Download uPA AND PAI-1 FIRST NOVEL TUMOR

2006 European Breast Cancer Meeting
Stockholm, Sweden
20–21 May 2006
USING PROGNOSTIC & PREDICTIVE FACTORS
IN BREAST CANCER
Fatima Cardoso, MD
Jules Bordet Institute & TRANSBIG
PROGNOSTIC FACTOR
%
Treat. A
Treat. B
+
-
PREDICTIVE FACTOR
Case 1
Case 2
Treat. B
%
Treat. B
%
Treat. A
Treat. A
+
-
+
-
WHY DO WE NEED PROGNOSTIC AND PREDICTIVE FACTORS
PROGNOSTIC FACTORS
PREDICTIVE FACTORS
Who needs a treatment?
Which treatment is best?
THERAPEUTIC CHOICES
AVOID UNDER AND OVER TREATMENT
INDIVIDUALIZE TREATMENT
BC GENE EXPRESSION PATTERNS and OUTCOME
Molecular (re-)classification of BC
ER-
ER+
HER-2-like Basal-like Basal-like
1
2
Luminal
1
Luminal
2
Luminal
3
RFS
Adapted from Sotiriou et al, PNAS, 2003
PROGRESS IN ADJUVANT CHEMOTHERAPY FOR
BREAST CANCER
Average
treatment effect
+++
++
+
±
Financial
toxicity
d)  20.000 $
c) 13.800 $
b)  7.400 $
a)  800 $
TAC x 6
FEC  docetaxel
+++
AC  paclitaxel dose-dense
FAC  FEC x 6
++
A(E)  CMF
CMF x 6 AC x 4  Paclitaxel x 4
+
AC x 4
L-PAM, MF
±
1970’s
1980’s
1990’s
2000’s
Successive generations of adjuvant CT regimens
+++ ADJUVANT TRASTUZUMAB +++
Adapted with permission from G. Hortobagyi
St Gallen 2005 Consensus: What’s new?
• New prognostic factors accepted: HER-2, vascular
invasion
• Node+ 1-3: in average risk group, if HER-2– and no
vascular invasion
Beyond St Gallen 2005 …
uPA, PAI-1
Cyclin E
Oncotype DX*
(predictive & Px)
Genomic
signatures
Topo-II-
*Genomic Health
uPA-PAI-1
CLINICAL RELEVANCE OF uPA & PAI-1 IN PRIMARY
BREAST CANCER
uPA and PAI-1: first novel tumor biological factors in breast cancer
with clinical relevance validated at highest level of evidence (LOE I)
 Standardized quality assured ELISA tests:
Sweep et al, Br J Cancer 78: 1434-41, 1998
 Prospective multi-center therapy trial („Chemo N0“):
Jänicke et al, JNCI 93: 913-20, 2001
 EORTC RBG meta analysis (n=8,377):
Look et al, JNCI 94:116-28, 2002
 Recommended for clinical risk assessment:
AGO Therapy Guidelines „breast cancer“ (since 2002):www.ago-online.de
N. Harbeck – used with permission
uPA AND PAI-1
FIRST NOVEL TUMOR BIOLOGICAL FACTORS IN BC WITH
LEVEL 1 OF EVIDENCE
WHY ARE THEY NOT WIDELY USED?
1. ELISA not commonly used in pathological practice
a. Biochemistry lab required
b. Further personnel training required
c. €€££$$ required
2. Frozen tumor specimen required
3. Large quantity (100 µg) required
Target population = small tumors – feasible ?
4. Population used in validation studies: Interaction with
ER status not well defined (?)
uPA AND PAI-1
FIRST NOVEL TUMOR BIOLOGICAL FACTORS IN BC WITH
LEVEL 1 OF EVIDENCE
HOW CAN THEY BECOME WIDELY USED?
1. Refining ELISA test
– less tissue
2. Alternative techniques
– other protein assays
– gene expression
3. Further validation according to ER status
ALL
ONGOING
GENOMIC SIGNATURES
IMPROVED RISK ASSESSMENT OF EARLY BREAST
CANCER THROUGH GENE EXPRESSION PROFILING
microarray
Gene-expression profile
Good signature
~4% die of breast cancer
~96% survive breast cancer
Poor signature
~50% die of breast cancer
~50% survive breast cancer
N Engl J Med, Vol 347 (25), Dec. 2002
BIG-TRANSBIG Secretariat– Used with permission
TRANSLATING
MOLECULAR
KNOWLEDGE
INTO EARLY
BREAST CANCER
MANAGEMENT
INDEPENDENT VALIDATION : DESIGN
Target
n = 400
Amsterdam
RNA
Achieved
n = 307
Tissue samples
 UK (Guy’s, Oxford) :
1984 => 1996
 France (IGR, CRH) :
1978 => 1998
 Sweden (Karolinska) :
1980 => 1990
• Node negative, untreated
• < 60 years old
• > 5 years follow-up
• T1, T2
• Tumor cell % > 50%
Gene expression
profiling
• Agilent platform
• 70-gene prognostic
custom designed
chip
Clinical data
« Local » pathological data
Audited
clinical
data
Centrally
reviewed
path data
(Milan)
High or
low gene
signature
risk
Brussels
Comparison of
clinical vs gene
signature
assessment of
prognostic risk
Endpoints
1. TDM
2. OS
3. DMFS, DFS
BIG-TRANSBIG Secretariat– Used with permission
OVERALL SURVIVAL by GENE SIGNATURE RISK
Amsterdam/Agendia Signature
0.6
10-year OS
70% (62%-76%)
0.4
Probability
0.8
1.0
10-year OS
89% (81%-94%)
0.2
Patients Events Risk group
16 Genetic low risk
66 Genetic high risk
0.0
113
194
0
2
4
6
8
10
12
14
98
130
82
110
69
90
45
53
Year
113
194
112
185
105
168
101
147
Number at risk
38 CLR
39 CHR
Average Survival HR  2.66
M. Buyse et al. JNCI 2006. In press
BIG-TRANSBIG Secretariat– Used with permission
TRANSBIG INDEPENDENT VALIDATION
The best signature?
Amsterdam’s Signature
70 genes
Rotterdam’s Signature
76 genes
Brussels’ GGI signature
Only few genes in common …
But similar biological pathways
TEST ALL IN VALIDATION SERIES & DECIDE
BIG-TRANSBIG Secretariat– Used with permission
1.0
OVERALL SURVIVAL by GENE SIGNATURE RISK
Rotterdam/Veridex Signature
0.6
low risk group: 0.98 (0.88-1.00)
0.4
high risk group: 0.84 (0.77-0.89)
10 year survival:
PatientsEvents Risk group
0.2
Probability
0.8
5-year survival:
55
143
6
39
low risk group: 0.87 (0.73-0.94)
Good signature
Poor signature
0.0
HR (95% CI): 2.87 (1.21-6.82)
0
2
high risk group: 0.72 (0.63-0.78)
Logrank P= 0.0126
4
6
8
10
46
98
38
89
Year
Good signature 55
Poor signature 143
55
138
C. Desmedt et al. Presentated at: EBCC 2006
52
51
124
106
Number at risk
BIG-TRANSBIG Secretariat– Used with permission
CONCLUSIONS VALIDATION PHASE
• The Amsterdam 70-gene signature has been independently
validated
• The Rotterdam 76-gene & Genomic Grade signatures have been
independently validated using the same TRANSBIG validation
series
• The performances of the signatures are similar
• There is a strong time dependency of all signatures (better
predictors of EARLY RELAPSE), which was not seen for the
clinical risk
• The Amsterdam 70-gene test is robust (laboratory reproducibility)
and available for patient diagnostic testing
• GREEN LIGHT FOR MINDACT TRIAL!
EORTC-BIG MINDACT TRIAL DESIGN
6,000 Node negative women
Evaluate Clinical-Pathological risk and 70-gene signature risk
55%
32%
N=3300
Clinical-pathological
and 70-gene both
HIGH risk
Discordant cases
Clin-Path HIGH
70-gene LOW
13%
N=780
Clinical-pathological
and 70-gene both LOW
risk
Clin-Path LOW
70-gene HIGH
N=1920
Use Clin-Path risk to decide
Chemo or not
R1
Use 70-gene risk to decide
Chemo or not
Chemotherapy
Endocrine therapy
Potential CT sparing in 10-15% pts
GENOMIC GRADE
Sotiriou et al., ASCO 2005
Histologic
Grade
Genomic
Grade
G1
GG1
G2
GG2
G3
GG3
• Poor inter observer reproducibility
• G2: difficult treatment decision
making, under- or over treatment
likely
C. Sotiriou – used with permission
• Findings consistent across multiple
data sets and microarray platforms
• More objective assessment
• Easier treatment decision-making
• High proportion of genes involved in
cell proliferation !
GENOMIC GRADE IN EACH OF THE
HISTOLOGIC GRADE SUBGROUPS
Histological Grade 1
Histological Grade 2
HG1
Genomic Grade 1
C. Sotiriou et al. JNCI 2006
Histological Grade 3
HG3
HG2
Genomic Grade 3
C. Sotiriou – used with permission
Oncotype DX
NSABP & Genomic Health
MULTI GENE RT-PCR ASSAY FOR PREDICTING
RECURRENCE IN NODE NEGATIVE BC PATIENTS
Tested using
RT-PCR
Three studies
250 candidate
genes
21 GENE PREDICTOR
low
Recurrence score
intermediate
high
THREE BREAST CANCER STUDIES USED TO SELECT
CANDIDATE GENES FOR A RECURRENCE SCORE UNDER
TAMOXIFEN TREATMENT
PROLIFERATION
Ki-67
STK15
Survivin
Cyclin B1
MYBL2
INVASION
Stromolysin 3
Cathepsin L2
Best RT-PCR performance
and most robust predictors
Recurrence score for TAM-treated pts
established and subsequently validated
HER2
GRB7
HER2
ESTROGEN
ER
PGR
Bcl2
SCUBE2
GSTM1
CD68
BAG1
REFERENCE
Beta-actin
GAPDH
RPLPO
GUS
TFRC
Paik et al, N Engl J Med 2004
B14-RESULTS
DRFS—Low, Intermediate, High RS Groups
100%
90%
338 pts
80%
149 pts
70%
181 pts
60%
50%
DRFS
40%
30%
20%
Low Risk (RS <18)
Intermediate Risk (RS 18 - 30)
High Risk (RS  31)
10%
0%
0
2
4
6
8
10
12
14
16
Years
Paik et al, N Engl J Med 2004
PREDICTIVE MARKERS
Oxford
Overview
2000
NIH
Consensus
Panel
2000
ASCO
Guidelines
2001
St Gallen
Consensus
Panel
2003
Accepted
Predictive Markers
In Breast Cancer
HER-2 neu
95% Negative predictive value
ER/PgR
30-70% Positive predictive
value
<5% chances of responding to
TRASTUZUMAB (HER-2) or to HT (ER)
30%-70% chances of responding to
HT (ER) & 40%-50% of responding to
TRASTUZUMAB (HER-2)
PREDICTIVE MARKERS FOR
CHEMOTHERAPY
ADJUVANT SETTING
CMF vs. ANTHRA-BASED TOPO II  RESULTS
All pts with HER-2 amplification
FISH
Topo II non-amplified
Topo II amplified
0.9
Anthra-Based
0.9
CMF
0.8
0.7
0.6
CMF
% EFS
0.8
% EFS
IHC
1.0
1.0
0.7
0.5
0.5
0.4
0.4
0.3
0.3
0
12
24
36
Time (Months)
8
15
7
14
4
11
48
Anthra-Based
0.6
Topo II pos.
1.0
0
12
4 CMF 15
9 Anthra 23
24
36
1.0
0.8
48
0.8
0.6
12
17
12
16
11
12
%
HEC
0.4
0.4
HR=0.66 (0.32-1.36)
p=0.25
0.2
Di Leo A et al, Clin Cancer Res, 2002
0.6
CMF
%
15
21
CMF
HEC
Time (Months)
No pts at risk:
4
11
Topo II neg.
HR=1.26 (0.63-2.50)
p=0.51
0.2
0.0
0.0
0
12
24
36
48
60
72
84
0
Time to first event (months)
CMF 52
HEC 52
48
50
39
47
30
37
24
29
19
24
12
24
36
48
60
72
84
Time to first event (months)
CMF 64
HEC 56
62
51
53
47
41
37
31
23
23
14
p-value interaction test: 0.13
Di Leo A et al, Ann Oncol 2001
BCIRG 006
4 x AC
4 x Docetaxel
60/600 mg/m2
100 mg/m2
4 x AC
4 x Docetaxel
ACT
Her2+
(Central FISH)
N+
or high
risk N-
60/600 mg/m2
100 mg/m2
ACTH
1 Year Trastuzumab
6 x Docetaxel and Carboplatin
N=3,222
Stratified by Nodes and
Hormonal Receptor
Status
75 mg/m2
AUC 6
TCH
Slamon D., SABCS 2005
1 Year Trastuzumab
1.0
Disease Free Survival
0.8
91%
86%
86%
80%
77%
84%
80%
AC->TH
TCH
73%
0.7
AC->T
Patients
Events
0.6
1073
1074
1075
147
77
98
AC->T
AC->TH
TCH
HR (AC->TH vs AC->T) = 0.49 [0.37;0.65] P<0.0001
HR (TCH vs AC->T) = 0.61 [0.47;0.79] P=0.0002
0.5
% Disease Free
0.9
93%
0
1
2
3
Year from randomization
4
5
Slamon D., SABCS 2005
1.0
DFS CO-AMPLIFIED TOPO II BY ARM
0.8
AC->T
TCH
Patients
AC->T
AC->TH
TCH
23
13
21
Logrank P= 0.24
0.6
227
265
252
Events Treatment
0.5
% Disease Free
AC->TH
0
6
12
18
24
30
36
42
48
54
Months
Slamon D., SABCS 2005
0.8
AC->TH
TCH
0.6
Patients Events Treatment
458
472
446
92
45
54
AC->T
AC->TH
TCH
Logrank P= <0.001
AC->T
0.0
% Disease Free
1.0
DFS NON CO-AMPLIFIED TOPO II BY ARM
0
6
12
18
24
30
36
42
48
54
Months
Slamon D., SABCS 2005
HER-2 AND TOPOISOMERASE-II PROMISING POTENTIAL
PREDICTIVE MARKERS OF ANTHRACYCLINE EFFICACY
HOW TO OBTAIN LEVEL 1
EVIDENCE
LARGE PROSPECTIVE TRIALS
META-ANALYSIS
HER-2 AND TOPOISOMERASE-II AS POTENTIAL PREDICTIVE
MARKERS OF ANTHRACYCLINE EFFICACY: A META-ANALYSIS
DANISH TRIAL
FEC vs CMF
BELGIAN TRIAL
EC vs CMF
UK TRIAL
ECMF vs CMF
NCIC-CTG TRIAL
CEF vs CMF
Tampere University Laboratory
Central evaluation of HER-2/TOPO II gene amplification by FISH
Correlation with outcome of CMF or anthracycline-based therapy
with  4,500 tumor samples
TOP TRIAL OR « TRIAL OF PRINCIPLE »
Operable tumors, > 2 cm
ER-negative
Inflammatory or LABC
Incisional biopsy
ER-negative
EPIRUBICIN
100 mg/m² x 4
EPIRUBICIN 100 mg/m² x 6
dose dense / 2w + G-CSF
Snap frozen sample
SURGERY
Docetaxel x 4
Radiotherapy ± HT
HER2/Topo2
FISH analysis
(Vysis probe)
Hypothesis :  pCr in HER-2 / Topo2 co-amplified tumors
 pCr in HER-2 - / basal-like 1 tumors
Gene
expression
analysis
Genomic signature
of response to
anthracyclines
EORTC-BIG-p53 TRANSLATIONAL
RESEARCH TRIAL: STUDY DESIGN
. Loc. adv.
. Infl.
. Large
Operable
R
A
N
D
Non Taxane arm
FEC100 or Canadian FEC
Local ± TAM
therapy
Taxane arm
T-T-T-ET-ET-ET
Local ± TAM
therapy
Sample 1: standard fixation
Incisional biopsy
Sample 2: snap frozen
P53
analysis
P53 pathway
Target accrual= 1300 (872 p53-, 436 p53+)
Hypothesis: ↑ DFS at 3 y by 5% in p53- and by 20% in p53+
Postmenopausal patients (no age limits)
Non-candidates for CT
T 2 cm
Stages I, II & III
ER and/or PgR+
15 days
FRAGRANCE trial
4 - 6 months
Letrozole
Genomic signature of
de novo AI resistance
Microarray
Analysis
Microarray
Analysis
Microarray
Analysis
INTEGRATING TRANSLATIONAL RESEARCH IN
CLINICAL RESEARCH & PRACTICE
INDISPENSABLE and already ongoing
• Multidisciplinarity
• Collaboration (between specialties, between centers…)
• Bench-to-bedside-to-bench
• Biological material collection (unethical not to do it!)
• Patient selection & treatment tailored to the individual
• New technologies, new statistical methods…
• Costs ??
MINDACT & TRANSBIG FUNDING - 1
OTHER:
National Funding
Pharmaceutical Industry
Biotechnology companies (Agendia)
Other grants
EU funding €7,000,000
NATIONAL FUNDING FOR
NATIONAL PATIENTS
(indispensible)
EU funding
Other
Total expected
costs:
€35, 000,000
ACKNOWLEDGEMENTS
BIG-TRANSBIG Team
M. Piccart
Bordet Fellows
Translational Research Team