rinsed off the anti-solutions with TNT and washed the slides twice in TNT for 2 min. We added 200 µl anti-goat solution (1:25 v/v AMCA Anti-Goat IgG (H+L), Vector Laboratories, cat. no. CI-5000, in Antibody Diluent, Dako REAL®, cat. no. S2022) to the cell areas and left the slides to incubate in the dark for 30 min. We repeated the TNT rinse and wash procedure. The slides were dehydrated in three one-minute steps of ethanol (70%, 85%, and 100% v/v, respectively). 191

192

Appendix 11: cIg-FISH protocol

Hybridization, washing, and mounting We used the following Vysis® locus-specific identifier (LSI) FISH probes (Abbott Molecular, Des Plaines, IL, US): • TP53 (17p13.1) SpectrumOrange (cat. no. 05J52-001) for the detection of del(17p13) • IGH Dual Color, Break Apart Rearrangement (cat. no. 05J73001) for the detection of IGH translocations • 13 (13q14) SpectrumGreen (cat. no. 05J80-001) for the detection of del(13q14) • IGH/FGFR3 Dual Color, Dual Fusion Translocation (cat. no. 05J74-001) for the detection of t(4;14)* • IGH/CCND1 Dual Color, Dual Fusion Translocation(cat. no. 05J69-001) for the detection of t(11;14)* • IGH/MAF Dual Color, Dual Fusion Probe (cat. no. 05J84-004) for the detection of t(14;16)* The latter three probes (marked with *) were only used if the first round of FISH analyses could not rule out IGH break apart. In case of few slides or unsuccessful first hybridization attempts, del(13q) and t(11;14) analyses were given lowest priority. FISH probes were diluted in denaturated water and Vysis® LSI/WCP Hybridization Buffer (cat. no. 32-804826) (1:2:7 v/v). We added 10 µl of said solution to each slide, and covered the cell area with a glass slip that was sealed with rubber cement. The slides were placed overnight in a Vysis® HYBrite (Abbott Molecular) machine set to 60 s of denaturation at +75°C followed by overnight hybridization ( 16 hours) at +37°C. We used solutions of saline sodium citrate (SSC) (150 mM NaCl, 15 mM trisodium citrate; pH 7.0) and NP-40 nonylphenol ethoxylate detergent (NP-40) for the Vysis® “Rapid Wash Procedure”: The glass covers were removed and the slides submerged in 0.4⇥SSC/0.3% NP-40 at +73°C for 2 min. The slides were then transferred to 2⇥SSC/0.1% NP-40 for 30-60 s at room temperature and left to air-dry in the dark for 20-40 min. We added 10-20 µl antifade Vectashield® Mounting Medium (Vector Laboratories, cat. no. H-1000), sealed off the cell area under a glass cover slip with rubber cement and stored the slides at 20°C until microscopy.