PLASMA CELLS (MORMAL AND NEOPLASTIC) CANCER RESEARCH CENTER, UNIVERSITY & UNIVERSITY HOSPITAL of SALAMANCA (SPAIN) Multicolor Immunophenotyping: Standardization and Applications March 9-11, 2012 TMH, Mumbay (India)

MRD MONITORING IN HAEMATOLOGICAL MALIGNANCIES In vivo drug kinetics Tumor micro-environment Treatment compliance Tumor cell features Therapy Morphology, Cytogenetics Southern-Blot, FCM DNA aneuploidy 1011 Resistance 1010 10-2 109 10-3 Complete remission Sensitivity F.I.S.H 108 10-4 Immunological CR Molecular CR 107 La detección de EMR estrategia habitual de control de hemopatías maligna. El porqué es lógico dado que un paciente en RC puede tener un número de células tumorales tan difernte como de 10 (10) a 1 células .Difernetes técnicas . Pero las más utilizadas y mayor capacidad predictiva son Fenotipo y PCR. Yo me referiré a PCR 10-5 Flow cytometry N. of tumor cells 106 10-6 P.C.R. 105 104 - CML - APL - Childhood ALL - … Therapeutic decisions 103 102 101 100 2

MRD TECHNIQUES FOR HAEMATOPOIETIC MALIGNANCIES FCM immunophenotyping PCR/RT-PCR analyses (sensitivity) (sensitivity) Disease category LAIP sIgk/sIgl Junctional Reg Chromosomal or TCRVb Ig/TCR genes aberrations (10-3-10-4) (10-2-10-3) (10-3-10-6) (10-4-10-6) Precursor B-ALL Children 80-90% NA 95% 40-50% Adults 70-80% NA 90% 35-45% T-ALL Children >95% 30-35% >95% 10-25% Adults >95% ? 90% 5-10% Chronic B-cell leukemias <5% >95% >95% 10-25% Chronic T-cell leukemias 5-10% 60-65% 95% <5% B-cell lymphomas <5% >95% 70-80% 25-30% T-cell lymphomas 20-25% 50-60% 95% 10-15% AML 70-90% NA 10% 10-30% CML NA NA NA >95% From: Szczepanski, Orfao et al, Lancet Oncol, 2001; 2: 409-417

IMMUNOPHENOTYPING - Acute Leukemias & Lymphoproliferative disorders: BACKGROUND IMMUNOPHENOTYPING - Acute Leukemias & Lymphoproliferative disorders: • Mandatory for diagnosis & monitoring - Multiple Myeloma: • Restricted to research • Differential diagnosis of unusual cases

+ = Plasma cell quantification (BM infiltration) Morphological PC count : - area of BM smear - infiltration pattern Variability Immunophenotyping: - precise identification by CD38/CD138 High-intensity Co-expression of CD38/CD138 Specific expression 10 1 2 3 4 CD38 FITC -> TRANSFORMED SSC -> 10 1 2 3 4 CD38 FITC -> CD138 PerCP/Cy5 -> + = TRANSFORMED SSC -> 10 10 1 10 2 10 3 10 4 CD138 PerCP/Cy5-> - but…..diluted sample  lower numbers

Correlation between Immunophenotyping & Morphology: Prognostic influence of the number of BMPC: 25 50 75 100 Proportion of plasma cell by morphology Proportion of plasma cell by flow cytometry W R 2 = 0,39 = 0,4

MINIMAL RESIDUAL DISEASE (MRD) BACKGROUND High-dose chemotherapy and Novel Drugs Complete remission (CR): 25%-75% Relapse-free survival (RFS) at 5 year: 40%-70% However, patients with MM ultimately relapse MINIMAL RESIDUAL DISEASE (MRD) persistence of residual malignant cells

Ocqueteau, Am J Pathol, 1996; San Miguel et al, Blood, 2002

MM vs Normal BM plasma cells Abnormal plasma cells Normal plasma cells

Myeloid-associated Ags: Pan-leuc. Ag: CD45+...20-40% B-cell-associated Ags: CD19+..........3-8% CD20+..........2-25% CD22+..........20-30% CD10+..........6-20% HLA-DR+het….. 10% CD23+.......... 0% FMC7+......... 0% PC-associated Ags: CD38++/+++.... 100% CD138 +....... 98% MM PLASMA CELL HPC-associated Ags: CD34+..........0% CD117 +......27% CyIg+ Co-stimulatory Ags: CD28+/++....... 30-40% CD40 +....... 100% CD81,CD27-/lo.40-50% CD52……………….10-50% Adhesion molecules: CD56+/++.....60-70% b1/b2 integrins 98% CD54….……….50-70% Myeloid-associated Ags: CD13+......... 28% CD33 +/++..... 24% Rawstron et al, Haematologica 2008

Asynchronous expression Incidence of aberrant phenotypes in PC from MM 10 20 30 40 50 60 70 80 90 100 CD19 CD38 CD45 CD56 CD28 CD33 CD117 CD20 96% 80% 73% 60% 36% 18% 32% 17% Asynchronous expression Infra-expression Mateo et al. J Clin Oncol; 2008;26:2737 Over-expression 92% Incidence of aberrant phenotypes in PC from MM

MOST USEFUL ANTIGENS FOR THE DETECTION OF ABERRANT PC IN MM Antigen Expression % MM with Requirement for Normal Altered altered expression MRD studies CD19 + (>70%) - 95% Essential CD56 - (>85%) ++ 75% Essential CD20 - (100%) + 10% Preferred CD117 - (100%) + 30% Preferred CD28 -/dim (100%) ++ 15% Recommended CD81 + -/dim N.A. Recommended CD27 ++ -/dim 40-50% Recommended N.A.: not analyzed/not reported. Rawstron et al, EMN consensus, Haematologica, 2008

Immmunophenotype of normal vs clonal PC 80 60 40 20 Clonal PC Normal PC CD56 p0.001 Clonal PC Normal PC 100 80 60 40 20 CD126 p0.001 60 50 40 30 20 10 Clonal PC Normal PC CD95 p=0.72 120 100 80 60 40 20 Clonal PC Normal PC CD86 p0.001 % of positive PC CD38 HLA-I 2-microglobulin CD40 10000 8000 6000 4000 2000 Clonal PC Normal PC 10000 8000 6000 4000 2000 Clonal PC Normal PC p=0.002 4000 3000 2000 1000 Clonal PC Normal PC Clonal PC Normal PC 3000 2000 1000 p=0.21 p=0.005 Mean FL Intensity p0.001 Perez-Andres et al, Leukemia, 2005; Perez-Andres et al, Int J Cancer, 2009

MGUS vs MM: IMMUNOPHENOTYPIC PANELS N.of PB AMCA FITC PE PerCPCy5.5 APC PE-Cy7 APCH7 colors PO 3 CD38 CD56 CD19 4 CD38 CD56 CD19 CD45 6 CD38 CD56 CD45 cyIgk CD19 cyIgl 8 CD45 CD138 CD38 CD56 CD117 cyIgk CD19 cyIgl

Characterization markers B cell homing Normal B lymphopoiesis CD11a, CD11c, CD31, CD49d, CD62L, CXCR5, CCR6, CD303 CD10, CD20, CD22 CD24, CD27, CD38 CD39, CD43, CD63 CD81, CD95, CD138 Bcl-2, HLA-DR, CyIg Known to differentiate CD13, CD15, CD28, CD33, CD56, CD45, CD117, b2M 7 informative markers

NORMAL vs NEOPLASTIC PC: IMMUNOPHENOTYPIC PANELS N.of PB HV500 FITC PE PerCPCy5.5 APC PE-Cy7 Alexa700 colors HV450 PO APC-H7 3 CD38 CD56 CD19 4 CD38 CD56 CD19 CD45 6 cyIgL cyIgk CD19 CD45 CD56 CD38 CD138 CD117 CD19 CD45 CD56 CD38 8 CD45 CD138 cyIgL cyIgk CD138 CD117 CD56 CD38

Principal component analysis CONSTRUCTION OF EuroFlow MRD PANELS: MM Identify PC Select PC Principal component analysis (n=12 markers) MM #1 MM #2 Normal BM #1 Normal BM #2 SSC CD38-FITC SSC CD38-FITC Merge PC (n-cases) MOST INFORMATIVE MARKERS CD19 19.83 CD56 19.02 CD81 12.29 CD45 11.47 CD27 9.95 CD117 9.34 CD38 5.18

EuroFlow PANEL: Plasma cell dyscrasias Abnormal PC detection /classification in MGUS & MM (APS view) Normal PCs Abnormal PCs Most informative markers CD19:PE Cy7-A LOGICAL 12.16 CD45:PacB-A LOGICAL 11.81 Responsible scientist: J.Flores

PCD panel: Backbone markers Pac Blue Orange FITC PE PerCP-Cy5.5 PECy7 APC APC-H7 1 CD45 CD138 CD38 CD19 2 Responsible scientists: Juan Flores

PCD panel: Backbone markers Pac Blue Orange FITC PE PerCP-Cy5.5 PECy7 APC APC-H7 1 CD45 CD138 CD38 CD19 2 Pac Blue Orange FITC PE PerCP-Cy5.5 PECy7 APC APC-H7 1 CD45 CD138 CD38 CD56 CD27 CD19 CyIgk CyIgl 2 CD28 b2M CD117 CD81 Responsible scientists: Juan Flores

MONOCLONAL GAMMOPATHIES: IDENTIFICATION OF CLONAL PLASMA CELLS 10 1 2 3 4 CD38 FITC -> TRANSFORMED SSC -> CD38-FITC gated PC T-SSC Clonal PC Normal PC C D 5 6 P E 9 1 A 4 CD19-PcpCy5 CD56-PE CD45-APC 10 1 2 3 4 CD38 FITC -> CD138 PerCP/Cy5 -> CD138-PerCP/Cy5.5 CD38-FITC Perez-Andres, J Biol Reg, 2004

MRD TECHNIQUES FOR HAEMATOPOIETIC MALIGNANCIES FCM immunophenotyping PCR/RT-PCR analyses (sensitivity) (sensitivity) Disease category LAIP sIgk/sIgl Junctional Reg Chromosomal or TCRVb Ig/TCR genes aberrations (10-3-10-4) (10-2-10-3) (10-3-10-6) (10-4-10-6) Precursor B-ALL Children >90% NA 95% 40-50% Adults >95% NA 90% 35-45% T-ALL Children >95% 30-35% >95% 10-25% Adults >95% ? 90% 5-10% Chronic B-cell leukemias >95% >95% >95% 10-25% Chronic T-cell leukemias 70-80% 60-65% 95% <5% B-cell lymphomas 90% >95% 70-80% 25-30% T-cell lymphomas 75-90% 50-60% 95% 10-15% Multiple myeloma >90% >90% 70-80% NT AML 70-90% NA 10% 30-40%* CML NA NA NA >95% * Increased through the usage of additional molecular markers (e.g.: WT1, NMP1 & FLT3 mutations

BM plasma cells in MGUS 50% 0,35% CD38 -> FSC-Height -> 10 1 2 3 4 JR67635.001 CD38 -> 0,35% JR67635.002 50% 256 512 768 1024 FSC-Height -> CD45 ->

Differential diagnosis MM MGUS Clonal Poly-Clonal versus Only 20% of MM patients showed poly-PC and constantly <5% (median: 0.25%)1 >5% poly-PC: 98% MGUS The most powerful single criteria for differential diagnosis (even in stage I MM) 1. Ocqueteau M, Am J Pathol 1998, 152: 1655 Risk of MGUS transformation2 Cases with predominantly (>95%) CD19- ve PC.... High risk (26% transformed in 31 months) 2. Rawstron A, Blood 2003, 102, 36 a (Abstr.116)

Prognostic influence of phenotypic profiles Months from diagnosis 72 66 60 54 48 42 36 30 24 18 12 6 1.0 .9 .8 .7 .6 .5 .4 .3 .2 .1 0.0 p=0.01 CD56+CD28- n= 1116 41 m +/+ or -/- n=266 36 m CD56-CD28+ n=116 29 m CD56 & CD117 CD56+CD117+ n= 130 45 m +/- or +/- n=267 36 m CD56-CD117- n=186 31 m p=0.001 CD28 & CD117 CD28-CD117+ n= 142 45 m +/- or +/- n=327 37 m CD28+CD117- n=114 29 m p=0.0005 PFS CD56 & CD28 PFS

Introduction Smoldering Multiple Myeloma Kyle & Alexanian 1980a. Estimated incidence: 15% of newly diagnosed MMb. Estimated Risk of progression: 10% per yearc vs. 1% on MGUS a Kyle 1980, Alexanian 1980; bRajkumar 05; cKyle 05

Proportion of aPC referred to the total-PC (aPC/BMPC) PC analysis in BM by FC 1st step Total cellularity . 2nd step PC compartment % aPC/BMPC % nPC/BMPC % PC within BM cellularity Proportion of aPC referred to the total-PC (aPC/BMPC)

Flow Cytometry Results % Total PC in BM* 2.8 (0.9-22.0) % of aPC / BMPC compartment 97 (35-100) < 95% aPC / BMPC 36 (40%) > 95% aPC / BMPC 53 (60%) * Median (range)

Impact of % aPC/BMPC by FC on Progression Free Survival 20 40 60 80 100 120 Months 0,0 0,2 0,4 0,6 0,8 1,0 % of Progression Free Survival p=0.0000 Median Not reached Median 40 months <95% aPC/BMPC n= 36 (4 progressions) 37% 92% >95% aPC/BMPC n= 53 (34 progressions) 5 years

Multivariate analysis for PFS p HR % a PC /BMPC 0.004 4.9 Immunoparesis 0.007 2.6

Impact of prognostic index on PFS Immunoparesis >95% aPC/BMPC Score (n) - - 0 (n=32) + / - -/+ 1 (n=27) + + 2 (n=27)

Impact of prognostic index on PFS 20 40 60 80 100 120 Months 0,0 0,2 0,4 0,6 0,8 1,0 % of Progression Free Survival Median not reached Median 75 months Median 20 months p= 0.003 91% 58% No adverse factors n= 32 (3 progressions) >95% aPC/BMPC or paresis n= 27 (12 progressions) 18% >95% aPC/BMPC + paresis n= 27 (22 progressions) 5 years

MM: IMMUNOPHENOTYPIC IDENTIFICATION OF NEOPLASTIC PLASMA CELLS IN REMISSION BM

MM: Diagnostic vs remission BM Diagnosis MRD/remission Clonal Poly-Clonal versus MM patients show few poly-PC constantly <5% (median: 0.25%)1

FLOW MRD IN MM: Why, when and how? - Does response to therapy impact on long-term patient outcome? - Does flow-based MRD improve prognostic stratification of myeloma patients? Is flow-based MRD a well suited technique for MRD assessment in MM? Can flow-based MRD techniques be used in routine diagnostic labs?

Impact of CR in the ASCT setting In the ASCT setting, there is a large body of evidence showing an association between optimal response (CR/VGPR) and long-term outcome (PFS and OS) 10 prospective trials (2991 patients): All showed a positive correlation (statistically significant in 8) . Similar findings in 5/8 retrospective trials (Van de Velde, Hematologica 2007, 92, 1399) - Significant correlation between maximal response and outcome prospective studies (<0.00001) & rétrospective studies (< 0.00001) Is it the same CR & VGPR ??

PETHEMA-GEM 2000: Outcome according to post-transplant response CR and nCR are not the same: “depth of response” PETHEMA-GEM 2000: Outcome according to post-transplant response EFS OS 1,0 1,0 CR vs nCR P=0.01 CR vs nCR or PR P<10-5 0,9 CR vs PR P<10-6 nCR vs PR P=0.07 0,9 nCR vs PR P=0.04 0,8 0,8 0,7 0,7 0,6 0,6 0,5 Cumulative Proportion Event Free Surviving Cumulative Proportion Surviving 0,5 0,4 0,3 0,4 0,2 0,3 0,1 0,2 0,0 12 24 36 48 60 72 84 96 0,1 12 24 36 48 60 72 84 96 Months from diagnosis Months from diagnosis CR, n=278 nCR, n=124 PR, n=280 PD, n=25 CR nCR PR PD Medians EFS, months 61 40 34 13 Medians OS, months NR 15 Lahuerta et al. JCO 2008;26:5775–5782

CR correlates with long-term PFS and OS in elderly patients treated with novel agents Retrospective analysis: 3 randomized European trials of GIMEMA and HOVON groups (n=1175) First-line treatment MP (n=332), MPT (n=332), VMP (n=257), VMPT-VT (n=254) PFS OS P<0.001 CR VGPR PR Significant benefit also seen when analysis is restricted to patients >75 years old Gay et al. Blood 2011

Which level of response should be measured? Depth of response Which level of response should be measured? Depth of response is related to TTP Progression Treatment initiation MR PR VGPR/ nCR CR sCR Molecular/Flow CR TTP MRD investigation in MM : molecular & Immnunophenotypic tools

Analysis of immunophenotypic response (IR) by MFC in 619 myeloma patients included in three consecutive Spanish trials GEM 2000 (n=510*) GEM 2005<65y (n=369*) Diagnosis Diagnosis 6 cycles 6 alterning cycles VBMCP/ VBAD Thalidomide/ Dexamethasone (TD) (n=121) Bortezomib/ Thalidomide/ Dexamethasone (VTD) (n=122) VBMCP/ VBAD (x4) Bortezomib (x2) (n=126) MRD investigation MRD investigation ASCT (n=157) MRD investigation ASCT (n=206) MRD investigation 3m post-ASCT 3m post-ASCT (n=295) (n=222) GEM 2005>65y (n=246*) MRD investigation Bortezomib/ Melphalan/ Prednisone (VMP) (n=121) 6 cycles Diagnosis (n=102) Bortezomib/ Thalidomide/ Prednisone (VTP) (n=125) * Patients achieving CR or VGPR after treatment without MRD investigation were excluded from the ITT analysis

EF + n=108 #MM-PC # % N-PC/BMPC 0.76 MRD evaluation 86% *MRD+ cases 44 #Results expressed as medians Complete remission Partial Response IFx - n=147 (79%) 0.1 <.001 36% 85 IFx + n=40 (21%) 62% 0.21 73 P *≥0.001% MM-PC Correlation between immunophenotyping & electrophoretic responses at three months post-ASCT (GEM 2000 trial, n=295) Paiva et al; Blood. 2008, 112: 4017-4023 41 41

independent of the induction regimen GEM2000 & GEM2005: Impact on survival of achieving an Immunophenotypic CR after HDT/ASCT independent of the induction regimen PFS OS 100 100 P =.132 80 P =.640 80 P =.091 60 60 40 40 P =.802 20 20 P <.001 P <.001 20 40 60 80 100 120 25 50 75 100 125 GEM2000 GEM2005 (<65y) Paiva et al. Blood 2010. 116; abstr 1910

M-component positive M-component negative ------- Follow-up P Progression Death Treatment interruption 1 IgG ---------------------------------------------------------------------- 2 B-J ------------------------------------------------------------------------------------------ 3 IgG ----------------------------------------------------------------------------------------------- 4 IgA ------------------------------------------------------------------------------------------------------ 5 IgG --------------------------------------------------------------------------------------------------------------- 6 B-J ------------------------------------------------------------------------------------------ P ------------------------------- 7 IgG ---------------------------------------------------------------------------------------------------------------------------------- 8 B-J -------------------------------- P ---------------------------- 9 IgG ------------------------------------------------------------------- 10 B-J -------------------------------------------------------------------- 11 IgG ----------------------------------------------------------------------- 12 IgA ------------------------------------------- P ------------------------------ 13 IgA ------------------------------------------- P --------------------------------- 14 IgG -------------------------------------------------------------------------------- 15 IgA --------------------------------------------------------------------------------- 16 IgG -------------------------------------------------------------------------------------------- 17 IgG ------------------------------------------------------------------------------- P ------- 18 IgG ------------------------------------------------------------------------------------------ 19 IgA --------------------------------------------------------------------- P -------------------- 20 IgG ------------------------------------------------------------------------------------------------------ 21 IgA --------------------------------------------------------------------------------------------------------------- 22 IgA ---------------------------------------------------------------------------------------------------- P ----------- 23 IgA ------------------------------------------------------------------------------------------------------------------------- 24 IgA ---------------------------------------------------------------------------------------------------- P ------------------------- 25 IgA ------------------------------------------------------------------------------------------- P ---------------------------------------- 26 IgG ------------------------------------------------------------------------------------------------------------------------------------------- 27 IgA ------------------------------------------------------------------------------------------------------------------------------------------- IR / non-CR non-IR / CR 1 2 3 4 5 6 7 8 9 10 11 12 // 16 // 20 // 24 // 28 // 32 // 36 // 40 // 44 // 48 Post-Induction Maintenance (months) Patient no. Kinetics of response: conventional CR vs. immunophenotypic response (IR) 7/7 (100%) patients turned IFx- 10/20 (50%) patients turned IFx+ Paiva et al, JCO, 2011

GEM2000: Impact on survival of achieving an immunophenotypic CR vs GEM2000: Impact on survival of achieving an immunophenotypic CR vs. conventional CR after HDT/ASCT PFS At 5 years: 59% 49% 24% 17% 100 80 60 MRD- IFE- 71 m (n= 94) 40 MRD- IFE+ 65 m (n=31) MRD+ IFE- 37 m (n=53) 20 MRD+ IFE+ 37 m (n=117) p= 0.002 25 50 75 100 125 Months 44

GEM 2000 trial: Multivariate Analysis p risk p risk MRD+ at day +100 0.002 3.6 0.02 2.0 High Risk Cytog*. 0.006 1.79 ns Age >60y. ns 0.04 1.6 IF+ at dey +100 ns ns PFS OS t(4;14), t(4;16), del (17p) Paiva et al; Blood. 2008 45

GEM 2000+2005: Immunophenotypic response & FISH for the prediction of early relapse in CR patients after HDT/ASCT (n=241) OS PFS P <.001 Months Medians: NR Median: 97m Median: 43m 80% 93% 120 100 80 60 40 20 0% Median: 17m @ 1y after ASCT Median: 64m Median: 35m MRD negative + Standard risk FISH (n=58) MRD positive OR High-risk FISH (n=45) MRD positive + High-risk FISH (n=7) 46

GEM 2005(>65y): Impact on survival of the depth of response after induction therapy (n=102) Immunophenotypic response (n=31) “Stringent CR” (n=11) CR (n=9) PR (≥70% reduction) (n=51) 60 50 40 30 20 10 100 80 Months P <.001 PFS P =.353 OS

Updated results from the MRC myeloma IX trial 711 intensively treated patients (CVAD or CTD and HDM) at 3 months post-HDM: 66% remained MRD+ve highly predictive of outcome (PFS; p=0.0001) increased MRD-ve rates with consolidation and maintenance  prolongation of PFS 510 non-transplant eligible patients (CTDa or MP) only 8% became MRD- but a significantly improved PFS was demonstrated (p=0.028) Immunophenotypic CR predicted outcome in CR (IFx -) patients and both standard and high-risk cytogenetic groups Owen et al. IMW Paris 2011 abstr O-09

MM: Flow cytometry immunophenotyping vs. molecular monitoring of MRD ? Molecular techniques Flow cytometry Speed 2-3 days (up to weeks) fast: 1-2 hours Target DNA or RNA protein/cells (RNA is an instable target) (“end-product”) Applicability 70-75% >95% Sensitivity 10-5-10-6 10-4-10-5 Multiplexing technically demanding relatively easy (even 25 to 100 tests per tube) Accuracy semi-quantitative quantitative Focus all cells in sample any subpopulation (or: prior purification) (FACSorted for further analyses) Facilities special laboratories needed only standard lab needed (pre-PCR lab, PCR lab, etc) (+ flow cytometer) Modified from J.J.M. van Dongen S800.587 49

HOW TO SIMPLIFY & OPTIMIZE FLOW-BASED MRD STRATEGIES - Improve the design of MRD panels for a greater efficiency and higher reproducibility. - Construct reference data files for normal and neoplastic cells (e.g.: per disease category) Multi-n-dimensional comparison of normal vs neoplastic cell populations (e.g.: at diagnosis and follow-up): - Automated PCA-guided approach for homogeneous cell populations(e.g. lymphoid) - Maturation tools for heterogeneous cell populations(e.g. myeloid)

Principal component analysis (n=14 markers/parameters) CONSTRUCTION OF EuroFlow MRD PANELS: MM Identify PC Select PC Principal component analysis (n=14 markers/parameters) MM #1 MM #2 Normal BM #1 Normal BM #2 SSC CD38-FITC SSC CD38-FITC Merge PC (n-cases) MOST INFORMATIVE MARKERS CD19 19.83 CD56 19.02 CD81 12.29 CD45 11.47 CD27 9.95 CD117 9.34 CD38 5.18

Automated classification of normal vs aberrant plasma cells in MM Diagnosis Pre-Transplant Post-transplant n-PC (0.12%) m-PC (22%) n-PC (0.03%)+m-PC (0.8%) Comparative View Comparative View Comparative View

FLOW-BASED MRD IN MM: Conclusions - Response to therapy impacts on long-term patient outcome both in the transplant and non-transplant settings - Flow-based MRD improves prognostic stratification of myeloma patients particualrly among those cases who reach CR Flow-based MRD is a well suited technique for MRD assessment in MM Full standardized and automated flow-based MRD approaches for MM have been developped Shall flow-based MRD be introduced in the treatment-decision algorithms of new (randomized) trials ?

CIRCULATING NEOPLASTIC PLASMA CELLS MGUS SMM MM P.-value % of cases with PB M-PC 7 (21%) 18 (69%) 43 (75%) <.001 N. of M-PC/mL 0.3 0.2 4.0 % of PB M-PC 0.004 0.02 0.09 .002 Paiva et al, Leukemia (under revision); ASH 2010 (abstract #617)

MINIMAL NUMBER OF PC REQUIRED TO BE ANALYZED IN A MRD ASSAY FOR MM N. of tests in the MRD assay N. of total nucleated cells/test N. of events/test to define a PC population 1 1,000,000 100 2 500,000 50 3 333,334 34 4 250,000 25 5 200,000 20 Rawstron, Orfao et al, Haematologica, 2008

Grupo Español de Mieloma (GEM) Hospitales Clínico de Barcelona 12 Octubre (Madrid) Clínico de Salamanca Clínico de San Carlos (Madrid) Hospital de Badalona Clínico de Asturias Fr. Peset (Valencia) Universitario de Canarias Rio Ortega (Valladolid) Cínico de Zaragoza Hospital General de Jerez Ramón y Cajal (Madrid) Morales Meseguer (Murcia) La Fe (Valencia) C.U. de Navarra Galdakao (Vizcaya) Clínico de Valladolid Sant Pau (Barcelona) Arnau Vilanova (Lérida) Universitario de Santiago General Universitario de Valencia Universitario de Getafe (Madrid) Insular de las Palmas H. de La Princesa (Madrid) Severo Ochoa (Madrid) Juan XIII (Tarragona) Toledo Gandía (Valencia) Vall D´Hebrón (Barcelona) San Jorge (Huesca) Verge de la Cinta (Tortosa) Alarcos (Ciudad Real) Mataró (Madrid) Juán Canalejo (Coruña) Ferrol Hospitales General de Segovia Cruces (Bilbao) St. Coloma de Gramanet (Barcelona) Gregorio Marañon (Madrid) Carlos Haya (Málaga) H. Tauli (Gerona) Huesca Palencia Alcira (Valencia) H. Del Mar (Barcelona) Mahón (Baleares) Clínico de Málaga Xeral Cies (Vigo) Plasencia Cáceres Algeciras Ávila Jaén S. Pau i Sta Tecla (Tarragona) General de Guadalajara Sagunto (Valencia) Son Dureta (Mallorca) Cuenca Alicante SUS M. Valdecilla (Santander) Albacete H. Del Bierzo Fundación Jiménez Díaz (Madrid) Elda (Alicante) V. Del Rosel (Cartagena) Castellón Mutua Tarrasa Consorcio Tarrasa C. Corachán (Barcelona) Salamanca´Group: G.Mateo, M. Perez-Andres, N.Gutierrez, R.Lopez, M.Mateos, R.Garcia-Sanz, J.Almeida, J.San Miguel

Cytometry Service & Department Medicine, CICancer, University Salamanca-CSIC, Salamanca, Spain Martín Perez-Andres Leandro Thiago Alberto Orfao School of Medicine, Southampton, UK Surinder S Sahota Serv. Hematology, Hosp. Univ. Salamanca, Salamanca, Spain Bruno Paiva Jesus F San Miguel University Medical Center, Groningen, Netherlands Nico A Bos University of Heidelberg, Heidelberg, Germany Dirk Hose Aalborg Hospital Science & Innovation Center AHSIC Aarhus University Hospital, Denmark Hans E Johnsen Vrije Universiteit, Brussel, Belgium Karin Vanderkerken INSERM, U847, CHU Montpellier, Institute of Research in Biotherapy, Université Montpellier1 Montpellier, France Bernard Klein Anouk Caraux Wilheminenhospital, Wien, Austria Niklas Zojer Erasmus University Medical Center, Rotterdam, Netherlands Pieter Sonneveld

SERVICIO DE CITOMETRIA, DEPARTAMENTO DE MEDICINA Y CENTRO DE INVESTIGACIÓN DEL CÁNCER (IBMCC) UNIVERSIDAD DE SALAMANCA

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