HIGH-RISK MULTIPLE MYELOMA (MM): DISTINGUISHING EARLY FAILURES (EF)

FROM SUSTAINED CONTROL (SC)

B. Barlogie, J. D. Shaughnessy Jr, J. Haessler, A. Hoering, F. Van Rhee, E. J. Anaissie, J.

Crowley

University of Arkansas for Medical Sciences Little Rock, AR

Cancer Research And Biostatistics Seattle, WA

BACKGROUND

• MYELOMA COMPRISES MULTIPLE ENTITIES WITH DISCRETELY

DIFFERENT OUTCOMES BEST CAPTURED BY GEP-BASED RISK

DESIGNATION (70-GENE MODEL)

• WITH TT2, MEDIAN SURVIVAL OF 2 YEARS IN 15% WITH HIGH-RISK

MYELOMA CONTRASTS WITH 10-YEAR SURVIVAL ESTIMATE OF 60%

IN LOW-RISK DISEASE

• IN HIGH-RISK MYELOMA, KAPLAN-MEIER PLOTS REVEAL 2 SUBSETS

– EARLY FAILURE (EF) WITH STEEP INITIAL SURVIVAL DROP-OFF

– SUSTAINED CONTROL (SC) WITH SHALLOW SLOPE AND EXTENDED

SURVIVAL

TT2 (BOTH ARMS): CLINICAL OUTCOMES ACCORDING TO GEP-DEFINED RISK

OVERALL SURVIVAL

0%

20%

40%

60%

80%

100%

0 2 4 6 8 10

Years from Start of Protocol Therapy

Low Risk: 109/305

High Risk: 35/46P < 0.0001

EVENT-FREE SURVIVAL

0%

20%

40%

60%

80%

100%

0 2 4 6 8 10

Years from Start of Protocol Therapy

Low Risk: 186/305

High Risk: 39/46P < 0.0001

2 distinct components in high-risk disease: early failure (EF) and sustained control (SC): breakpoint at 3 years

EF SCEF SC

OBJECTIVES

• AMONG 15% OF PATIENTS WITH HIGH-RISK MYELOMA

TREATED WITH TT2 AND TT3, DETERMINE WHETHER

EF AND SC SUBSETS CAN BE DISTINGUISHED AT

BASELINE BY

– STANDARD PROGNOSTIC FACTORS

– PLASMA-CELL GENE EXPRESSION PROFILING (GEP)

• DEFINE GENES THAT DISTINGUISH EF AND SC SUBSETS

TOWARD IMPROVING THERAPY OF HIGH-RISK

MYELOMA

PATIENTS & METHODS

• PATIENT POPULATION

– 123 WITH HIGH-RISK MYELOMA IN TT2 AND TT3

• SC vs EF DISTINCTION

– >=3YR OVERALL SURVIVAL vs REMAINDER

– >=3YR SUSTAINED CR vs EVENT WITHIN 1YR

• LOGISTIC REGRESSION ANALYSIS TO SEGREGATE EF FROM

SC BASED ON GEP AND STANDARD VARIABLES

HIGHER FREQUENCY OF UNFAVORABLE GEP FEATURES IN EF vs SC MYELOMA

SURVIVAL MODEL CR DUR MODEL

VARIABLEEF

(N=65)SC

(N=58)P

EF (N=38)

SC (N=28)

P

B2M >=5.5mg/L 45% 50% 0.55 45% 32% 0.30

Albumin <3.5g/dL 49% 45% 0.63 50% 29% 0.08

LDH >= 190 U/L 60% 43% 0.06 66% 50% 0.20

CA 78% 67% 0.18 78% 79% 0.99

GEP >median score 60% 38% <0.02 68% 39% 0.02

GEP delTP53 22% 5% <0.01 18% 7% 0.28

MV LOGISTIC REGRESSION ANALYSIS OF VARIABLES LINKED TO EF vs SC

* > MEDIAN IN HIGH-RISK MM

% EF WITH FACTOR

MODEL Variable N YES NO OR P

SURVIVAL GEP delTP53 120 81% 48% 4.60 0.025

GEP very high risk* 120 64% 42% 2.41 0.022

CR DURATION GEP very high risk* 64 69% 41% 3.09 0.031

SHIFT TO HIGHER GEP RISK SCORE IN EF vs SC HIGH-RISK MYELOMA

Approximate Distribution of GEP risk score by failure time

Risk Score

Den

sity

SCEF

-1 0 1 2 3 4

0.0

0.5

1.0

1.5

2.0

p-value=0.007

Approximate Distribution of GEP risk score by failure time

Risk Score

Den

sity

SCEF

-1 0 1 2 3 4

0.0

0.5

1.0

1.5

p-value=0.003

SURVIVAL MODEL CR DURATION MODEL

SCEF

SURVIVAL MODEL-BASED GEP DIFFERENCES BETWEEN EF AND SC

Approximate Distribution of GEP PI by failure time

GEP proliferation index

Den

sity

SCEF

-5 0 5 10 15 20 25

0.00

0.02

0.04

0.06

0.08

0.10

0.12

p-value=0.015

Most CD-1 is EF Shift to higher PI in EF vs SCMolecular subgroup designation

Failure Time EFSC

Frequency

0

10

20

30

40

50

60

GEP Subgroup

CD-1 CD-2 HY LB MF MS MY PR

p-value=0.348

60

40

30

10

20

50

Freq

uenc

y

0.10

0.8

0.4

0.2

0

0.6

0.12

PRMYMSMFLBHYCD-2CD-1

14 GENES DISTINGUISH EF AND SC SUBGROUPS OF HIGH-RISK MYELOMA

EF SC

C20orf142TP53INPST6GAL1235659_atYIPF6MAN2A1MEIS1SPIBRNF43SHISASLC43A3PLK1RUNX2PMAIP1

P < 0.0001 (FDR: 15.8%)

Gene Description Chr

SHISA

WNT repressor and head inducer; endoplasmic reticulum; Wnt ligand signals through co-receptor on PM; single pass LRP5 and seven pass Frizzled (Fz); SHISA removes Frizzled receptor from PM via ER retention; NOTE: DKK1, head inducer; secreted; WNT repressor; removes LRP5/6 from PM thru endocytosis; Supports role for Wnt suppression in MM pathogenesis

4p13

PLK1

S/K kinase; nuclear; regulates centrosome maturation, spindle assembly, chromosome arm cohesions, APC/C inhibition, mitotic exit and cytokinesis; Interacts with EVI5, EVI5 is one of 19 in GEP70; may suppress EVI5?

16p12

SPIBEts family transcription factor; nuclear; controls pDC and B-cell development; expressed in liver stem cells; linked to recent surge in liver mets?; Is EF disease a plasmacytoid dendritic cell neoplasm? 19q13

TP53INP1TP53 inducible; nuclear; concentrated in PML/POD/ND10 nuclear bodies; induces TP53-phosphorylation and TP53-mediated apoptosis 8q22

MAN2A1Complex N-glycan biosynthesis; Golgi; Mutations causes SLE-like Dx in mice; inversely correlated with SHISA; Does Wnt suppression eliminate N-glycan modifications in MM cells? 5q21.2

EXAMPLES OF EF-ASSOCIATED GENES

TP53INP1

Apoptosis

•Adriamycin•H2O2

•gamma irradiation

TP53-p

TP53

TP53 targetsTP53INP1

TP53INP1 ON CHROMOSOME 8q22 TP53-DEPENDENT DAMAGE-INDUCIBLE NUCLEAR PROTEIN

1

Over-expression of TP53INP1 linked to

SC with better outcome in high-

risk myeloma

Vel and VTDPACE PGx: Differential Sensitivity of TP53INP1 to Induction Chemo

UP-REGULATION WITHIN 48HR OF TP53INP1 BY BORTEZOMIB AND AUGMENTED BY ADDED TDPACE

RANKING TP53INP1 BASELINE VALUES FROM LOW TO HIGH,48HR F/U POST-VEL & VTDPACE AS PART OF TOTAL THERAPY 3

TP53INP1 PGx Melphalan (10mg/m2 x 48h) in Newly Diagnosed Disease

TP53INP1 CAN BE UP-REGULATED BY TEST DOSE OF MELPHALAN 10MG/M2 IN 48HR

SUMMARY & CONCLUSIONS

• Compared to SC, EF characterized by– Higher 70-gene risk scores (“super-risk”)– Lower delTP53 scores

• Among 14 EF-SC discriminating genes, TP53INP1 of particular interest:– Over-expression in SC linked to apoptosis and

better clinical outcome– Rapidly inducible by melphalan and bortezomib

in patients with low levels of TP53INP1 expression

– Hence not just biomarker but therapeutic target

ISSUES UNDER STUDY

• Develop “super-high risk” model– Examine its potential of distinguishing poorly performing

outliers in low-risk myeloma– Role in predicting post-relapse survival?

• Examine super-high risk-associated genes in context of molecular subgroups – CD-1?

• Determine bone marrow environment-unique genomic features in EF vs SC

• Examine modulation of super-high risk genes by anti-myeloma agents, e.g. MEL & BOR as rapid inducers of TP53INP1 to restore MM-cell sensitivity

THANKS TO

• Patients & referring physicians• MIRT faculty and staff• Granting agencies

– NCI Program Project grant– MMRF

• Philanthropy– Lambert, LeBow, Grand

Foundation