Genomic Sequencing in Myeloma:

Ready for Prime Time?

DANA-FARBER CANCER

INSTITUTE

Nikhil C. Munshi, MD Professor of Medicine

Harvard Medical SchoolBoston VA Healthcare System

Director Basic and Correlative SciencesDana-Farber Cancer Institute

Multiple Myeloma – Genomic Studies

Normal MGUS Myeloma 55 MM Cell Lines; 73 Patient Samples

Gene Expression Profile aCGH

192 Newly Dx patients - HDT

Cytogenetics/FISH SNP Array Copy Number Alteration

Microarray gene expression datasetsStudy IFM 2005# IFM 2005# HOVON 65

MM / GMMG $APEX /SUMMIT

Number of Samples 136 67 282 162

Platform Affymetrix Exon 1.0 ST array

Affymetrix Exon 1.0 ST array

Affymetrix U133 Plus 2.0 array

Affymetrix U133 Plus 2.0 array

Treatment Protocol VAD, ASCT

Bortezomib, ASCT

VAD/PAD, ASCT

Bortezomib

Response Measurement

Post-Transplant

Post-Induction

Post-Transplant

Post-novel agent Relapsed

Complete Response 44 (32%) 24 (36 %) 76 (27 %) 73 (43%)∞

#: Unpublished, in preparation$: Broyl A, et al. Blood 2010

∞: Post-refractory cases from APEX and SUMMIT trials; 13 patients had CR and 60 had PR.

Gene Expression Profile-based Response Prediction

Amin et al. Blood 2011

Low Accuracy of Prediction

Method Sensitivity Specificity PPV NPV AccuracySVM RBF 56 63 62 75 64SVM Polynomial 52 63 60 68 62SVM Linear 51 62 64 72 64Decision Tree 49 70 56 76 61KNN (n=10) 53 71 57 64 63LDA 48 66 60 63 60DLDA 42 69 63 75 64PAM 54 74 60 70 68Bayesian 54 64 65 72 68ANN 49 68 58 70 60

Amin et al. Blood 2011

High-throughput genomic analysis spanning all regulatory checkpoints

Genome

MutationsCopy Number

WGSaCGH/SNP

array

RNAtranscript

RNA level

Transcriptional Control

RNAsplicing

RNA Processing

GEP arrayMethylation Array

Exon arrays

miRNA

miRNA arrays

RNA level

RNA Modification

Translation

Protein

Post-translational Modifications

Functional proteins*

ProteamicsAcytylomePhosphome*

What is the Purpose of Genome Sequencing?

• Diagnostic end points

• Understand the biology

• Prognostication

• Therapeutic application

Somatic variants in Multiple Myeloma

MISSENSE SYNONIMOUS NONSENSE STOP_LOST INTRON

2342

841

1721

561

Type of mutation

C->A/G->T C->G/G->C T->A/A->T T->G/A->C C->T/G->A T->C/A->GTransversions Transitions

608 532

267 283

1704

522

Nucleotide Change

20

60

Average n.

PD5850a

PD5852a

PD5854a

PD5856a

PD5858a

PD5860a

PD5862a

PD5864a

PD5866a

PD5868a

PD5870a

PD5872a

PD5874a

PD5876a

PD5878a

PD5880a

PD5882a

PD5884a

PD5886a

PD5888a

PD5890a

PD5892a

PD5894a

PD5896a

PD5898a

PD5900a

PD7181c

PD4285

PD4288

PD4291

PD4293

PD4296

PD43000

50

100

150

200

250

300

350

400

450

Validated Substitutions

Heterogeneity of Somatic Variants

Non-synonymous variant recurrenceGene n. of cases % recurrentKRAS 16 23.9%BRAF 9 21.4%NRAS 8 11.9%RYR2 8 11.9%FSIP2 7 10.4%TP53 7 10.4%FAT4 5 7.5%HMCN1 5 7.5%DNAH5 5 7.5%ZFHX4 5 7.5%PEG3AS 5 7.5%FLG 4 6.0%PTPRZ1 4 6.0%DNAH9 4 6.0%GPR98 4 6.0%

*Futreal A.P. et al, Nat Rev Cancer (2004).4,177-183

Total n. of genes found in screen 2462Cancer Census* Genes 83Non Cancer Census Genes 2379

Recurrent ≥2 396Unique 2066

Unique; 2066

Recurrent

<5%; 367

Recurrent 5-10%; 23

Recurrent 10-15%; 5

Recurrent >20%; 1

Distribution of genes

Prevalence of Somatic Mutations Across Human Cancers

Alexandrov et al Nature 2013

Mutational Profile in Myeloma

Waldenstrom’s macroglobulinemia

Mutational Profile in Myeloma

Prognostic Implications of Mutations in Myeloma

Frequency of

Mutation

SubclonalFraction

(Bolli et al. Nature Comms, 2014)

Immunohistochemical and molecular characterization of BRAF V600E mutation status in multiple myeloma.

Andrulis M et al. Cancer Discovery 2013;3:862-869

©2013 by American Association for Cancer Research

Patient With BRAF V600E - Response to Vemurafenib

Andrulis M et al. Cancer Discovery 2013;3:862-869

©2013 by American Association for Cancer Research

Only 4/9 of BRAF mutations are activating

Patient Gene ProteinPD4285 KRAS p.G12APD4286 KRAS p.Q61HPD4289 KRAS p.Q61HPD4289 BRAF p.G466VPD4292 BRAF p.D380YPD4294 BRAF p.D594GPD4296 KRAS p.G12CPD4301 NRAS p.Q61HPD5851a NRAS p.G12SPD5859a KRAS p.G12APD5861a KRAS p.A146VPD5865a KRAS p.Q61HPD5865a BRAF p.V600EPD5869a NRAS p.Q61KPD5871a BRAF p.V600EPD5874a BRAF p.E586KPD5875a NRAS p.Q61RPD5876a KRAS p.Q61HPD5878a KRAS p.G12RPD5878a BRAF p.G596VPD5882a BRAF p.V600EPD5885a KRAS p.Q61RPD5886a NRAS p.Q61RPD5887a KRAS p.Q61HPD5888a KRAS p.Q22KPD5889a KRAS p.G12CPD5890a KRAS p.G12VPD5891a BRAF p.G466VPD5892a NRAS p.G13RPD5894a KRAS p.Q61KPD5895a KRAS p.Q61LPD5901a NRAS p.Q61RPD7181 NRAS p.Q61R

Patient Gene Protein Kinase Activity*PD4289 BRAF p.G466V ImpairedPD4292 BRAF p.D380Y ?PD4294 BRAF p.D594G ImpairedPD5865a BRAF p.V600E HighPD5871a BRAF p.V600E HighPD5874a BRAF p.E586K HighPD5878a BRAF p.G596V ImpairedPD5882a BRAF p.V600E HighPD5891a BRAF p.G466V Impaired

Impaired; 4

?; 1

High; 4

BRAF KINASE ACTIVITY

*Wan et al, Cell 2004 vol. 116 (6) pp. 855-67

Outline• Subclonal diversification in myeloma

• Genomic evolution over time

RAS-RAF mutations are often late and convergent

Clonal Evolution in Myeloma

• Whole exome sequencing in 15 patients with serial samples collected at the time of progression at least 4 months apart

To evaluate change in clonal composition at progression.

• Normal tissue samples • SNP array identified changes compared between

early and later samples.

Subclonal fraction early sample

Sub

clon

al f

ract

ion

late

sam

ple

Cluster of clonal mutations –in all cells

Cluster of clonal mutations- Lost in late sample

Cluster of clonal mutations - Acquired in late sample

Branching evolution

(Bolli et al. Nature Comms, 2014)

Patterns of genomic evolution

Driver mutations emerge over time

Next-Generation Sequencing Method

LymphoSIGHT platform: Sequencing of Immunoglobulin gene

CTGGCCCCAGTAGTCATACCAACTAGCGTTGGCCCCAGAAATCAAGACCATCTAAAACGGCCCCAGAGATCGAAGTACCAGTGTTTGGCCCCAGACGTCCATATTGTAGTAGCTGGCCCCAGAAGTCAGACCGGCTAACA

Collect marrow and

Purify Myeloma

cells

Extract DNA Multiplex PCR to

amplify VDJ

Common PCR to prepare for

sequencing

Sequence ~1M 100bp reads

gDNA ORmRNA

PCR amplicons Sequencing library

Sequence dataMyeloma Cells

• Identification of all “clonotypes” in the sample

• Determination of the frequency of each clonotype

ResultsEvidence of Oligoclonality

• Observed evidence of more than one clone with distinct Ig sequences

• Unrelated clones: Clones whose common ancestor is before the pre B cell stage

• Related sequences: Clones with a late common ancestor (related clones)

23

77%

7%

16%

One CloneUnrelated ClonesRelated Clones

Related and Unrelated Subclones: Case 4

• Two minor clones are highly similar but unrelated to the major clone

Clone 2 (6%)

Clone 3 (1%)

VH3 DH1 JH1N N

VH1 DH2 JH6N N

Clone 1 (86%)

VH1 DH2 JH6N N

C

Bases indicated are mutations from the germline sequence

A

A

Clinical implications of subclonal diversification

• Evolution is a continuous process

• All patients with myeloma have evidence for subclonal diversification

• RAS-RAF pathway mutations frequently subclonal, with convergence• Likely to affect response to kinase inhibitors

• Different clones likely to have variable treatment response, growth dynamics, Ab production etc

Outline• Subclonal diversification in myeloma• Genomic evolution over time• Expression of mutant allele

Limited Expression of Mutated GenesWhat Mutations Are Relevant?

(Rashid et al. Blood, 2014 In Press)

27%

Not All Mutations are Expressed: Not Even Drivers

(Rashid et al. Blood, 2014 In Press)

97.1

1.5

Sample 1

Clone 1

Clone 2

25.5

74.5

Sample 1Clone 1 Clone 2others

Sample 2

Clone 1

Sample 2

Clone 1

93.5

0.3

Sample 3 Clone 1Clone 2

68.8

16.2

Sample 3Clone 1Clone 2

Sample 4

Clone 1

Sample 4

Clone 1

84.7

7.9

Sample 5Clone 1Clone 2

99.8

Sample 5

Clone 1Clone 2

Differential Expression of

Individual Clones

DNA RNA

IFM/DFCI 2009 StudyNewly Diagnosed MM (N=1,000)

RVDx3

RVD x 2

RVD x 5

Revlimid 18 mos

Melphalan 200mg/m2* +

ASCT

Induction

Consolidation

Maintenance

CY (3g/m2) MOBILIZATIONGoal: 5 x106 cells/kg

RVDx3

CY (3g/m2)MOBILIZATIONGoal: 5 x106 cells/kg

Randomize

Collection

Revlimid 18 mosSCT at relapse

Calibration

MRD

MRD

MRD

MR

D @

CRM

RD

@ C

R

Clinical Implication• Different patterns of disease evolution over time

across patients. Need for repeated genomic analysis

• Most frequent and not so frequent mutations have been identified – Providing new targets

• Limited expression of mutant allele – Need to confirm functional impact of gene mutation.

• Except for MEK/ERK pathway no other mutation is observed in > 10% - Are there number of myeloma sub groups with clonal variability?

• Sub clonal variants and clonal evolution – Need for multi target therapy and develop clone control mechanisms

Is Genome Sequencing Ready for Prime Time?

• Yes - For limited POP targeted therapy studies

- To understand the biology

• No - Diagnostic end points

- Prognostication

- Wider therapeutic application

High-throughput genomic analysis spanning all regulatory checkpoints

Genome

MutationsCopy Number

WGSaCGH/SNP

array

RNAtranscript

RNA level

Transcriptional Control

RNAsplicing

RNA Processing

GEP arrayMethylation Array

Exon arrays

miRNA

miRNA arrays

RNA level

RNA Modification

Translation

Protein

Post-translational Modifications

Functional proteins*

ProteamicsAcytylomePhosphome*

Masood Shammas, PhDPrabhala Rao, PhDMariateresa Fulciniti, PhDWeihua Song, MDJagannath Pal, MD, PhDPuru Nanjappa, PhDJianhong Lin, MDMaria Gkotzamanidou , MD, PhDAdan Soerling, MD, PhDWeihong Zhang, MDTeresa Calimari, MDAriel Kwart, BSSophia Adamia, PhDRajya Bandi, MS

YuTzu Tai, MDJooeun Bae, PhD

Kenneth Anderson, MD

Giovanni Parmigiani, PhDCheng Li, PhDYi Li, PhDNaim Rashid, PhD and Mehmet Samur, PhD Bioinformatics Group

Dr. Herve Avet-LousieuDr Stephane Miniville, Dr. Philippe MoreauDr. Florence MAGRANGEASDr. Michel Attal and IFM

Peter CampbellAndy FutrealGraham Bignell Niccolo BoliDavid Wage

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