Rafael Fonseca MD, Mayo Clinic
The classification of myeloma;
subtypes of the disease
Scottsdale, Arizona
Rochester, Minnesota
Jacksonville, Florida
Mayo Clinic College of Medicine
Mayo Clinic Comprehensive Cancer Center
Disclosures
· Consulting: AMGEN, Genzyme, BMS,
Otsuka, Celgene, Lilly, Medtronic
· Speakers Bureaus: None
· Research: Cylene, Proteolix
· Patent for FISH based prognostication in
MM
Classification schemes
Classification schemes
· Biology classification
· Pathophysiology
Translocations
· Progression events
MGUS to MM
· Prognostic classification
· Baseline features
t(4;14)
· Natural history
-17p13
· Predictive classifications
TRAF3
· Therapy specific
Biologic
classification
Prognostic
Predictive
classification
classification
Classification schemes
Classification schemes; How many?
· Global ploidy (H-MM vs NH-MM)
· Translocation
· Progression (-17, 1q+/1pdel)
· NF-kB activated or not
· Mutation; common (ras,p53) & rare (B-RAF)
· Epigenetic subtypes
· Subclones
· miRNA classifiers (previously discussed)
· Truly multidimensional
Genetic Classification of MM
Primary
Secondary
No
IgH
IgH
IgH
TRXs
TRX
TRX
Non
Ploidy
Hyperdiploid
variable
Hyperdiploid
Deletion 13
Less deletion 13
enriched
Fonseca Blood 102:2562, 2003
Genetic Classification of MM
Agnelli et al Brit J of Haematol, 136, 565573
Agnelli et al Hematologica 2007 vol. 92 (1) pp. 56-65
Ploidy and Age
Ross et al Leukemia (2005) 19, 16341642
Ploidy and aCGH
Ploidy and aCGH
Hyperdiploid
Hyperdiploidy Subgroups
125
Cluster 1
100
Cluster 2
Cluster 3
75
Cluster 4
50
25
0
0
250
500
750
1000
1250
Survival (days)
TC Classification
Classification of MM
Bone
Ploidy
Prognosis
H
k/l
Morph
CD20
ras
-13
CCND
DKK1
t(11;14)
D1
NH
Good
G
LPL
+++
++
-/+
++
(CCND3)
D3
t(14;16)
(other
NH
Poor
A
PB
-
-
++
+/-
D2
MAF)
t(4;14)
NH/h
Poor
A
PB
-
-
+++
+/-
D2
VAD vs VD in t(4;14)
t(4;14) vs not; VD Rx
EFS 28 vs 16 mos
Avet-Loiseau H et al. JCO 2010;28:4630-4634
Study population stratified according
to cytogenetic abnormalities
232 pts
Standard-risk
High-risk
no cytogenetic
t(4;14) ± t(14;16)
abnormalities + del (13q)
+ del(17p)
+ t(11;14)
44 pts(19%)
188 pts(80%)
t(4;14)±del(13q)
del(17p)±del(13q)
both
t(14;16)
17 (7%)
21(9%)
3 (1%)
3 (1%)
Overall survival according
to cytogenetic abnormalities
1.0
Standard risk: NR
0.8
pts
of0.6
High risk: 38m
0.4
Proportion
p=0.001
0.2
0.0
HR: 2.3, 95% IC: 1.4-4.0
0
5
10
15
20
25
30
35
40
45
50
Time in months from 1st randomization
Is the t(14;16) prognostic?
Survival by t(14;16) status
Other MAF Translocations
Correlation Between High Risk and MAF
CD56 Expression by t(14;16) status
New Diagnosis MM
P53 deletion/mutation
100%
90%
80%
70%
60%
50%
MGUS
92%
83%
40%
SMM
30%
newly diagnosed MM
20%
33%
first relapse MM
10%
18%
second relapse MM
0%
1%
4%
8.20%
PCL *
HMCLs
Studied 8 patients with 17p deletions at RR 7 did not have deletion at diagnosis
FISH (MGUS n=184, SMM n=116, relapsed MM n=62 and PCL n=26)
aCGH (newly diagnosed MM n=224, relapsed MM n=158 and HMCLs n=48)
p 53 mutational status was evaluated in relapsed MM (n=84) and HMCLs (n=48)
*Tiedemann et al. Leukemia. 2008; 22, 1044-1052
Fonseca. Manuscript in preparation
EFS and OS for -17p VAD vs VD
Avet-Loiseau H et al. JCO 2010;28:4630-4634
GEP signatures
Shaughnessy et al, Blood2007, 109(6), 22762284
Total DML in Tumors and HMCL
Salhia B et al. Cancer Res 2010;70:6934-6944
· CCND1
2%
· Known; ras (50%), NF-kB
· BRAF
4%
(37%), p53 (8%)
·
·
DIS3 (RPP44)
11%
Protein translation 42%
·
·
FAM46C
13%
Histone modifying
enzymes (lead HOXA9)
· XBP1
4%
· Fibrin clot formation 16%
· LRRK2
6%
· IRF
6%
· PRDM1
6%
Nature 24 March 2011, 471:467
Clinical Course - Case Report
Is myeloma like AP CML
So many, many, many, many MM!
· Ultimately all will be...
· An "N of 1"
· All classifiers will be
global approximations
· How many "buckets" to
use is arbitrary and
defined by clinical
N of 1
utilitarian needs
Acknowledgements
Mayo Clinic
Mayo Clinic
TGEN
Keith Stewart
Esteban Braggio
Jeff Trent
Leif Bergsagel
Tr
T avis Henry
John Carpten
Marta Chesi
Samar Issa
Mike Barrett
Phil Greipp
Angela Mayo
Robert Kyle
Jacy Spong
Laboratory
SV Rajkumar
Greg Ahmann
Dysproteinemia Group
Scott Van Wier
Joe Mikhael
Tammy Price-Troska
Craig Reeder
Rachel Hagerty
Gordon Dewald
NUS
Kim Henderson
Wee
W
Joo Chng
Syed Jalal
Laboratory
Rhett Ketterling