media.nature.com · Web viewPrerequisites for evaluation were negativity in all NTCs, a correlation coefficient of the standard curves ≥ 0.99, an efficiency ≥ 85% for ABL1 and

Gaidzik VI, et al DNMT3A MRD in AML

Supplementary Appendix

The following AML Study Group (AMLSG) institutions and investigators participated in this study: Martin Trepel M.D., Klinikum Augsburg, Augsburg, Germany; Dietmar Reichert M.D., Ubbo-

Emmius Klinik, Aurich, Germany; Daniel Pink M.D., Helios Klinikum, Bad Saarow, Germany;

Jörg Westermann M.D., Charité Campus Virchow-Klinikum, Berlin, Germany; Dirk Strumberg

M.D., Klinikum-Ruhr Universität, Bochum-Herne, Germany; Wolff Schmiegel M.D., Roland

Schroers M.D., Knappschaftskrankenhaus, Bochum-Langendreer, Germany, Peter Brossart,

M.D., Universitätsklinikum Bonn, Bonn Germany; Jürgen Krauter M.D., Städtisches Klinikum,

Braunschweig, Germany; Bernd Hertenstein M.D., Henrike Thomssen M.D., Klinikum

Bremen-Mitte, Bremen, Germany; Helga Bernhard M.D., Klinikum Darmstadt, Darmstadt,

Germany; Rainer Haas M.D., Andrea Kuendgen M.D., Universitätsklinikum Düsseldorf,

Düsseldorf, Germany; Peter Reimer M.D., Mohammed Wattad M.D., Kliniken Essen Süd, Ev.

Krankenhaus Essen-Werden gGmbH, Essen, Germany; Rebekka Mannal M.D., Michael

Geißler M.D., Klinikum Esslingen, Esslingen, Germany; Nadezda Basara M.D., Malteser

Krankenhaus St-Franziskus-Hospital, Flensburg, Germany; Elke Jäger M.D., Krankenhaus

Nordwest GmbH, Frankfurt, Germany; Hans Martin M.D., Universitätsklinikum Frankfurt,

Frankfurt, Germany; Hans Günter Derigs M.D., Klinikum Frankfurt-Höchst GmbH, Frankfurt,

Germany; Michael Lübbert M.D., Universitätsklinikum Freiburg, Freiburg, Germany;

Alexander Burchardt M.D., Matthias Rummel M.D., Universitätsklinikum Gießen, Gießen,

Germany; Volker Runde M.D., Wilhelm-Anton-Hospital, Goch, Germany; Gerald Wulf M.D.,

Lorenz Trümper M.D., Universitätsklinikum Göttingen, Göttingen, Germany; Walter Fiedler

M.D., Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany; Hans Salwender M.D.,

Asklepios Klinik Altona, Hamburg, Germany; Elisabeth Lange M.D., Evangelisches

Krankenhaus Hamm, Hamm, Germany; Andrea Sendler M.D., Klinikum Hanau, Hanau,

Germany; Arnold Ganser M.D., Brigitte Schlegelberger M.D., Medizinische Hochschule

Hannover, Hannover, Germany; Hartmut Kirchner M.D. KRH Klinikum Siloah, Hannover,

Germany; Uwe Martens M.D., SLK-Kliniken GmbH Heilbronn, Heilbronn, Germany; Michael

Pfreundschuh M.D., Gerhard Held M.D., Universitätsklinikum des Saarlandes, Homburg,

Germany; David Nachbaur M.D., Günter Gastl M.D., Universitätsklinikum Innsbruck,

Innsbruck, Austria; Mark Ringhoffer M.D., Martin Bentz M.D., Städtisches Klinikum Karlsruhe

gGmbH, Karlsruhe, Germany; Heinz A. Horst M.D., Michael Kneba M.D.,

Universitätsklinikum Schleswig-Holstein–Campus Kiel, Kiel, Germany; Stephan Kremers

M.D., Caritas-Krankenhaus Lebach, Lebach, Germany; Frank Hartmann M.D., Klinikum

Lemgo-Lippe, Lemgo, Germany; Andreas Petzer M.D., Krankenhaus der Barmherzigen

Schwestern Linz, Linz, Austria; Michael Girschikofsky M.D., Krankenhaus der Elisabethinen

Linz, Linz, Austria; Gerhard Heil M.D., Klinikum Lüdenscheid, Lüdenscheid, Germany;

1


Thomas Fischer M.D., Universitätsklinikum Magdeburg, Magdeburg, Germany; Thomas

Kindler M.D., Wolfgang Herr M.D., Matthias Theobald M.D., Universitätsklinikum Mainz,

Mainz, Germany; Martin Grießhammer M.D., Johannes Wesling Klinikum, Minden Germany;

Katharina Götze M.D., Christian Peschel M.D., Klinikum rechts der Isar der Technischen

Universität München, München, Germany; Sabine Struve M.D., Clemens Wendtner M.D.,

Klinikum Schwabing, München, Germany; Holger Hebart M.D., Stauferklinikum Schwäbisch-

Gmünd, Mutlangen, Germany; Ali-Nuri Hünerlitürkoglu M.D., Lukaskrankenhaus GmbH

Neuss, Neuss; Germany; Claus-Henning Köhne M.D., Klinikum Oldenburg, Oldenburg,

Germany; Frank Griesinger M.D., Pius-Hospital Oldenburg, Oldenburg, Germany; Thomas

Südhoff M.D., Klinikum Passau, Passau, Germany; Otto Alexander Josef Kloke M.D.,

Elisabeth-Krankenhaus GmbH, Recklinghausen, Germany; Axel Matzdorff M.D., Caritas-

Klinik St. Theresia, Saarbrücken, Germany; Richard Greil M.D., Gudrun Russ M.D.,

Universitätsklinikum der Paracelsus Medizinischen Universität Salzburg, Salzburg, Austria;

Gerald Illerhaus M.D., Klinikum Stuttgart, Stuttgart, Germany; Jochen Greiner M.D.,

Diakonie-Klinikum Stuttgart, Stuttgart, Germany; Thomas Kubin M.D., Matthias Burkert M.D.,

Klinikum Traunstein, Traunstein, Germany; Heinz Kirchen M.D., Krankenhaus der

Barmherzigen Brüder, Trier, Germany; Rolf Mahlberg M.D., Mutterhaus der Borromäerinnen,

Trier, Germany; Helmut Salih M.D., Lothar Kanz M.D., Universitätsklinikum Tübingen,

Tübingen, Germany; Hartmut Döhner M.D., Konstanze Döhner M.D., Richard F. Schlenk

M.D, Universitätsklinikum Ulm, Ulm, Germany; Wolfgang Brugger M.D., Schwarzwald-Baar

Klinikum Villingen-Schwenningen GmbH, Villingen-Schwenningen, Germany; Elisabeth

Koller M.D., Hanuschkrankenhaus, Wien, Austria; Aruna Raghavachar M.D., Helios-Klinikum

Wuppertal, Wuppertal, Germany.

Methods

Patient Samples Bone marrow (BM) and peripheral blood (PB) cells were enriched for mononuclear cells by

Ficoll gradient and were frozen at -80°C. Total RNA and DNA were extracted from at best 1 ×

107 cells with the AllPrep Mini Kit (Qiagen, Hilden, Germany) according to standard protocol.

1 μg of RNA were reverse transcribed into cDNA with the QuantiTect Reverse Transcription

Kit (Qiagen GmbH, Hilden) and Random Hexamers (Applied Biosystems, Foster City, CA) in

a 20 μl reaction mix according to the protocol.

Real-Time Quantitative Polymerase Chain Reaction Analyses RQ-PCR assays were performed on the QuantStudio 12K Flex Real-Time PCR System

(Applied Biosystems, Foster City, CA). All reagents were derived from the TaqMan® PCR

2


Core Reagents Kit (Applied Biosystems, Foster City, CA). The 25 μl reaction mix for

DNMT3Amut quantification contained 2,5 μl cDNA, 1,25 U AmpliTaq Gold®, 1,25 U

AmpErase® UNG, 2,5 μl 10x Taqman PCR buffer A, 2,5 mM MgCl, 250 µM dNTPs, 500 nM

of each DNMT3A specific forward and reverse primer, 120 nM FAM/ BHQ1 labeled DNMT3A

probe, 240nM specific DNMT3A wildtype locked nucleic acid (LNA) primer for DNMT3Amut-

R882H and 200nM DNMT3A wildtype LNA primer for DNMT3Amut-R882C, respectively. The

25 μl reaction mix for ABL1 quantification contained 2,5 μl cDNA, 1,25 U AmpliTaq Gold®,

1,25 U AmpErase® UNG, 2,5 μl 10x Taqman PCR buffer A, 4 mM MgCl, 250 μM dNTPs,

300nM ABL1 forward primer, 300nM ABL1 reverse primer, and 200nM HEX/ BHQ1 labeled

ABL1 probe. PCR conditions were 2 min at 50°C, 10 min polymerase activation at 95°C and

45 cycles of denaturation at 95°C for 15 sec and annealing at 62°C for 1 min.

Each RQ-PCR run included a standard curve of a serial dilution from 106 to 102 plasmids for

ABL1 and the respective DNMT3Amut type, negative controls defined as no template controls

(NTC), and patient samples. DNMT3Amut and ABL1 were analyzed in triplicate.

QuantStudio 12K Flex Software (Applied Biosystems, Foster City, CA) was used to visualize

amplification curves and calculate Ct values at a threshold of 0.08 and an auto-baseline call

as recommended by the software for DNMT3Amut and ABL1. Prerequisites for evaluation

were negativity in all NTCs, a correlation coefficient of the standard curves ≥ 0.99, an

efficiency ≥ 85% for ABL1 and ≥ 80% for each DNMT3Amut type. A sample was considered

positive if Ct< 43.7 in 1 to 2 of 3 wells. For fulfilling the criteria “RQ-PCR negativity” all three

DNMT3Amut Ct values needed to be Ct> 43.7. Overall, at least 500 copies, or 100-500 copies

of ABL1 under consideration of the respective Ct-value, had to be detected.

Determination of specificity and sensitivity of the RQ-PCR assaySensitivities were determined by serial dilution of the cell line OCI-AML3 (DNMT3Amut-

R882C) or RNA from samples of patients (DNMT3Amut-R882H) in HL60 (DNMT3Awt) cells.

Maximum sensitivity was 10-4 for DNMT3Amut-R882C and 10-3 for DNMT3Amut-R882H. The

assays were highly specific as Ct values in DNMT3Awt AML samples or DNMT3Awt cell lines

were out of the quantitative range (Ct>45).

Digital Polymerase Chain Reaction Analyses The dPCR assay was performed using the QuantStudio® 3D Digital PCR System, notably

including the QuantStudio® 3D Digital PCR Chip Loader and the ProFlexTM PCR System

(Applied Biosystems, Foster City, CA).

The following primer and probes were designed and combined within a Custom TaqMan®

SNP Genotyping Assay (Applied Biosystems, Foster City, CA): forward primer:

CACTATACTGACGTCTCCAACATG; reverse primer: GACCGGCCCAGCAGTCT; probe 3


DNMT3Amut-R882H: CCACTTGGCGAGGCA (5'-FAM); probe DNMT3AWT:

CCGCTTGGCGAGGCA (5'-VIC).

The 17,4 µl reaction mix necessary for a single dPCR chip contained 1,75µl diluted genomic

DNA, 8,7 µl QuantStudio® 3D Digital PCR Master Mix (Applied Biosystems, Foster City, CA)

and 0,8 µl Custom TaqMan® SNP Genotyping Assay. The dilution factor of the required DNA

depended on the sample concentration; generally a diluted concentration of approximately

10-20 ng/µl was aspired. PCR conditions were 10 min polymerase activation at 96°C, 39

cycles of annealing at 54°C for 2 min and denaturation at 98°C for 30 sec. Each dPCR run

included a wildtype control DNA derived from the cell line HL60 as well as a negative control

defined as NTC and the corresponding patient samples.

QuantStudio® 3D AnalysisSuite Cloud Software 3.1 (Applied Biosystems, Foster City, CA)

was used to visualize amplification by means of Scatter Plot or Histogram View and to

calculate DNMT3Awt copies/µl (using VIC) and DNMT3Amut (using FAM) for each sample and

control. The thresholds for VIC and FAM differentiation were set manually for each run as

recommended by the calculation and visualization means of the software. Prerequisites for

evaluation were >15000 of 20000 analyzable data points and consistent distribution of the

reaction mix on the chip. The used quantification algorithm was “Poisson”. DNMT3Amut

transcript levels in dPCR were reported as percentages of target vs total copy numbers. A

sample was considered positive if the DNMT3Amut copies/µl were higher than the false

positive DNMT3Amut copies/µl of the wildtype control and the calculated levels exceeded

0,03%.

Determination of specificity and sensitivity of the dPCR assaySensitivity of dPCR assay was determined by serial dilution of DNA from a patient sample

with DNMT3Amut-R882H in HL60 (DNMT3Awt) cells. Maximum sensitivity was between 0,03%

and 0,05% for DNMT3Amut-R882H. This corresponds to a sensitivity of approximately 3 to 5 x

10-4 of a RQ-PCR assay.

4


Table S1. Overview of patients with allogeneic hematopoietic cell transplantation with regard to their entire therapy course and conditioning regimens.

Study Study ID Therapy Time of HCT Conditioning Regimen Type of Transplant

AMLSG 07-04 861 Prephase/ICE/ICE/HCT/Relapse CR1 TBI-Cy PBHD98A 1098 ICE/ICE/HAM/HCT/Rituximab CR1 TBI-Cy PBAMLSG 07-04 674 ICE/ICE/HCT CR1 TBI-Cy PBAMLSG 07-04 728 A-ICE/ICE/HA/HCT/Relapse/HU CR1 TBI-Cy PBAMLSG 07-04 313 Dauno-AraC/Dauno-AraC/HA/HCT CR1 TBI-Cy PBAMLSG 07-04 455 A-ICE/A-ICE/A-HA/HCT/DLI CR1 TBI-Cy PBAMLSG 07-04 467 A-ICE/ A-ICE/A-HA/HCT/Relapse CR1 TBI-Cy PBAMLSG 07-04 472 ICE/A-ICE/HCT CR1 TBI-Cy PBAMLSG 07-04 581 ICE/ICE/HCT CR1 TBI-Cy AMLSG 07-04 588 A-ICE/A-ICE/A-HA/HCT/Relapse/HU/GO-A-HAM CR1 TBI-Cy PB

AMLSG 07-04 908 ICE/ICE/HA/HA/HA/relapse/Flag-Ida/HCT/Relapse/palliative therapy RD1 TBI-Cy PB

AMLSG 07-04 152 AV-ICE/AV-ICE/AVA/HCT/Relapse/AraC, Idarubicin/HCT CR1 TBI-Cy PB

AMLSG 07-04 594 A-ICE/A-ICE/A-HA/HCT CR1 TBI-Cy PBAMLSG 07-04 969 ICE/ICE/HCT CR1 TBI-Cy PBAMLSG 07-04 1129 A-ICE/A-ICE/A-HA/A-HA/HCT CR1 Bu-Cy PBAMLSG 07-04 461 ICE/A-ICE/HA/HCT CR1 Bu-Cy PB

AMLSG 07-04 478 Dauno-AraC/Dauno-AraC/HCT/Relapse/Mito-FLAG/Flamsa/HCT/Relapse/HU CR1 Bu-Cy PB

AMLSG 07-04 331 A-ICE/A-ICE/A-HA/HCT CR1 Bu-Cy PB

HD98A 867 ICE/A-HAM/HCT/DLI/Relapse/DLI/3xMito-xantrone/HCT/Relapse/2xMitoxantron/HU CR1 Bu-Cy-RIT PB

AMLSG 07-04 892 ICE/A-ICE/A-HA/HCT/ CR1 RIT, Busulfan, Fludarabine, Campath PBAMLSG 07-04 800 ICE/ICE/HA/HCT CR1 Busulfan, Fludarabine PB

5


AMLSG 07-04 643 PrephaseAraC/ICE/ICE/HCT/Relapse/GO-HAM/Relapse/HAM/DLI CR1 Busulfan, Cyclophosphamide, ATG PB

AMLSG 07-04 844 A-ICE/A-ICE/A-HA/HCT/relapse/HAM/Relapse/Etoposide, AraC, Leustatin, Zavedos CR1 Treosulfane, Cyclophosphamide,

ATG PB

AMLSG 07-04 1031 A-ICE/A-ICE/HCT CR1 Fludarabine, Treosulfan PBAMLSG 09-09 75 GO-A-ICE/A-HAM/HCT/Relapse CR1 Fludarabine PBAMLSG 09-09 77 A-ICE/A-ICE/A-HA//HCT CR1 Fludarabine, Carmustin, Melphalan BMAMLSG 07-04 655 A-ICE/A-ICE/A-HA/A-HA/HCT CR1 Fludarabine, BCNU, Melphalan PBAMLSG 07-04 791 A-ICE/A-ICE/A-HA/HCT CR1 Flamsa PBAMLSG 09-09 6042 A-ICE/A-ICE//HAM/FLAG/HCT/Relapse/FLAG RD1 Flamsa BM

AMLSG 07-04 637 A-ICE/A-ICE/A-HA/HCT/DLI/Relapse/3xDLI/AraC/Relapse/LD AraC CR1 Flamsa-RIC PB

AMLSG 07-04 346 Prephase/Dauno-AraC/Dauno-AraC/HCT RD1 Flamsa, Bu, ATGAMLSG 07-04 275 Dauno-AraC/HCT RD1 ATG, Melphalan, Thiotepa AMLSG 09-09 152 GO-A-ICE/GO-A-ICE/HCT CR1 PB

AMLSG 07-04 419 ICE/ICE/I-MAC/HCT/Relapse/AraC+DLI/i.th.MTX,HU,AraC/CNS-Relapse/Radiatio CR1

AMLSG 07-04 2 Dauno-AraC/Dauno-AraC/A-HAM/HCT/ RD1 AMLSG 07-04 6 A-ICE/HAM/Flamsa/HCT/DLI/DLI/DLI RD1

AMLSG 07-04 831Dauno-AraC/GO-A-HAM/HCT/Relapse/Clofarabine,Ida,AraC/DLI/Relapse/Clofarabine,Ida,AraC/HCT

RD1

AMLSG 07-04 1086 A-ICE/S-HAM/HCT RD1 AMLSG 07-04 391 V-ICE/V-ICE/GO-A-HAM/HCT/HCT CR1 AMLSG 07-04 407 Prephase/V-ICE/ICE/HA/HCT CR1 PBAMLSG 07-04 553 ICE/ICE/HCT CR1

Abbreviations: ICE, idarubicin, cytarabine, etoposide; A, all-trans retinoic acid; AraC, Cytarabine; HU, hydroxyurea; Dauno, Daunorubicin; HCT, allogeneic hematopoietic cell transplantation; CR, complete remission; RD, refractory disease; HA, high-dose cytarabine; Flag-Ida, fludarabin, cytarabine, idarubicin, granulocyte colony stimulating factor; FLAMSA, fludarabine, amsaceinw, cytarabine, granulocyte colony stimulating factor; DLI, donor lymphocyte infusion; GO, gemtuzumab ozogamicin; HAM, high-dose cytarabine, mitoxantrone; i.th., intrathecal; MTX, methotrexate; MAC, cytarabine, mitoxantrone; V, valproic acid; TBI, total body irradiation; Cy, cyclophosphamide; BU, busulfane; ATG, anti-thymozyte globuline; RIT, radioimmuntherapy; BM, bone marrow stem cells; PB, peripheral blood stem cells.

6


Table S2. Cox regression analyses of DNMT3Amut transcript levels in peripheral blood samples as log 10 transformed continuous variable at different time-points during therapy and at the end of treatment. All patients were included, irrespective of response to induction or treatment.

Time-point DNMT3Amut

transcript levelsmedian, range

No ofpatients

RelapseHR (95% CI) P

DeathHR (95% CI) P

After induction I 500, 0 - 12950 86 0.99 (0.74 - 1.31) 0.91 0.93 (0.68 - 1.27) 0.66

After induction II 833, 0 – 22090 82 0.95 (0.75 - 1.20) 0.66 0.95 (0.72 - 1.25) 0.71

After consolidation I 783, 0 – 17560 66 1.39 (0.97 - 2.01) 0.07 1.45 (0.94 - 2.24) 0.10

After consolidation II 862, 0 – 12890 36 0.88 (0.58 - 1.32) 0.53 1.12 (0.57 - 2.20) 0.75

At the end of treatment 1916, 0 – 48780 54 1.21 (0.85 - 1.73) 0.29 1.1 (0.65 - 1.84) 0.72

Abbreviations: No, number; HR, Hazard Ratio; CI, confidence interval; P, p-value.

7


Figure S1. Number of bone marrow (BM) and peripheral blood (PB) samples obtained at the

time of diagnosis, during treatment and follow-up.

8


Figure S2. Consort diagram of patients which have been enrolled in one of three multicenter

treatment trials of the German-Austrian AML Study Group (AMLSG). Selection

criteria for our study were the presence of DNMT3A mutation R882C or R882,

and the availability of a diagnostic sample as well as at least two follow-up

samples.

9


Figure S3. Remission duration (S3A, S3C) and overall survival (S3B, S3D) according to

minimal residual disease (MRD) status of DNMT3Amut in bone marrow and

peripheral blood samples (S3A, S3B) and in peripheral blood samples only

(S3C, S3D) after induction therapy (RQ-PCR positive versus RQ-PCR

negative patients).

S3A Remission duration S3B Overall survival

S3C Remission duration S3D Overall survival

10


Figure S4. Remission duration (S4A) and overall survival (S4B) according to minimal

residual disease (MRD) status of DNMT3Amut in peripheral blood samples after

double induction therapy (log10 reduction <median versus log10 reduction

>median).


11



minimal residual disease (MRD) status of DNMT3Amut in bone marrow (S5A,

S5B) as well as bone marrow and peripheral blood samples (S5C, S5D) after

induction therapy according to the quartiles of the distribution.



12



residual disease (MRD) status of DNMT3Amut in peripheral blood samples only

(S6A, S6B) at the end of treatment (RQ-PCR positive versus RQ-PCR

negative patients).


13



residual disease (MRD) status of DNMT3Amut in peripheral blood samples at

the end of treatment (log10 reduction <median versus log10 reduction

>median).


14



minimal residual disease (MRD) status of DNMT3Amut in bone marrow samples

(S8A, S8B) as well as in bone marrow and peripheral blood samples (S8C,

S8D) at the end of treatment according to the quartiles of the distribution.



15


Figure S9. DNMT3A mutation (DNMT3Amut) transcript levels at the end of treatment and

during follow-up. Transcript levels are shown for bone marrow and peripheral

blood (S9A) as well as for patients in complete remission (CR) and relapse

(S9B).

S9A

16


S9B

17

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