High Risk Myeloma

Dr Matthew Jenner Consultant Haematologist Southampton General Hospital 15 September 2014

Introduction

• Myeloma heterogeneous disease

• Clinical spectrum • Progression through

different stages of disease: – Premalignant MGUS – Smouldering

(asymptomatic) myeloma – Symptomatic myeloma – Relapsed and refractory

myeloma – Plasma cell leukaemia

• Younger age through to very old age

Variables that impact prognosis in any malignancy

• Patient factors – ‘fitness’ (age, PS etc.)

• Tumour stage

– in myeloma, markers of disease bulk

• Tumour biology – Genetic lesions detected by cytogenetics, gene

expression or mutation analysis – Response to treatment

• Treatment options for high risk myeloma

Patient factors and outcome

Patient factors • Age • Performance status (activity levels) • Co-morbidities • Medication • Kidney function

Tumour factors and stage

Tumour factors and stage

• Tumour factors – Haemoglobin – White cell count – Platelet count

• Bone disease • Renal toxicity • Paraprotein factors

– Type of paraprotein – Beta 2 macroglobulin

• Site of disease • Immunophenotype/MRD • Prior response

Copyright ©2006 American Society of Hematology. Copyright restrictions may apply.

Drayson, M. et al. Blood 2006;108:2013-2019

Figure 1. Overall survival by paraprotein class Paraprotein class and overall survival

The ISS • Combines tumour and patient factors • β2M is associated with disease bulk and renal

function • Albumin is associated with general condition of

patient and tumour burden

Greipp et al, JCO, 2005: 23;3412

The ISS

Greipp et al, JCO, 2005: 23;3412

p=9.36E-23

I n=347 ms 83 mo II n=544 ms 48 mo III n=513 ms 35 mo

ISS

Overall Survival

Myeloma IX - The ISS

Greipp: I: 62 mo II: 44 mo III: 29 mo

Extramedullary myeloma

• Myeloma deposit occurring outside bone marrow • Important to distinguish between bone expansion

vs. true extramedullary disease or tissue invasion • Also to distinguish from solitary plasmacytoma

– Can be cured with radiotherapy alone

Extramedullary myeloma

• True extramedullary disease – Skin – Liver – Gut

• including plasma cell leukaemia (>2 x 109/l circulating plasma cells) – Poor prognosis – More likely to be refractory to chemotherapy – Shorter response to treatment – Associated with a higher rate of adverse genetic

findings

Immunophenotyping

• Normal vs. abnormal plasma cell population • Absolute plasma cell percentage less

important • Aberrant markers • Minimal residual disease

PFS and OS of symptomatic MM patients grouped according to the presence (N = 80) or absence (N = 514) of more than 5% N-PCs/BMPCs at diagnosis.

Paiva B et al. Blood 2009;114:4369-4372 ©2009 by American Society of Hematology

Progression-free survival and overall survival according to the presence or absence of MM-PCs in the bone marrow at day 100 after ASCT.

Paiva B et al. Blood 2008;112:4017-4023 ©2008 by American Society of Hematology

PFS

PFS achieving CR

OS

OS achieving CR

Response to prior treatment

• Depth of response – CR vs. VGPR vs. PR

• Duration of response to treatment – Best predictor of long term outcome in an individual

patient – Remainder of parameters are prognostic but not

necessarily predictive

Genetic factors and outcome

Normal plasma cell development • Terminally

differentiated B lymphocyte

• Undergoes maturation in bone marrow and lymph node

• Plasma cells produce diverse, high affinity antibodies – VDJ recombination – Hypermutation – Immunoglobulin heavy

chain gene (IgH) class switching

Myeloma cytogenetics: historical perspective

chr14

chr1

Cytogenetic abnormalities and outcome

Myeloma cytogenetics: historical perspective

Conventional cytogenetics • Structural and numerical

changes – Gains and loss of

chromosome 1 – Deletion 13 – Gains of odd numbered

chromosomes (hyperdiploidy)

– 14q32 translocations • Successful in less than

30% due to – Low proliferative index of

plasma cells – Low % plasma cells in bone

marrow – High growth rate of other

BM cells

• When abnormalities found, often very complex

• Much less useful than acute leukaemias

• Resolution cytoband level

Characterisation of IgH translocations

Aberrant class switch recombination results in translocations

• Normal CSR: DNA deleted to enable switch from IgM to IgG or IgA production

• Aberrant/illegitamate CSR results in translocation through switch regions to partner chromsomes • Occurs in approx 40% MM and in MGUS and SMM

• t(4;14) translocation results in overexpression of two potential oncogenes FGFR3 and MMSET

IgH translocations in myeloma

Fluorescent in situ hybridisation (FISH) to identify genetic events in pathogenesis of myeloma

• Late 1990s • New techniques have over

come the need for metaphases • Done directly on cells • Can be done on BM aspirate • Ideally the PCs are selected

out using CD138 magnetic beads and the normal cells discarded

• Fluorescently labelled probe is hybridised to cells and visualised

• Structural and numerical changes

• To target known events with predefined probes

• Resolution cytoband level

t(4;14) red=FGFR3; green=IGH Fusion=FGFR3/IGH Normal=2R2G

Copyright ©2005 American Society of Hematology. Copyright restrictions may apply.

Kuehl, W. M. et al. Hematology 2005;2005:346-352

Initiating genetic events in myeloma pathogenesis

Copyright ©2007 American Society of Hematology. Copyright restrictions may apply.

Avet-Loiseau, H. et al. Blood 2007;109:3489-3495

The grey curve is for patients presenting the genomic abnormality, whereas the black curve represents the OS of patients lacking the chromosomal aberration.

Impact of genomic aberrations on overall survival

IFM 99 trials: VAD/Tandem auto VAD/Auto/mini-allo

Copyright ©2010 Ferrata Storti Foundation

Ross, F. M. et al. Haematologica 2010;95:1221-1225

UKMF Cytogenetic Database

Kaplan-Meier survival curves for patients with (A) t(4;14), (B) t(14;16), (C) t(14;20)

Myeloma IX: ‘Bad’ IgH translocations and 17p deletion

n=502

n=106

Intensive arm

Χ2 = 22.553 p = 2.044E-6

Χ2 = 10.881 p = 0.001

n=545

n=46

Intensive arm

“Bad” IgH: t(4;14) t(14;16) t(14;20)

Del(17p)

Courtesy of Fiona Ross

Myeloma IX: 1q gain and 1p32 loss

Χ2 = 19.013 p = 1.01E-5

n=332

n=199

Intensive arm

Χ2 = 11.826 p = 0.001

1p normal, n=457

1p del, n=53

Intensive arm

Courtesy of Fiona Ross

12 24 36 48 60 0

Favourable iFISH Adverse iFISH

0 12 24 36 48 60 OS (months)

0

20

40

60

80

100

Patie

nts

(%)

88 93

81 77

53 44

32 16

10 5

CTDa MP

72

88 93

OS (months)

0

20

40

60

80

100

Patie

nts

(%)

60 55

43 44

23 17

8 8

3 6

CTDa MP

60 55

CTDa MP P < .001

Myeloma IX: Landmark analysis in patients with favourable and adverse iFISH

• In patients with favourable FISH there was a strong OS advantage for CTDa compared to MP.

• This effect was not seen in patients with adverse cytogenetics:

• t(4;14), t(14:16), +1q, del(17p)

CTDa MP P = .41

A B

Morgan Davies et al Blood 2011

Impact of individual genetic factors on outcome

• IgH translocations (chromosome 14) – t(4;14) – t(14;16) – t(14;20)

• loss of chromosome regions – deletion 17p – (deletion 1p in younger patients)

• gain of chromosome regions – gain of 1q

Impact of single lesions

p=0.002

Overall Survival

none n=451 ms 61 mo 17p del n=38 ms 44 mo +1q n=213 ms 41 mo advIGH n=38 ms 39 mo

Impact of combined lesions

p=4.518E-17

Overall Survival

0 n=451 ms 61 mo 1 n=289 ms 42 mo 2 n=113 ms 23 mo 3 n=16 ms 9 mo

Genetic Risk Groups

PFS OS

p=6.36E-15 p=1.08E-15

0 n=451 ms 21 mo 1 n=289 ms 18 m0 >1 n=129 ms 12 mo

0 n=451 ms 61 mo 1 n=289 ms 42 mo >1 n=129 ms 21 mo

Gene expression profiling and copy number analysis

Gene expression profiling

• Global analysis of expressed genes

• DNA code leading to RNA expression

• Upregulated genes: – Oncogenes – Transcription factors – May be targets to be blocked by

drugs • Downregulated genes

– Tumour suppressor genes – May give indication as to

mechanisms of tumourigenesis

Copy number analysis

• High resolution global analysis of gains and losses

• Minimally altered regions contain potential genes of interest

Methods: 500K SNP Mapping and Expression Data

1http://biosun1.harvard.edu/complab/dchip/ 2http://plaza.umin.ac.jp/genome/

Tumour and constitutional DNA and RNA from 80 newly diagnosed patients

Data analysis using dChip1 and CNAG2

Nsp

Sty

500K mapping set define regions of interest

Expression arrays

perform supervised expression analysis based on regions of interest

map differentially expressed genes back to regions of interest

Overview

13% patients with a high-risk signature Shaughnessy et al. Blood 2007;109:2276-2284

Gene Expression Profiling: Arkansas 70 gene model

EFS OS

P < 0.001, HR 5.16

P < 0.001, HR 4.51

Gene expression profiling in 250 newly diagnosed patients enrolled in IFM 99 trials: 15 gene model

Identification of a 15-gene model which is highly predictive of survival

Decaux et al. J Clin Oncol 2008;26:4798-4805

Survival at 3 years: low-risk group 90.5%, high-risk groups 47.4%

Hazard ratio = 6.77 95% CI: 3.92 to 11.73 P < 0.001

Avet-Loiseau et al. J Clin Oncol 2009;27:4585-90

Copy number analysis: IFM • Genome wide analysis of malignant plasma cells

from 192 patients with newly diagnosed myeloma. • Using high-density, single-nucleotide polymorphism

(SNP) arrays to identify genetic lesions associated with prognosis

• Multivariate analysis retained three independent lesions:

– amp(1q23.3) – amp(5q31.3) – del(12p13.31

amp5q

amp1q

del12p

Avet-Loiseau et al. J Clin Oncol 2009;27:4585-90

Chromosomal multivariate analyses: IFM

Associated with poor outcome Associated with favourable outcome

Impact of genetic factors

• Myeloma IX trial: – Certain abnormalities less good

• Some chromosome 14 translocations • Gain of 1q, loss of 17p

– Multiple abnormalities more important than single abnormalities

• Role of other drugs in overcoming genetic high risk myeloma?

Other drug strategies: Arkansas

• Total therapy – Multidrug sequential treatment (V-DT-PACE) – Intensive chemotherapy – Tandem autologous transplantation – Consolidation/maintenance

• High risk myeloma defined by gene expression profiling

• Lowest risk myeloma does best • t(4;14) no longer high risk

Other drug strategies: French and Italian

• Upfront bortezomib compared to non-bortezomib induction

• Appears to overcome adverse effect of t(4;14) • Less impact on del(17p) • Duration of bortezomib treatment may be

important but duration of bortezomib non-randomised

Phase III Trial of PAD and bortezomib maintenance vs. VAD and thalidomide in Myeloma: Survival

Survival Outcome HR 95% CI P Value PFS Overall From last HDM

0.79 0.82

0.66-0.95 0.66-1.02

.01 .08

OS 0.73 0.56-0.96 .02 Sonneveld P, et al. ASH 2010. Abstract 40.

0

25

50

75

100 Cu

mul

ativ

e %

Pr

ogre

ssio

n Fr

ee

0 12 24 36 48

VAD PAD

373 371

n 243 215

F VAD

PAD

Mos

HR: 0.79 (95% CI: 0.66-0.95; P = .01)

Other drug strategies: Dutch

Kaplan-Meier survival curves of progression-free survival (PFS) and overall survival (OS) according to treatment arm within subgroups according to del(13/13q) or t(4;14) or according

to del(17p).

Sonneveld P et al. JCO 2012;30:2946-2955

©2012 by American Society of Clinical Oncology

Arm A VAD/thal Arm B PAD/bort

Bortezomib appears to overcome adverse effect of del(17p) Perhaps related to adverse impact of thalidomide on del(17p) myeloma?

Other drug strategies: lenalidomide combinations

• Very large studies still awaited • Probable benefit in t(4;14) myeloma • Less clear impact on other abnormalities • Multidrug combinations likely to offer best

outcomes – Nooka et al 2013:

• VRD consolidation post ASCT for 3 years • Median PFS 32/12

Identification of novel agents that improve the survival of patients with high-risk MM. xy plot of percent OS for the 2 arms of randomized controlled clinical trials for patients with different

genetic lesions.

Bergsagel P L et al. Blood 2013;121:884-892

©2013 by American Society of Hematology

Clonal evolution of myeloma samples: impact of successive therapies

Next generation sequencing

• MUK High Risk Trial

High risk myeloma proposal

• Key questions: – Trial concept

• Prospectively identifying high risk newly diagnosed myeloma in a national study

– Treatment approaches • More intensive?

– More pain more gain • More smart?

– Avoid DNA damage • Conventional approach?

Introduction:

• High risk myeloma accounts for 20-30% of presenting cases

• This subset of patients do not benefit from current treatment approaches

• There is a need for this population to develop both – Good diagnostic tools to identify these patients – New treatment strategies

• The high risk trial is a specific trial geared towards fit newly diagnosed high risk patients

• Registration phase: identify high risk patients • Treatment phase: investigate 2 new treatment approaches • Evaluate alongside anticipated best treatment including

maintenance

Diagnosing high risk myeloma

• Our current definition of high risk is based on: - a full blood-count to identify Plasma cell

leukaemia - >1 high risk translocation or copy number

abnormality: - A PCR based expression assay to identify

translocations - MLPA to identify copy number changes such as 1q+,

1p- and 17q - Gene expression profile for High risk profile

(ECM92 score) Kuiper et al (2009) Kaiser et al (2013)

• Cytogenetic inter-relationship

1 7

Deletion 1p- (n=71)

Deletion 17p (n=74)

Adverse translocation (n=144)

6

2 135

60

61

Number gained Frequency

1p- 10%

1q+ 34%

17p 9%

Adverse Translocation 21%

GEP 20%

Overall 25-35%

1 7

Deletion 17p (n=74)

Adverse (n=144)

18

65 71

48

180

Gain 1q (n=264)

20

18 14

ECM92

Cytogenetics

Myeloma IX data

High risk patients perform poorly regardless of the treatment they receive

Myeloma IX experience: median PFS and OS were respectively 13.4 and 24 months

High risk patients perform poorly regardless of the treatment they receive

MM4 Hovon experience: median PFS and OS were respectively 14.4 months and 24.2 months

Prognostic stratification: pre trial entry

1200 newly diagnosed myeloma patients 20-30% lost

20-30% High risk

70% Standard risk

15-20% t(11;14)

60 % Hyper

diploidy

Other

High risk trial

Other trials

ND

MM

CTD CRD CVD

Induction X2 cycles

Max.

VRD- PACE

VRDd

CRD

Mel x4 ASCT VRX12/12

Def

ine

high

risk

sta

tus

R

HDM ASCT VRDX 6

To progression

HDM ASCT Rd

R VRD VRD- PACE VRD

HDM ASCT

VRdX12/12 VRDdX 6

High Risk Trial Proposal

Registration phase: 1200 newly diagnosed patients 8 week turnaround time Randomize 51 patients per arm (153 patients in total).

Endpoints:

Primary phase II: • PFS • Abilility to turn around risk-defining investigations within 8 weeks

Secondary

• Overall survival • Deliverability of treatment • Clinical benefit rate • Maximum overall response • Time to progression • Time to maximum response • Response at first relapse • Safety • Toxicity • Recruitment rate

Exploratory: To evaluate the potential to reduce genome instability by altering treatment strategies avoiding excessive alkylating agent exposure.

Conclusions

• Multiple myelomas not just multiple myeloma • Patient factors and myeloma factors • Advances in technology and diagnostic

capability • Limited progress with high risk myeloma so far • Strong case for risk stratified approach • Potential for high risk myeloma studies to

answer key questions

Questions?