genomic heterogeneity of multiple myeloma and implications ... · weinhold et al., blood 2016 . 13...
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Genomic
Heterogeneity of
Multiple Myeloma and
Implications
for Targeted Therapy
and Treatment
Resistance
Niels Weinhold, PhD
September 13, 2016
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Introduction to myeloma genetics
Double-hit myeloma
Private clones
Overview
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3
Introduction to myeloma genetics
Double-hit myeloma
Private clones
Overview
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Primary (initiating) & secondary events
+3
+5
+7
+9
+11
+15
+19
+21
Manier et al., Nat. Rev. Clin. Oncol., 2016
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Primary (initiating) & secondary events
+3
+5
+7
+9
+11
+15
+19
+21
t(MYC)
del(17p)/TP53
del1p32, del1p12 &
gain/amp 1q21
Manier et al., Nat. Rev. Clin. Oncol., 2016
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GEP70: 70 genes associated with outcome
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Primary (initiating) & secondary events
+3
+5
+7
+9
+11
+15
+19
+21
del(17p)/TP53
Presence
vs
Type
Manier et al., Nat. Rev. Clin. Oncol. 2016
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Introduction to myeloma genetics
Double-hit myeloma
Private clones
Overview
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Longitudinal exome sequencing study: overview
Weinhold et al., Blood 2016
17p12 (TP53)
???
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Frequence and prognostic value of TP53 aberrations
Presentation
del(17p) in 5 patients
TP53mut in 4 patients
Relapse
del(17p) in 10 patients
TP53mut in 10 patients
11 patients with one
affected allele
5 patients with double
event
Weinhold et al., Blood 2016
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Acquired double-hits at relapse
Presentation: 18 bi-allelic events in 12 patients
Relapse: 26 bi-allelic events in 17 patients
FAM46C bi-allelic events in 6 patients
Risk at presentation: 4/19 vs. 7/10, P=0.02
Risk at relapse: 3/15 vs. 12/14, P=0.001
Weinhold et al., Blood 2016
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Variant allele frequency: presentation
Va
ria
nt
all
ele
fre
qu
en
cy:
rela
pse
TP53: Competing subclones
NRAS
DIS3
del(17p)
KRAS
DIS3
TP53 Subclonal vs. double hit
Frequency information
for both aberrations
important!
Clonal competition
Pre-existing?
Shared
mutations
Clone with del(17p)
Weinhold et al., Blood 2016
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Introduction to myeloma genetics
Double-hit myeloma
Private clones
Overview
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“Focal lesion” project
Aim: determine the extent of heterogeneity in space
42 newly diagnosed myeloma patients
Whole exome sequencing & high resolution arrays
Paired samples: aspirates from iliac crest & focal lesion(s)
Focal lesions
Accumulations of malignant plasma cells in
restricted areas within the bone marrow
74% of patients with >=1 according to MRI*
Mean number: 10*
Sample 1
“Random” aspirate
from iliac crest
Paired sample(s)
Focal lesion(s)
*Walker et al. JCO 2007
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Heterogeneity: “primary” event hyperdiploidy
shared unshared Not present
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Heterogeneity: ploidy
Focal lesion (L4)
Iliac crest
Trisomies: hyperdiploid karyotype
Initiating event???
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Heterogeneity: “primary” t(IgH) and progression events
shared unshared Not present
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Focal lesion (L4)
del(1p) del(17p)
Heterogeneity in space: high risk & bi-allelic event
TP53 Pre-existing ultra-high-risk event!!!
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Mutations: types of heterogeneity
Shared
minor>major
Unshared
Variant allele frequency: random aspirate (iliac crest)
Va
ria
nt
all
ele
fre
qu
en
cy:
foca
l le
sio
n
Shared
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Total number of mutations and heterogeneity
Median total:64
Min->major clone
Unshared >=20% VAF
Unshared <20% VAF 0% (0-26%)
11% (0-62%)
5% (0-42%)
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Actionable and driver mutations: distribution
“Driver” genes (Other) actionable mutations*
*Walker et al. JCO 2015
Nr of patients
with mutation
Blue = unshared
Mutations in “driver” genes are not
necessarily shared
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BRAF V600E as target: example
BRAF mutat ion in 1/ 3 of reads
Trisomy 7
Majority of cells with mutat ion
“Good target !”
Expectation*
*Andrulis et al. Cancer Discovery 2013
BRAF
???
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Same patient: clonality analysis based on seq data
Clone in
focal
lesion
Clone at
iliac crest
Variant allele frequency: random aspirate (iliac crest)
Va
ria
nt
all
ele
fre
qu
en
cy:
foca
l le
sio
n
BRAF
High
Risk
Low risk
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KRAS
FGF12
BRAF STAT3
Site-specific dominance
Allopatric speciation?
Impact on standard risk stratification?
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GEP70: random aspirate vs. focal lesion
42
(16%)
GEP70 focal lesion
221
(84%)
Regionally restricted dominance
of high risk clones!
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Outcome according to GEP70 of paired samples
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Spatial analyses: conclusions
Heterogeneity in space in majority of cases on the nucleotide level
Full spectrum of mutations not detectable with single sample
“Driver” and other actionable mutations are frequently non-
ubiquitous
High risk sub-clones frequently unequally distributed
Targeted treatment may even support high risk clones
Possible explanation for low sensitivity of high risk markers
“Simple” Darwinian model (clonal sweeps) does not explain
patterns in myeloma
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Acknowledgements
Thank you for your
attention!