Supplementary information summary : TABLES:

1

Downregulation of specific miRNAs in hyperdiploid multiple myeloma mimics the oncogenic effect of IgH translocations occurring in the non-

hyperdiploid subtype

Ana Rio-Machin 1, Bibiana Ferreira 1, Travis Henry 2, Gonzalo Gómez-López 3, Xabier Agirre 4, Sara Alvarez 1,

Sandra Rodriguez-Perales 1, Felipe Prosper 4, M José Calasanz 5, Joaquín Martínez 6, Rafael Fonseca 2, and Juan C

Cigudosa 1

1 Molecular Cytogenetics Group, Centro Nacional Investigaciones Oncologicas (CNIO), Calle Melchor Fernández Almagro 3, 28029, Madrid,

Spain ; Centro de Investigaciones de Enfermedades Raras (CIBERER), Madrid, Spain.2 Division of Hematology–Oncology, Mayo Clinic, 13400 E. Shea Blvd. Scottsdale, AZ 85259, Arizona, USA.3 Bioinformatics Unit, Centro Nacional Investigaciones Oncologicas (CNIO), Calle Melchor Fernández Almagro 3, 28029, Madrid, Spain.4 Foundation for Applied Medical Research, Division of Cancer and Area of Cell Therapy and Hematology Service, Clínica Universitaria,

Universidad de Navarra, Avenida de Pío XII 36, 31008, Pamplona, Spain.5 Department of Genetics, University of Navarra, Campus Universitario, 31080, Pamplona, Spain.6 Hematology Service, Hospital Universitario 12 de Octubre, Avda. de Córdoba s/n, 28041, Madrid, Spain.

Corresponding author: Juan C. Cigudosa

Molecular Cytogenetics GroupHuman Cancer Genetics ProgramCentro Nacional de Investigaciones Oncológicas (CNIO)C/Melchor Fernández Almagro, 328029 Madrid, SpainPhone #: 34 912246900Fax #: 34912246923Mail: [email protected]

2

SUPPLEMENTARY INFORMATION SUMMARY:

TABLES:

Supplementary Table 1: Description of the samples: their clinical origin and use in this work.

Supplementary Table 2: Cytogenetic and clinical characteristics of the evaluated patients in the miRNAs microarray.

Supplementary Table 3: Sequence of the primers used for the bisulphite sequencing.

Supplementary Table 4: Locations of the miRNAs consensus binding sites in the 3’UTR regions of the selected target genes.

Supplementary Table 5: Microarray supervised analysis : significantly differentially expressed miRNAs.

Supplementary Table 6: Predicted Target Genes that are overexpressed in h-MM vs nh-MM (FDR<0.01 )

FIGURES:

Supplementary Figure 1: Validation II.

Supplementary Figure 2: Methylation status of hsa-miR-152 and hsa-miR339.

Supplementary Figure 3: Luciferase assay.

Supplementary Figure 4: Complete Western Blot gel images of Figure 2B.

Supplementary Figure 5: Densitometric analysis I.

Supplementary Figure 6: OH-2 cell line.

Supplementary Figure 7: Densitometric analysis II.

Supplementary Figure 8: Target genes and miRNAs expression in MM cases.

Supplementary Table 1. Description of the samples: their clinical origin and use in this work

DISCOVERY SERIES VALIDATION SERIES METHYLATION SERIES

Clincal Group

Department of Genetics,

University of Navarra, Pamplona,

Spain

Division of Hematology-Oncology,

Mayo Clinic, Scottsdale, Arizona, USA

Hematology Service, Hospital

Universitario 12 de Octubre,

Madrid, Spain

Number of

samples

nh-MM = 36

h-MM =17

nh-MM = 10

h-MM =11

nh-MM = 10

h-MM =8

Cell lines

nh-MM: JJN3, L363, OPM-2,

K620; KMS28BM, KMS28PE

h-MM: OH-2

None

nh-MM: L363, OPM-2, SK-MM-2;

KMS28BM, H929

h-MM: OH-2

3

Supplementary Table 2. Cytogenetic and clinical characteristics of the evaluated patients in the miRNAs microarray

nh-MM CASES IgH marker

Number of chromosomes Diagnosis

1 nh + IgH 46 De novo2 nh + IgH 46 De novo3 nh - 46 De novo4 nh + FGFR3 (TACC3) 48 De novo5 nh + IgH 46 De novo6 nh - 46 De novo7 nh - 46 De novo8 nh + MAFB 46 De novo9 nh + IgH 46 De novo

10 nh - 46 De novo11 nh + IgH 46 De novo12 nh - 46 De novo13 nh - 46 De novo14 nh + MAFB 48 De novo15 nh - 46 De novo16 nh - 46 De novo

17 nh + CCND1 46 [83%] 45 [17%] De novo

18 nh - 46 De novo19 nh + IgH 46 De novo20 nh + IgH 46 De novo21 nh + IgH 46 De novo22 nh + IgH 46 De novo23 nh - 46 De novo24 nh - 46 De novo25 nh + FGFR3 (TACC3) 48 De novo26 nh - 46 De novo27 nh + IgH 46 De novo28 nh + FGFR3 (TACC3) 47 De novo29 nh + CCND1 46 De novo30 nh + FGFR3 (TACC3) 46 De novo31 nh + FGFR3 (TACC3) 46 De novo32 nh + CCND1 50 De novo33 nh + CCND1 46 De novo34 nh + CCND1 46 De novo

35 nh + FGFR3 (TACC3) 46 [60%] 44 [40%] De novo

36 nh + CCND1 46 De novo

h-MM CASES IgH marker

Number of chromosomes Diagnosis

1 h - 47 De novo2 h - 53 De novo3 h - 51 De novo4 h - 50 De novo

5 h - 54 [80%] 47[20%] De novo

6 h - 53 De novo7 h - 51 De novo8 h - 51 De novo9 h - 52 De novo

10 h - 54 De novo

11 h - 50 35%] 54 [65%] De novo

12 h - 54 De novo13 h - 53 De novo14 h - 48 De novo

15 h - 53 [90%] 54 [10%] De novo

16 h -46 [20%] 45[66%]

52[14%]De novo

17 h - 50,XX De novo

4

GENES TECHNIQUE PRIMERS

hsa-miR-339 BSP

hsa-miR-339-M-Fw 5´-GGTTTTTGTAGTCGCGATAC-3´

hsa-miR-339-M-Rv 5´-AACTAACACGAACTTCCGC-3´

hsa-miR-339-U-Fw 5´-GGTGGTTTTTGTAGTTGTGATAT-3´

hsa-miR-339-U-Rv 5´-CAACTAACACAAACTTCCACAA-3´

hsa-miR-152 BSP

hsa-miR-152-M-Fw 5´-CGCGGAATCGTAATTTATTC -3´

hsa-miR-152-M-Rv 5´-ACCCGAAAAAAAAAATTCGT -3´

hsa-miR-152-U-Fw 5´-TTTTGTGGAATTGTAATTTATTT -3´

hsa-miR-152-U-Rv 5´-ACCCAAAAAAAAAAATTCATCCC-3´

Supplementary Table 3. Sequence of the primers used for the bisulphite sequencing

5

Supplementary Table 4. Locations of the miRNAs consensus binding sites in the 3’UTR regions of the selected target genes.

GENE3’UTR REGION

(miRNA predicted recognition site is underlined)miRNA

Modification of the

binding site

(directed mutagenesis)

TACC3

(4p16.3)

5’AGAGAACGAGGAGCTGACCAGGATCTGCGACGACCTCATCTCCAAGATGGAGAAGATCTGACCTCCACGGAGC

CGCTGTCCCCGCCCCCCTGCTCCCGTCTGTCTGTCCTGTCTGATTCTCTTAGGTGTCATGTTCTTTTTTCTGTCT

TGTCTTCAACTTTTTTAAAAACTAGATTGCTTTGAAAACATGACTCAATAAAAGTTTCCTTTCAA 3’

hsa-miR-425

GTGTCAT

GAACCTT

CCND1

(11q13)

5’[…]GAAGTGTTGAAGGGAGGTGGCAAGAGTGTGGAGGCTGACGTGTGAGGGAGGACAGGCGGGAGGAGGTGTG

AGGAGGAGGCTCCCGAGGGGAAGGGGCGGTGCCCACACCGGGGACAGGCCGCAGCTCCATTTTCTTATTGCGCTG

CTACCGTTGACTTCCAGGCACGGTTTGGAAATATTCACATCGCTTCTGTGTATCTCTTTCACATTGTTTGCTGCT

ATTGGAGGATCAGTTTTTTGTTTTACAATGTCATATACTGCCATGTACTAGTTTTAGTTTTCTCTTAGAACATTG

TATTACAGATGCCTTTTTTGTAGTTTTTTTTTTTTTTATGTGATCAATTTT […] 3’

hsa-miR-425

TGTCAT

CGAAGT

MAFB

(20q11.2-

q13.1)

5’[…]GACTACAGCCTTGTCTTATGGTCAAATTGATACCCTTAATAAGAAAGGAAAGGAAAGGAAAACAGATCCT

CCCCTCTGCTTTTTATTGTAACCAGAATCACCCTGAGGTCCCTTCTGAACCCTCTGGGCCTGCGCTAATTGTAGG

AGCCACAGCGCTCCTAGGGTGAGAGGCTTAGCCATCCCTGACCCTGGCAGTGCACTGGTAAGCAGACACTGCACT

GAACCAACTGCTATGCTCAGAATGTACCAGAAACCCAAACATTGGCAAGTAATTTTGCAACTTTCAAGTGCGTTC

TTTAGACCAATGCATTGCGTTTCTTTCCC […] 3’

hsa-miR-152

TGCACTGA

TTGGCAGA

FGFR3

(4p16.3)

5’[…]TGGGGGGACCCAGTGCAGAATGTAAGTGGGCCCACCCGGTGGGACCCCCGTGGGGCAGGGAG

CTGGGCCCGACATGGCTCCGGCCTCTGCCTTTGCACCACGGGACATCACAGGGTGGGCCTCGGCCCC

TCCCACACCCAAAGCTGAGCCTGCAGGGAAGCCCCACATGTCCAGCACCTTGTGCCTGGGGTGTTAG

TGGCACCGCCTCCCCACCTCCAGGCTTTCCCACTTCCCACCCTGCCCCTCAGAGACTGAAATTACGG

GTACCTGAAGATGGGAGCCTTTACCTTTTATGCAAAAGGTTT […] 3’

hsa-miR-24

CTGAGCC

CATACTC

6

Supplementary Table 5. Microarray supervised analysis : significantly differentially expressed miRNAs

(FDR < 0.05)

miRNA Up regulated in

nh-MM vs h-MMq- value (%) Genomic location Clustered miRNAs

hsa-miR-425 0.000 3p21.31 hsa-miR-191

hsa-miR-152 0.000 17q21.32 NO

hsa-miR-24 0.000 9q22.32hsa-miR-23, hsa-miR-27

and hsa-miR-3074

hsa-miR-339 0.000 7p22.3 NO

hsa-miR- 125a 0.000 19q13.41 hsa-miR-99b and hsa-let-7e

hsa-let-7 a y d 0.000 9q22.32 hsa-let-7a, hsa-let-7f and hsa-let-7d

hsa-miR-33b 0.000 17p11.2 NO

hsa-miR-331 0.000 12q22 hsa-miR-3685

hsa-miR-185 0.000 22q11.21 NO

hsa-miR-186 0.000 1p31.1 NO

hsa-miR-195 0.000 17p13.1 hsa-miR-497

hsa-miR-654 0.000 14q32.31

hsa-mir-543, hsa-mir-495, hsa-mir-376c,

hsa-mir-376a-2 and b, hsa-mir-376a-1, hsa-

mir-300, hsa-mir-1185-1 and 2, hsa-mir-

381, hsa-mir-487b, hsa-mir-539, hsa-mir-

889, hsa-mir-544a, hsa-mir-655

hsa-miR-15a 0.000 13q14.2 hsa-miR-16-1

hsa-miR-140 0.000 16q22.1 NO

hsa-miR-21 4.401 17q23.1 NO

hsa-miR-107 4.401 10q23.31 NO7

Supplementary Figure 1:

Supplementary Figure 1: Validation II. Expression levels of the selected miRNAs in a different series of nh-MM cases

and h-MM cases were assessed by real-time PCR. The result of the microarray was validated again.

miRNA EXPRESSION IN THE VALIDATION SERIES

nh-MM

h-MM

***

***

***

***

***

* < 0,05 ** < 0,01*** < 0,001

8

CpG

1Cp

G 2

CpG

3

CpG

4

CpG

5

CpG

6

CpG

7

CpG

8Cp

G 9

CpG

10

CpG

11

Non-Hyperdiploid MM cases

+ control

Hyperdiploid MM cases

hsa-miR-339


hsa-miR-152

CpG

1

CpG

2

CpG

3

CpG

4Cp

G 5

CpG

6Cp

G 7

CpG

8

CpG

9Cp

G 1

0Cp

G 1

1Cp

G 1

2

CpG

13

CpG

14

CpG

15

CpG

16

CpG

17

+ control

Non-Hyperdiploid MM cases

Hyperdiploid MM cases

Supplementary Figure 2: Methylation status of hsa-miR-152 and hsa-miR339. Bisulphite sequencing of the

hsa-miR-339 and hsa-miR-152 CpG island regions in positive methylated control (+ control) and 18 MM cases

(10 nh-MM and 8 h-MM cases). Each circle indicates a CpG dinucleotide (black circle: methylated CpG; open

circle: unmethylated CpG). Methylation of the promoter region of miR152 seems not be demonstrated in the

primary samples, and, although the miR339 promoter shows methylated CpGs, no clear differences are seen

when we compare the two MM subtypes.

9

Supplementary Table 6. Predicted Target Genes that are overexpressed in h-MM vs nh-MM (FDR<0.001 ) using expression

dataset provided by Chng et al. 2007 (miRanda (miRBase v12.0) and TargetScan v 5.1)

ANKRD47ATP5SCCDC73CHMP5CYFIP1DDX10DDX49DIMT1LDUSP2ELOVL5FZR1HERC2KIAA0652MCA2_HUMANPPP1R14BPTCH1PTOV1RNF14RPL13ARPS13RPS17RPS6

ANAPC2C14orf2C19orf53C3orf54CCNB1IP1CCRL2CD151CYB5R4DLEC1EGLX_HUMANFPGSGTF2A2HIST1H2ABHIST2H2ACHOXA5IMPDH2LOC730029MAK10MST1NP_079413.3O95745_HUMANPLAA

ATP5DC14orf2C6orf1C7orf26C9orf16CDK5CLK3CLPPDDX49ENGFBXL12HMHA1HRASIDH2IHPK2

hsa-miR-425 hsa-miR-152 hsa-miR-24

10

ADPGKC7orf26C9orf16CDC37L1CDC37L1DNM2DNM2ESRRAF12FBXL12IFRD2LSM4NUP210OAZ2OTUB1

AMIGO3APEHC19orf58C9orf48CD151CLPBDLC1DPM2EEF1GENDOGFPGSHCN2HNRPA1IL11RAMAN2A2NP_060390.3NP_060390.3OTUB1PEX16STK11STOML2TKTTMED1WDR74

ABCB8ABCB8AVENBZW2C14orf2C19orf53CCDC73CLP1COX5ADPM2EIF3S12GADD45GIP1GTF2A2HGFHIGD2AHIST2H2BAIHPK2

hsa-miR-125ahsa-miR-339 hsa-let-7

hsa-miR-425PSMB7FAM162AATP5LRPL24NDUFS7RPL13ARPS6RPL4QARSESRRANPM1COX7CHINT1RPS3ATP5J2PFKMGYG1BAG1CSNK1A1COPS2IPO7CLNS1AMRPS27HARSRPL23AASDHPPTIVDSORDMFNGEIF3EVILLSNUPNLDHBPOLR2HRSL1D1

hsa-miR-152 hsa-miR-24RPS19RPL28CCT6AGRHPRXRCC4RPL36ATP5LRPL24RPL7AECSITRPL29NDUFS7RPS15RPL13ASDCCAG3RPL18TOR1BNDUFB5GSTO1USE1PIK3R3GNB2L1QARSRPL12TKTRPS9HINT1PSMA2STOML2RPL35AEEF2ATP5J2AUHRPS27LC19orf53PFKM

IDH2BAG1GALTIPO7CLNS1ANDUFB6MRPS27EDF1HARSNDUFA2RPL37MDH2IVDPPCDCTIMM13SORDMFNGNANSVILLCCNG1ETFAEIF3MSNUPNRPL22UNC13BTRIP6IMPDH2POLR2H

ANKRD6PTCD2CARD8EEF1DPSMA1MAN2C1FASTKD1RNF44GARTNPM1TRIM14BAG1ABCF2GALK2PTPLAD1TMED3QARSBCL2L1PIP5K1BRPL35SLAMF1CCT8MEIS2PMLTHG1LRPL28

RPL28CCT6ANDUFS7RPL13ARPL18RPL14MDH2C9orf16PPCDCSNUPNRPL22RFXANK

hsa-miR-339 hsa-miR-125aPSMB7UBA52RPS19RPL28GRHPRXRCC4RPL36RPL7ARPL29MRPL34NDUFS7SDCCAG3RPL18RPS6GSTO1RPL14USE1RPL4GPIGNB2L1QARSESRRARPL12NPM1TKTRPS9HINT1RPS3STOML2RPL35APFKMIDH2NCBP2ACAT1RALGPS1BTF3

KANK1NAIPCLNS1AMRPS27EDF1HARSNDUFA2RPL37MRPL48MDH2AASDHPPTIVDC9orf16AHCYNOP16PPCDCTIMM13SORDMFNGNANSEIF3EVILLETFATRIP6RFXANK

PSMB7CCT6AXRCC4RPL24NDUFB5PIK3R3RPL4QARSNPM1NDUFS4RPS9COX7CCOX5ARPL35ARPS16RPS27LRSL24D1PFKMBAG1CSNK1A1COPS2IPO7MRPS27NDUFA2ATP5OMDH2AASDHPPTBTBD3TXNPPCDCLSM7NANSEIF3EVILLCCNG1TIMM8B

ETFAEIF3MSNUPNRRAGDLDHBNDUFB1RSL1D1

hsa-let-7

Supplementary Table 7. Predicted Target Genes that are overexpressed in h-MM vs nh-MM (FDR<0.001 ) using expression

dataset provided by Agnelli et al. 2007 (miRanda (miRBase v12.0) and TargetScan v 5.1)

11

Supplementary Figure 3: Luciferase assay. The empty reporter plasmid (empty pGL3 luciferase vector) or the luciferase constructs

containing, respectively, a wild-type and a mutated 3’UTR regions of the selected target genes (TACC3, CCND1, FGFR3 and MAFB)

were co-transfected into Hela cells with the miRNA vectors (pMSCV-425, pMSCV-24, pMSCV-152 and scramble miRNA) and

together with Renilla vector for normalization. Luciferase activity was determined 48 h after reporter plasmid transfection in all

cases. The reduction in luciferase activity induced by the three miRNAs expression was observed in each case, allowing us to

demonstrate that MAFB1, CCND1 and FGFR3 are real targets of hsa-miR-152, hsa-miR-425 and hsa-miR-24, respectively. . Data are

presented as mean from four separate experiments with n = 3 for each experiment. Error bars represent Standard error of the

mean (SEM)


LUCIFERASE ASSAY

12

13

MAFB

48h 72h

U266 +hsa-miR-152

α- Tubulin

24hU266 SCR

43kDa

55 kDa

FGFR3

48h 72h

U266 +hsa-miR-24

GAPDH

24hU266 SCR

38 kDa

135 kDa

48h 72h

U266 +hsa-miR-425

24hU266 SCR

α- Tubulin

TACC3

55 kDa

140 kDa Cyclin D1

48h 72h

U266 +hsa-miR-425

α- Tubulin

24hU266 SCR

38 kDa

55 kDa

Supplementary Figure 4: Complete Western Blot gel images of Figure 2B. As shown, the signals from Scr transfected cells correspond to the same set of experiments.



14

Supplementary Figure 5: Densitometric analysis. The target protein expression was quantified by densitometric analysis

carried out using the ImageJ software on images acquired from the results of Western blotting (Figure 2B). The analysis shows

the percentage of decrease in Tacc3, Cyclin D1 and MafB expression after the overexpression of the corresponding miRNAs

(hsa-miR-425, hsa-miR-425 and hsa-miR-24, respectively) in U266 cells over cells transfected with scramble miRNA vector and

normalized with the GAPDH or α-tubulin protein expression used as loading control. Data are presented as mean from three

separate experiments. Error bars represent Standard error (SE).

15


Supplementary Figure 6: OH-2 cell line. Expression levels of the selected miRNAs in the h-MM cell line OH-2 were

assessed by real-time PCR. We were able to show the downregulation of the three miRNAs in the OH-2 cell line, as

occurs in h-MM patients. In both (A) and (B)data are expressed as 2 -∆Ct values obtained by normalization using RNU19 as

endogenous control. Error bars represent SD.

16


17

Supplementary Figure 7: Densitometric analysis. The target protein expression was quantified by densitometric analysis

carried out using the ImageJ software on images acquired from the results of Western blotting (Figure 3B). The analysis

shows the entity of increase in Tacc3, Cyclin D1, Fgfr3 and MafB expression at 48h or 72h after the inhibition of the

corresponding miRNAs (hsa-miR-425, hsa-miR-24 and hsa-miR-152, respectively) in Hela or 293FT cells. The results were

normalized with the GAPDH protein expression used as loading control and were expressed as percentage of the protein

expression in the cells transfected with miRIDIAN control vector. Data are presented as mean from three separate

experiments. Error bars represent SEM.

18

TACC3 hsa-miR-425

CCND1

MAFB

FGFR3

hsa-miR-152

hsa-miR-24

h-MM patients

CD138+ cells

nh-MMpatients


19

Supplementary Figure 8: Target genes and miRNAs expression in MM cases . (Extension of Figure 3B and 3C)

Error bars represent SD.

20

21

Supplementary Table 8: Publicly available gene and miRNA expression data on multiple myeloma (MM).

ReferenceDatabase accession number

Patients data needed

miRNA expression

profile

Gene expression

profile (GEP)Chng et al, Molecular dissection of hyperdiploid multiple myeloma by gene expression profiling. (Cancer Res, 2007) GEP: GSE6477 YES NO YES

Agnelli et al, Upregulation of translational machinery and distinct genetic subgroups characterise hyperdiploidy in multiple myeloma (Br J Haematol. 2007)

GEP: GSE6401 YES NO YES

Agnelli et al, A SNP microarray and FISH-based procedure to detect allelic imbalances in multiple myeloma: An integrated genomics approach reveals a wide gene dosage effect (Genes Chromosomes Cancer. 2009)

GEP: GSE13591 Only TC classification NO YES

Lionetti et al, Identification of microRNA expression patterns and definition of a microRNA/mRNA regulatory network in distinct molecular groups of multiple myeloma (Blood. 2009)

miRNAs: GSE17498GEP: GSM341951 NO YES YES

Zhoua et al, High-risk myeloma is associated with global elevation of miRNAs and overexpression of EIF2C2/AGO2 (PNAS. 2009)

miRNAS and GEP: GSE17306 NO YES YES

Gutierréz et al, Deregulation of microRNA expression in the different genetic subtypes of multiple myeloma and correlation with gene expression profiling (Leukemia. 2010)

miRNAS and GEP: GSE16558 NO YES YES

Agnelli et al, Molecular classification of multiple myeloma: a distinct transcriptional profile characterizes patients expressing CCND1 and negative for 14q32 translocations. (J Clin Oncol. 2005)

GEP: GSE2912 NO NO YES

Mattioli et al, Gene expression profiling of plasma cell dyscrasias reveals molecular patterns associated with distinct IGH translocations in multiple myeloma (Oncogene. 2005)


Carrasco et al, High-resolution genomic profiles define distinct clinico-pathogenetic subgroups of multiple myeloma patients. (Cancer Cell. 2006)


http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=+GSE6477

http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE6401



http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM341951



http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=+GSE2912



22



miRNA expression

profile

Gene expression

profile (GEP)Shaughnessy et al, A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1 (Blood. 2007)


Jenner et al, Gene mapping and expression analysis of 16q loss of heterozygosity identifiesWWOX and CYLD as being important in determining clinical outcome in multiple myeloma (Blood. 2007)


Decaux et al, Prediction of Survival in Multiple Myeloma Based on Gene Expression Profiles Reveals Cell Cycle and Chromosomal Instability Signatures in High-Risk Patients and Hyperdiploid Signatures in Low-Risk Patients: A Study of the Intergroupe Francophone du Myélome (J Clin Oncol. 2008)


Hose et al, Inhibition of aurora kinases for tailored risk-adapted treatment of multiple myeloma (Blood. 2009)

GEP: E-GEOD-2658

andE-MTAB-81

NO NO YES

Broyl et al, Gene expression profiling for molecular classification of multiple myeloma in newly diagnosed patients(Blood. 2010)


Driscoll et al, The sumoylation pathway is dysregulated in multiple myeloma and is associated with adverse patient outcome (Blood. 2010)


Pichiorri et al, MicroRNAs regulate critical genes associated with multiple myeloma pathogenesis (PNAS. 2008)

miRNAs: E-TABM-508 NO YES NO

Roccaro et al, MicroRNAs 15a and 16 regulate tumor proliferation in multiple myeloma (Blood. 2009) NO NO YES NO

Jianxiang et al, MicroRNA expression in multiple myeloma is associated with genetic subtype, isotype and survival (Biology Direct 2011)

miRNAs: Wrong Access number

GSE243371 ? YES NO




http://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-2658

23



miRNA expression

profile

Gene expression

profile (GEP)Moreaux et al, CD200 is a new prognostic factor in multiple myeloma. (Blood. 2006) NO NO NO YES

Condomines et al, Cancer/Testis Genes in Multiple Myeloma: Expression Patterns and Prognosis Value Determined by Microarray Analysis (J Immunol. 2007)

NO NO NO YES

Jourdan et al, Gene expression of anti- and pro-apoptotic proteins in malignant and normal plasma cells (Br J Haematol. 2009)

NO NO NO YES

Zhang et al, Overexpression of microRNA-29b induces apoptosis of multiple myeloma cells through down regulating Mcl-1 (Biochem Biophys Res Commun. 2011)

NO NO NO YES

Documents

Supplementary information summary : TABLES: