Baseline clinical characteristics for the 81 CMML patients Routine diagnostic testing and statistical analyses... 3

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1 Next-Generation Sequencing Technology Reveals a Characteristic Pattern of Molecular Mutations in 72.8% of Chronic Myelomonocytic Leukemia (CMML) by Detecting Frequent Alterations in TET2, CBL, RAS, and RUNX1 Alexander Kohlmann et al. Supplementary Information Baseline clinical characteristics for the 81 CMML patients... 2 Routine diagnostic testing and statistical analyses... 3 Target genes for Next-Generation Sequencing (NGS)... 5 PCR primer design for next-generation sequencing... 6 PCR amplification protocols for next-generation sequencing... 9 Associations between molecular mutations and clinical parameters Survival analyses Detection of mutated subclones References

2 Baseline clinical characteristics for the 81 CMML patients Table S1: Clinical characteristics of the patient cohort. CMML Patients (n=81) Sex Male 57 (70.4%) Female 24 (29.6%) Age (years) Median 72.8 Range CMML 1 45 (55.6%) 2 36 (44.4%) MD/MP MD 63 (81.8%) MP 14 (18.2%) no data 4 Karyotype Normal or -Y 63 (81.8%) Aberrant 14 (18.2%) no data 4 White blood cell count (10 9 /liter) Median 13.4 Range no data 11 Platelets (10 9 /liter) Median 82.5 Range no data 13 Bone marrow blasts (%) Median 10 Range no data 27 Peripheral blood blasts (%) Median 3 Range 0-35 no data 48 Bone marrow monocytes (%) Median 9.5 Range 0-60 no data 30 Peripheral blood monocytes (%) Median 35 Range 4-71 no data 32 MD: myelodysplastic; MP: myeloproliferative 2

3 Routine diagnostic testing and statistical analyses Immunophenotyping Immunophenotyping was performed applying multiparameter flow cytometry and fivecolor combinations of monoclonal antibodies selected for the identification of MDSassociated aberrant immunophenotypes. 1;2 Cytogenetics and FISH Chromosome banding analysis and fluorescence in situ hybridization (FISH) was performed as published elsewhere. 3 Cases with loss of the Y-chromosome as the sole cytogenetic abnormality were assigned to the group with normal karyotype as loss of the Y-chromosome may occur in older males without hematologic disease. The detailed karyotype for each patient is given in the Supplemental Spreadsheet 1. FISH analyses were performed with probes for the detection of an ETV6 rearrangement or deletion (Abbott, Wiesbaden, Germany), deletion of the NF1 gene (Kreatech, Amsterdam, The Netherlands), and the TET2 gene using BAC RP11-351K6 on 4q24 (BlueGnome, Cambridge, UK). For those patients, where chromosomal abnormalities had been detected, either by metaphase cytogenetics or interphase-fish (combined patients n=22/77, 28.6%), the median number of malignant cells was 98% by chromosome banding analyses (20 metaphases per case analyzed) and 85% by FISH (100 cells per case analyzed), respectively (Supplemental Spreadsheet 1). 3

4 Molecular genetics Genomic DNA used for mutational analysis was collected from the purified fraction of mononuclear cells after Ficoll density centrifugation (QIAamp DNA Mini kit, Qiagen, Hilden, Germany). Isolation of mononuclear cells, mrna extraction, and random primed cdna synthesis was performed as described previously. 4 The entire coding region of the RUNX1 gene (GenBank entry D43968) was amplified from cdna using four separate polymerase chain reactions (PCRs) and analyzed by denaturing highperformance liquid chromatography (DHPLC) on the WAVE system (Transgenomic Inc., Omaha, NE). All fragments that revealed an aberrant dissociation behavior by DHPLC analysis were subsequently analyzed by Sanger sequencing. 5 Analysis for NRAS mutations and JAK2V617F was performed by LightCycler technology (Roche Applied Science, Mannheim, Germany) as described previously. 4;6 The analysis of KRAS mutations in codons 12, 13, and 61 was done as previously described. 4 DNA was extracted by standard methods. Exons 2 and 3 were amplified by PCR and subsequently analyzed by Sanger sequencing. Statistical analysis Dichotomous variables were compared between different groups using Fisher s exact test and continuous variables by Student s T-test. Survival was analyzed by the Kaplan Meier estimator and differences according to dichotomous variables by log rank test. Differences in survival according to continuous variables were analyzed by Cox regression analysis. Calculations were performed using SPSS V (SPSS Inc., Chicago, IL). Reported p-values are two-sided and not corrected for multiple testing. 4

5 Target genes for Next-Generation Sequencing (NGS) Table S2 lists the accession numbers for the 7 target genes selected for the NGS pipeline. Primer design was based on the Ensemble accession numbers listed below (Ensembl 53: Mar 2009). 7 Table S2. Ensemble accession numbers. Gene symbol CBL JAK2 KRAS MPL NRAS RUNX1 TET2 Ensemble ID ENSG ENSG ENSG ENSG ENSG ENSG ENSG

6 PCR primer design for next-generation sequencing Table S3 lists the primer pairs for 43 amplicons representing CBL, JAK2, KRAS, MPL, NRAS, RUNX1, and TET2. NGS-specific fusion sequences are highlighted accordingly. NGS-specific fusion sequences were as follows: primer A fusion sequence: 5' GCC TCC CTC GCG CCA TCA G 3' primer B fusion sequence: 5' GCC TTG CCA GCC CGC TCA G 3' The following gene-specific primer sequences were adapted from the literature: JAK2 exon 12: forward primer according to Scott et al. 8 exon 14: forward and reverse primer according to Levine et al. 9 RUNX1 exon 3, 5: according to Preudhomme et al. 10 exon 4, 6, 7, 8.1 forward, 8.2: according to Christiansen et al. 11 exon 8.1 reverse: according to SA6-fw primer by Matsuno et al. 12 NRAS exon 2: according to Paulsson et al. 13 KRAS exon 2, 3: according to Paulsson et al. 13 6

7 Table S3. Information on PCR primer and amplification protocols. Gene Strand Exon PCR Forward Sequence 5' -> 3' Reverse Sequence 5' -> 3' CBL CBL JAK JAK KRAS KRAS MPL NRAS NRAS RUNX1-3 1 RUNX1-4 2 RUNX1-5 1 RUNX1-6 1 RUNX1-8 4 RUNX1-8 4 RUNX1-7B 3 GCC TCC CTC GCG CCA TCA GGG AAA CAA GTC TTC ACT TTT TCT GT GCC TCC CTC GCG CCA TCA GGA TGC ATC TGT TAC TAT CTT TTG C GCC TCC CTC GCG CCA TCA GCT CCT CTT TGG AGC AAT TCA GCC TCC CTC GCG CCA TCA GTG CTG AAA GTA GGA GAA AGT GCA T GCC TTG CCA GCC CGC TCA GCA CCA GTA ATA TGC ATA TTA AAA CAA G GCC TTG CCA GCC CGC TCA GAA GAA AGC CCT CCC CAG TCC T GCC TCC CTC GCG CCA TCA GAG TAG GGG CTG GCT GGA TG GCC TTG CCA GCC CGC TCA GGC CTC ACC TCT ATG GTG GGA T GCC TTG CCA GCC CGC TCA GCA CAA AGA TCA TCC TTT CAG AGA A GCC TTG CCA GCC CGC TCA GCC TGT CCT CCC ACC ACC CTC GCC TTG CCA GCC CGC TCA GTG CCA TGA AAC GTG TTT CAA GC GCC TTG CCA GCC CGC TCA GCC CAA GGA ATC TGA GAC ATG GTC C GCC TTG CCA GCC CGC TCA GGG CAG TGG GCT CCA TCT GGT AC GCC TTG CCA GCC CGC TCA GAT GGA GAA CTG GTA GGA GCC GCC TTG CCA GCC CGC TCA GGG GCT TGT CGC GAA CAG GAG G GCC TTG CCA GCC CGC TCA GCC AGC TCA GCT GCA AAG AAT GTG GCC TCC CTC GCG CCA TCA GAT TCA ACT AGA GGG CAG CCT TG GCC TCC CTC GCG CCA TCA GCA CAA GAA AGT AGA GGG TAT TCC GCC TCC CTC GCG CCA TCA GCA CAT AAC TGC AGT GGG CCT G GCC TCC CTC GCG CCA TCA GCC TGT GAG ATC ACT CAC CCA TC GCC TCC CTC GCG CCA TCA GAA TTC TGT TCA GGT TCC AGC AG GCC TCC CTC GCG CCA TCA GGG GAA GTG AAA ATA GAG GGT AAA C GCC TTG CCA GCC CGC TCA GCC GAA TTT TCC AAG GTT ATT ACA GCC TTG CCA GCC CGC TCA GAT GGA TTT TGC CAG TCT CCT AA GCC TTG CCA GCC CGC TCA GCC AAT GTC ACA TGA ATG TAA ATC GCC TTG CCA GCC CGC TCA GTA CAG TGT TTT CAG TTT CAA AAA GCC TCC CTC GCG CCA TCA GTG TAT TAA CCT TAT GTG TGA CAT GTT C GCC TCC CTC GCG CCA TCA GCT GTG TTT CTC CCT TCT CAG GAT TC GCC TTG CCA GCC CGC TCA GGT CAC AGA GCG AAC CAA GAA T GCC TCC CTC GCG CCA TCA GGT ACT GTA GAT GTG GCT CGC CA GCC TCC CTC GCG CCA TCA GCC CCT TAC CCT CCA CAC C GCC TCC CTC GCG CCA TCA GGC TGT TTG CAG GGT CCT AA GCC TCC CTC GCG CCA TCA GCA TTG CTA TTC CTC TGC AAC C GCC TCC CTC GCG CCA TCA GTG TTC AGG CCA CCA ACC TCA TTC GCC TCC CTC GCG CCA TCA GCC CTC CCT GCT CCC CAC AA GCC TCC CTC GCG CCA TCA GCG CAA CCT CCT ACT CAC TTC CG GCC TCC CTC GCG CCA TCA GGT TCC AAG CCA GCT CGC CC GCC TCC CTC GCG CCA TCA GCC CAC CCC ACT TTA CAT ATA ATT G GCC TTG CCA GCC CGC TCA GAC TGT GCG TTT TAT TCC TCC AT GCC TTG CCA GCC CGC TCA GAA TTA GCA CTT TTC CCC TCC TG GCC TTG CCA GCC CGC TCA GGT TAG AGG TCT GTG CGG AAT TG GCC TTG CCA GCC CGC TCA GTT TTG TTT TAA ATA CCG TTC AGA GC GCC TTG CCA GCC CGC TCA GAT GGA TTA GGA CTC TGG GAA GG GCC TTG CCA GCC CGC TCA GCC TGG TTT CAG ATA GTG CTG TG 7

8 TET TET TET TET TET TET TET TET TET TET TET TET TET GCC TCC CTC GCG CCA TCA GGA TTC TGA AGG GTC GAG ACA AG GCC TCC CTC GCG CCA TCA GTC ACA AAT GTA CCA AGT TGA AAT G GCC TCC CTC GCG CCA TCA GTG AGC CAT TTT CAA ACT CAC AC GCC TCC CTC GCG CCA TCA GCA AAA TCA AGC GAG TTC GAG GCC TCC CTC GCG CCA TCA GAT AAT GTG ATC CCA AAG CAA GA GCC TCC CTC GCG CCA TCA GAA AAG CAT GCT GCT CTA AGG TG GCC TCC CTC GCG CCA TCA GAT GGA GCA GCA TCT GAA GCA GCC TCC CTC GCG CCA TCA GAA CAG CTG CTT CTG TTC TCA AT GCC TCC CTC GCG CCA TCA GTG CCT CTT GAA TTC ATT TGC TA GCC TCC CTC GCG CCA TCA GAG TGA CCC TTG TTT TGT TTT GG GCC TCC CTC GCG CCA TCA GGC ACA GCC TAT ATA ATG CTA TCC A GCC TCC CTC GCG CCA TCA GAG GGG AAT AAT CTA ACT GAT AGT CTC T GCC TCC CTC GCG CCA TCA GGT TTT CGG TGT AAG AGT AAA ACT AAC T GCC TCC CTC GCG CCA TCA GCC TGT AGT TGA GGC TGT AAT GTC GCC TCC CTC GCG CCA TCA GTG CCA TTC AGG TAC TGA GTT CT GCC TCC CTC GCG CCA TCA GAA AGA TAC CTG TTT CTG TTC TCT CTT GCC TCC CTC GCG CCA TCA GCA CTT CAG ATA TCT ATG GAA GCA C GCC TCC CTC GCG CCA TCA GAG CCA AGG TTT GGA AAT AGC C GCC TCC CTC GCG CCA TCA GTC TCA CAT AAT CCA TAA CTA CAG TGC GCC TCC CTC GCG CCA TCA GAG AGG ACA ACG ATG AGG TCT G GCC TCC CTC GCG CCA TCA GAA GCC AAA ATG GCT GAA AAA G GCC TTG CCA GCC CGC TCA GCT GGA GAT GTT GGT CCA CTG TA GCC TTG CCA GCC CGC TCA GGT TTG TGC TGC CTG TTT ATG AG GCC TTG CCA GCC CGC TCA GGT ACT TCC TCC AGT CCC ATT TG GCC TTG CCA GCC CGC TCA GGT TGT GAC TTC TGC TCC TGT TC GCC TTG CCA GCC CGC TCA GTT TGG GGT TGC TGT GTT TG GCC TTG CCA GCC CGC TCA GAA GAG CCT TAT GGT CAA ATA ACG GCC TTG CCA GCC CGC TCA GTG AGT CTT GAC AGG TGT ATC CAA GCC TTG CCA GCC CGC TCA GGA CAC AAG CAT CGG TAA CTT GA GCC TTG CCA GCC CGC TCA GGT AAC CCA ATT CTC AGG GTC AG GCC TTG CCA GCC CGC TCA GAC CAA AGA TTG GGC TTT CCT AT GCC TTG CCA GCC CGC TCA GTG TCA TAT TGT TCA CTT CAT CTA AGC GCC TTG CCA GCC CGC TCA GTT TTT GGA CAT AGG TCA TTA GTA ACA A GCC TTG CCA GCC CGC TCA GAG TGT GAG AAC AGA CTC AAC AGC GCC TTG CCA GCC CGC TCA GCT AGT TTC CTT TGT CGG CAA GT GCC TTG CCA GCC CGC TCA GAA GTT GAT GGG GGC AAA AC GCC TTG CCA GCC CGC TCA GCA GCT TGA GAT GAG GTG GAA TA GCC TTG CCA GCC CGC TCA GAT TTT GGT TTC CAT AAC CTA AGT ATT GCC TTG CCA GCC CGC TCA GGG GCA TGA AGA GAG CTG TTG GCC TTG CCA GCC CGC TCA GAA TGT CAG GAT CCA GAA AGC TC GCC TTG CCA GCC CGC TCA GGT CTG GGC CAT ACT TTT CAC GCC TTG CCA GCC CGC TCA GTT GTG GTC TTT TCA AGT GAG GT 8

9 PCR amplification protocols for next-generation sequencing PCR protocols were performed with 50 ng of genomic template DNA. All PCR master mixes were prepared according to the manufacturer s recommendations. Protocols 1, 2, 3, and 5 were performed using the Taq PCR Master Mix kit (Qiagen, Hilden, Germany), protocol 4 was performed using the GC-RICH PCR System kit (Roche Applied Science, Penzberg, Germany), respectively. All PCR reactions were performed on the 96-Well GeneAmp PCR System 9700 (Applied Biosystems, Foster City, CA). All protocols included a final cooling step at 4 C after final elongation. Protocol #1 (touchdown, Δ-0.5 C): Step Cycles Time (min) Temperature Cycles Time (min) Temperature Initial Denaturation 1 5: C 1 5: C Denaturation Annealing Elongation 10 0:30 0:30 0: C 60.0 C 55.0 C 72.0 C 25 0:30 0:30 0: C 55.0 C 72.0 C Final Elongation 1 7: C Protocol #2: Step Cycles Time (min) Temperature Initial Denaturation 1 5: C Denaturation Annealing Elongation 35 0:45 0:45 0: C 58.0 C 72.0 C Final Elongation 1 10: C 9

10 Protocol #3: Step Cycles Time (min) Temperature Initial Denaturation 1 5: C Denaturation Annealing Elongation 35 0:45 0:45 0: C 59.0 C 72.0 C Final Elongation 1 10: C Protocol #4: Step Cycles Time (min) Temperature Initial Denaturation 1 5: C Denaturation Annealing Elongation 40 1:00 1:00 1: C 60.0 C 72.0 C Final Elongation 1 10: C Protocol #5: Step Cycles Time (min) Temperature Initial Denaturation 1 5: C Denaturation Annealing Elongation 35 0:45 0:45 0: C 62.0 C 72.0 C Final Elongation 1 10: C 10

11 Associations between molecular mutations and clinical parameters With respect to associations between molecular mutations and clinical parameters, no significant associations were observed between any of the point mutations or deletions and the karyotype or gender. There were also no associations detected between molecular aberrations and the diagnostic categories CMML-1 and CMML-2, with exception of JAK2V617F, being found more often in CMML-1 (n=7) than in CMML-2 (n=1; chi-square test: p=0.07). An analysis according to MP-CMML and MD-CMML status detected JAK2V617F more often in MP-CMML (23.1 vs. 6.3%; chi-square test; p=0.089). Relating cellular peripheral blood or bone marrow components, such as leukocytes, blast cells, monocytes, thrombocytes, and hemoglobin to the respective genetic aberrations revealed a significant positive correlation between mutations in JAK2 and thrombocyte count (t-test; p=0.014). TET2-mutated cases were observed to carry a lower percentage of bone marrow monocytes (6.7 vs. 13.2%; t-test; p=0.017). 11

Survival analyses A mutational analysis taking both TET2 and CBL into account revealed that patients with mutations in TET2 and/or CBL had a better overall survival (p=0.048) (Supplemental Figure 1).

12 Survival analyses A mutational analysis taking both TET2 and CBL into account revealed that patients with mutations in TET2 and/or CBL had a better overall survival (p=0.048) (Supplemental Figure 1). TET2 and/or CBL mutated wild type p=0.048 Supplemental Figure 1. Kaplan Meier survival estimates according to TET2 and/or CBL mutations. Data are shown for overall survival of CMML patients (median overall survival: vs years; alive at 2 yrs: 78% vs. 60%). Cases harboring mutations in TET2 and/or CBL are represented by the dashed line. The solid line indicates cases with wild type TET2 and/or CBL. Tick marks represent patients whose data were censored at the last time they were known to be alive. 12

Also, a model taking three genes into account (TET2 and/or CBL and/or KRAS) stratified the patients into distinct prognostic subgroups (p=0.012) (Supplemental Figure 2).

13 Also, a model taking three genes into account (TET2 and/or CBL and/or KRAS) stratified the patients into distinct prognostic subgroups (p=0.012) (Supplemental Figure 2). Of note, this model also remained significant when limited to the smaller cohort of 31 patients that had received active therapy (p=0.022). TET2 and/or CBL and/or KRAS mutated wild type p=0.012 Supplemental Figure 2. Kaplan Meier survival estimates according to TET2 and/or CBL and/or KRAS mutations. Data are shown for overall survival of CMML patients (median overall survival: vs years; alive at 2 yrs: 80% vs. 55%). Cases harboring mutations in TET2 and/or CBL and/or KRAS are represented by the dashed line. The solid line indicates cases with wild type TET2, CBL, and/or KRAS, respectively. Tick marks represent patients whose data were censored at the last time they were known to be alive. 13

14 Detection of mutated subclones As given in Supplemental Table S4, there were 17 double mutations in 16 patients, i.e. 2 or more mutations per gene: CBL: n=3 (1 case with 3 mutations), KRAS: n=1, NRAS: n=5 (1 case with 3 mutations), and TET2: n=8 cases (1 case with 4 mutations). In 6 cases the mutations were located within the same initial PCR amplicon: CBL: n=1, KRAS: n=1, and NRAS: n=4. Upon further investigation of the detected mutations we observed that in all 6 cases, two or more subclones were obtained, i.e. the distinct mutations were located in separate reads derived from the same amplicon (Supplemental Figure 3). However, despite the median read length of ~245 bp the reads were too short to correlate aberrations with a monoallelic or biallelic status. It could be speculated though, that for example in case 74 the three variances in exon 11 would be monoallelic since they occurred in a similar frequency of reads (Supplemental Table 4). However, this can t be answered conclusively, because these mutations were spread over three distinct PCR amplicons. Overall, NGS here allowed new insights into mutations and additionally the distinction of separate subclones with mutations derived from the same PCR amplicon. Supplemental Figure 3. Detection of mutated subclones. (A) (F) Detected subclones in cases with two or more mutations in CBL, KRAS, and NRAS. Each graph depicts the observed mutations as highlighted in Supplemental Table S4. 14

15 Table S4. Cases with two or more mutations in the same gene. Case Gene Status Mutation 1 [percentage] Mutation 2 [percentage] Mutation 3 [percentage] Mutation 4 [percentage] Patient 13 CBL separate amplicons exon 8; Cys404Tyr [32.01%] exon 9; Arg420Gln [33.54%] Patient 20 CBL same amplicon, two subclones exon 8; Cys384Arg [84.57%] exon 8; Met400Arg [6.3%] Patient 39 CBL separate amplicons exon 8; His398Arg [87.69%] exon 9; delile [5.29%] Patient 31 Patient 1 Patient 4 KRAS NRAS NRAS same amplicon, two subclones same amplicon, three subclones same amplicon, two subclones exon 2; Gly12Cys [9.08%] exon 2; Leu19Phe [17.27%] exon 2; Thr20Ser [17.95%] exon 2; Gly12Asp [2.18%] exon 2; Gly12Cys [15.48%] exon 2; Gly13Asp [1.69%] exon 2; Gly12Asp[21.15%] exon 2; Gly12Ser [11.1%] Patient 12 NRAS separate amplicons exon 2; Gly13Cys [13.89%] exon 3; Gly60Glu [20.02%] Patient 18 Patient 19 NRAS NRAS same amplicon, two subclones same amplicon, two subclones exon 2; Gly12Val [1.33%] exon 2; Gly13Asp [42.8%] exon 2; Gly12Asp [3.09%] exon 2; Gly12Val [30.17%] Patient 19 TET2 separate amplicons exon 3; Gln440X [44.38%] exon 11; Arg1896Gly [49.85%] Patient 74 TET2 separate amplicons exon 5; Cys1193Phe [4.23%] exon 11; Arg1572Trp [40.38%] exon 11; Tyr1628X [40.47%] exon 11; Lys1905Glu [44.17%] Patient 22 TET2 separate amplicons exon 6; Arg1261Cys [22.95%] exon 10; Arg1404X [44.8%] Patient 62 TET2 separate amplicons exon 3; Gln876X [41.81%] exon 11; delasn1613 FS [56.25%] Patient 73 TET2 separate amplicons exon 6; Trp1233Gly [26.06%] exon 9; Gly1361Asp [10.3%] Patient 75 TET2 separate amplicons exon 3; Trp1003X [23.85%] exon 7; Ser1303Arg [29.66%] Patient 76 TET2 separate amplicons exon 3; delcys724 FS [18.64%] exon 3; delala1096 FS [52.7%] Patient 81 TET2 separate amplicons exon 10; Arg1452X [42.25%] exon 11; Thr1884Ala [50.33%] 15

16 A CBL Case #20 exon 8; Cys384Arg exon 8; Met400Arg B KRAS Case #33 exon 2; Gly12Cys exon 2; Leu19Phe exon 2; Thr20Ser 16

17 C NRAS Case #1 exon 2; Gly12Cys exon 2; Gly12Asp exon 2; Gly13Asp D NRAS Case #4 exon 2; Gly12Asp exon 2; Gly12Ser 17

18 E NRAS Case #18 exon 2; Gly13Asp exon 2; Gly12Val F NRAS Case #19 exon 2; Gly12Val exon 2; Gly12Asp 18

19 References 1. Kern W, Haferlach C, Schnittger S, Haferlach T. Clinical utility of multiparameter flow cytometry in the diagnosis of 1013 patients with suspected myelodysplastic syndrome: correlation to cytomorphology, cytogenetic, and clinical data. Blood 2009;(ASH Annual Meeting Abstracts), Nov 2009; 114: 595.: 2. van de Loosdrecht AA, Alhan C, Bene MC et al. Standardization of flow cytometry in myelodysplastic syndromes: report from the first European LeukemiaNet working conference on flow cytometry in myelodysplastic syndromes. Haematologica 2009;94: Schoch C, Schnittger S, Bursch S et al. Comparison of chromosome banding analysis, interphase- and hypermetaphase-fish, qualitative and quantitative PCR for diagnosis and for follow-up in chronic myeloid leukemia: a study on 350 cases. Leukemia 2002;16: Schnittger S, Schoch C, Dugas M et al. Analysis of FLT3 length mutations in 1003 patients with acute myeloid leukemia: correlation to cytogenetics, FAB subtype, and prognosis in the AMLCG study and usefulness as a marker for the detection of minimal residual disease. Blood 2002;100: Dicker F, Haferlach C, Kern W, Haferlach T, Schnittger S. Trisomy 13 is strongly associated with AML1/RUNX1 mutations and increased FLT3 expression in acute myeloid leukemia. Blood 2007;110: Bacher U, Haferlach T, Schoch C, Kern W, Schnittger S. Implications of NRAS mutations in AML: a study of 2502 patients. Blood 2006;107: Hubbard TJ, Aken BL, Ayling S et al. Ensembl Nucleic Acids Res. 2009;37:D690-D Scott LM, Tong W, Levine RL et al. JAK2 exon 12 mutations in polycythemia vera and idiopathic erythrocytosis. N.Engl.J Med. 2007;356: Levine RL, Wadleigh M, Cools J et al. Activating mutation in the tyrosine kinase JAK2 in polycythemia vera, essential thrombocythemia, and myeloid metaplasia with myelofibrosis. Cancer Cell 2005;7: Preudhomme C, Warot-Loze D, Roumier C et al. High incidence of biallelic point mutations in the Runt domain of the AML1/PEBP2 alpha B gene in Mo acute myeloid leukemia and in myeloid malignancies with acquired trisomy 21. Blood 2000;96: Christiansen DH, Andersen MK, Pedersen-Bjergaard J. Mutations of AML1 are common in therapy-related myelodysplasia following therapy with alkylating agents 19

20 and are significantly associated with deletion or loss of chromosome arm 7q and with subsequent leukemic transformation. Blood 2004;104: Matsuno N, Osato M, Yamashita N et al. Dual mutations in the AML1 and FLT3 genes are associated with leukemogenesis in acute myeloblastic leukemia of the M0 subtype. Leukemia 2003;17: Paulsson K, Horvat A, Strombeck B et al. Mutations of FLT3, NRAS, KRAS, and PTPN11 are frequent and possibly mutually exclusive in high hyperdiploid childhood acute lymphoblastic leukemia. Genes Chromosomes.Cancer 2008;47:

c Tuj1(-) apoptotic live 1 DIV 2 DIV 1 DIV 2 DIV Tuj1(+) Tuj1/GFP/DAPI Tuj1 DAPI GFP

c Tuj1(-) apoptotic live 1 DIV 2 DIV 1 DIV 2 DIV Tuj1(+) Tuj1/GFP/DAPI Tuj1 DAPI GFP Supplementary Figure 1 Establishment of the gain- and loss-of-function experiments and cell survival assays. a Relative expression of mature mir-484 30 20 10 0 **** **** NCP mir- 484P NCP mir- 484P b Relative