Download - Al B. Benson III, MD, FACP Professor of Medicine Associate Director for Clinical Investigations
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Al B. Benson III, MD, FACPProfessor of MedicineAssociate Director for Clinical InvestigationsRobert H. Lurie Comprehensive Cancer Centerof Northwestern University
Biomarker-Driven Design: Complexities Using AColon Cancer Model
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Prognostic Markers versus Predictive Markers
www.cancerdiagnosis.nci.nih.gov
Prognostic marker
Indicates the likelihood of outcome (tumor recurrence or patient survival) regardless of the specific treatment the patient receives
Predictive marker
Indicates the likelihood of response to a specific therapy
• Markers may have both prognostic and predictive value– This can complicate assessment
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Prognostic versus Predictive Markers
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Comparative Effectiveness
• Individual factors contribute to differences in clinical outcomes– Race or ethnic diversity– Co-morbidities– Drug-drug interactions– Tumor heterogeneity– Tumor genetics– Host genetics
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Standard therapy Responders and Patients
Not Predisposed to Toxicity
All patients with same diagnosis
Alternate therapy non-responders
and toxic responders
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Why Correlational Studies in Colorectal Cancer?
• Trials represent a “generic” population– Predictably a high % will have no benefit
• Tumors are heterogenous
• Numerous new “targeted” therapies, e.g., EGFR, VEGF
• Models: Breast cancer, GIST
• Toxicities
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Ann Thor, ECOG, 2002
From “Marker” to “Test”
• Significant and independent value
• Validated by clinical testing
• Feasibility, reproducibility and widely available with quality control (robust)
• Performance should benefit the patient
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Comparison and Applicability of Different Methodologies for Assessment of Tumor Markers
YYNNNNYApplication to routine diagnosis
YYNNNNNCellular localization evaluable
NNYYYYYMicrodissection needed
YYNNYYYUse in formalin-fixed, wax-embedded tissue
Protein
DNA / mRNA
mRNAmRNADNADNADNACellular constituent examined
ICHISHNorthern blottingRT-
PCRLOH
PCR SSCPPCR
McLeod HL and Murray GI. British J of Cancer 79(2)191-203, 1999
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Prevalence of Alterations
0
20
40
60
80
100
18qL0H 17pL0H p53overexpr.
p21waf1
expr.8pL0H
Pre
vale
nce
(%
95
%C
I)
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Current
patients
A
B
All patients receive standard treatment (A)
Clinical trials survival benefit from A
Future
patients Molecular analysis of tumor and patients
AA
BB
CC
DD
Choice of treatmentdependent upon molecular profile of tumor and onpatient genotype
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CancerOutcome
Lymph node status
Distant metastasis Surgical technique
Patient biology
Tumor biology
Access to care
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All patients with same diagnosis
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Standard therapy Responders and Patients
Not Predisposed to Toxicity
All patients with same diagnosis
Alternate therapy non-responders
and toxic responders
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Marker Analyses from Clinical Trials
• Retrospective Analyses– Majority of marker reports– Incomplete tissue collection– Small numbers of patients– Various methodologies– Can be hypothesis generating– Exception = Kras
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Marker Analyses from Clinical Trials
• Prospective Correlative Studies in Clinical Trials– Tissue collection not mandated– Statistically significant number of patients and
comparisons– Robust clinical data– Many trials now include correlatives
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Marker Analyses from Clinical Trials
• Marker-driven Treatment Strategy – Stratification– Treatment assignment
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Incidence of Colorectal Cancer U.S. 2003 N=152,000
Stage I24% Stage II
26%
Stage III29%
Stage IV22%
Eligible for Adjuvant
ChemotherapyN=83,000 (55%)
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AJCC 6th Edition:Colorectal Cancer
• IIIA (T1-2N1M0)
• IIIB (T3-4N1M0)
• IIIC (TanyN2M0)
- Stage III divided into
• IIA (T3N0M0)
• IIB (T4N0M0)
- Stage II divided into
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Estimates of 5 Year DFS (%) with Surgery Plus Adjuvant Therapy
Nodal T stage Low Grade High GradeStatus
S +AT S +AT
0 nodes T3 73 77 65 70 T4 60 66 51 57
T1-T2 62 75 53 681-4 nodes T3 49 65 38 56
T4 33 51 23 40
T1-T2 39 57 28 46> 5 nodes T3 24 43 15 32
T4 11 27 5 17
Adapted from Cill et al.. J Clin Oncol 22 :1801, 2004
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LV
OXA
RR
MOSAIC: Treatment arms
LV5FU2
FOLFOX4: LV5FU2 + Oxaliplatin 85mg/m²
Every 2 weeks, 6 months of treatment (12 cycles)
D1D1 5FU bolus5FU bolus D2D2 5FU bolus5FU bolus
LV LV5-FU infusion* 5-FU infusion*
D1D1 5FU bolus5FU bolus D2D2 5FU bolus5FU bolus
LV LV5-FU infusion* 5-FU infusion*LV LV5-FU infusion* 5-FU infusion*
D1D1 5FU bolus5FU bolus D2D2 5FU bolus5FU bolus
LV LV5-FU infusion* 5-FU infusion*
D1D1 5FU bolus5FU bolus D2D2 5FU bolus5FU bolus
LV LV5-FU infusion* 5-FU infusion*LV LV5-FU infusion* 5-FU infusion*
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Disease-free Survival: ITT
Data cut-off: June 2006Disease-free survival (months)
FOLFOX4
LV5FU2
Pro
bab
ilit
y
1.0
0.8
0.6
0.4
0.2
0
0.9
0.7
0.5
0.3
0.1
0 6 12 18 24 6030 36 42 48 54
Events
FOLFOX4 304/1123 (27.1%)
LV5FU2 360/1123 (32.1%)
HR [95% CI]: 0.80 [0.68–0.93]
5.9%
p=0.003
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Disease-free Survival: Stage II and Stage III Patients
Data cut-off: June 2006
HR [95% CI] p-value
Stage II 0.84 [0.62–1.14] 0.258
Stage III 0.78 [0.65–0.93] 0.005
FOLFOX4 stage II
LV5FU2 stage II
FOLFOX4 stage III
LV5FU2 stage III
Months
Pro
bab
ilit
y
1.0
0.8
0.6
0.4
0.2
0
0.9
0.7
0.5
0.3
0.1
0 6 12 18 24 6030 36 42 48 54 66 72
3.8%
7.5%
p=0.258
p=0.005
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Disease-free Survival: High-risk Stage II Patients
Disease-free survival (months)
FOLFOX4 n=286
LV5FU2 n=290
Pro
bab
ilit
y
1.0
0.8
0.6
0.4
0.2
0
0.9
0.7
0.5
0.3
0.1
0 6 12 18 24 6030 36 42 48 54 66 72
3-year 5-year
FOLFOX4 85.4% 82.1%
LV5FU2 80.4% 74.9%
HR [95% CI]: 0.74 [0.52–1.06]
High-risk stage II- defined as at least one of the following: T4, tumor perforation, bowel obstruction, poorly differentiated tumor, venous invasion , <10 lymph nodes examined; Data cut-off: June 2006
7.2%
Exploratory analysis
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Approximate Number of Patients Needed to Detect a Realistic Treatment Benefit*
Dukes’ B Dukes’ C
No. of No. of Survival ARR Patients Survival ARR Patients
At 3 years 85% 2.5% 8,000 65% 5.2% 3,400
At 4 years 80% 3.3% 5,800 58% 6.0% 2,800
At 5 years 75% 4.0% 4,700 50% 6.6% 2,400
Abbreviation: ARR = absolute risk reduction•For 90% power of detecting the treatment benefit using two-tailed significance tests at the 5% level, assuming the true relative risk reduction is 18% for both Dukes’ B and Dukes’ C.
Buyse, Piedbois, 2001
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Prognostic Factors in Colorectal CancerCOLLEGE OF AMERICAN PATHOLOGISTS CONSENSUS
Category 1 – evidence from multiple statistically-robust published trials and used in pt. management
Category IIA – extensively studied and sufficient for path reports, but needs validation
Category IIB – promising
Category III – insufficient study
Category IV – well-studied and no prognostic significance
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Prognostic Factors in Colorectal CancerCOLLEGE OF AMERICAN PATHOLOGISTS CONSENSUS
Category I path-local extent of tumor = pT path-nodes = pN blood or lymphatic invasion post-op residual tumor = R (e.g., + margin) post-op CEA
Category IIA tumor grade radial margin status residual tumor s/p neoadjuvant tx
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Intergroup Adjuvant Colon CancerINT 0035 (E 2284)
Observation
Levamisole
5-FU / levamisole
S
U
R
G
E
R
Y
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Intergroup Adjuvant Colon CancerINT 0089 (E 2288)
5-FU / leucovorin (Mayo)
5-FU / leucovorin (Roswell)
5-FU / levamisole
5-FU / levamisole / leucovorin
S
U
R
G
E
R
Y
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Analysis of Molecular Markers in Patients with Stage III Colon Cancer
Watanbe T, et al. N Engl J Med 344(16);1196-1206, 2001
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Analysis of Molecular Markers in Patients with Stage III Colon Cancer
Watanbe T, et al. N Engl J Med 344(16);1196-1206, 2001
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E5202 Trial Schema
Low-Risk PatientsMSS or MSI-L with
retention of 18q allelesMSI-H
Arm A:mFOLFOX6q2w × 12
Arm B:mFOLFOX6 + bevacizumab* q2w × 12
Arm C:Observation only
High-Risk PatientsMSS/18q LOH orMSI-L/18q LOH
areRANDOMIZED
MSI-L = low-level microsatellite instabilityMSI-H = high-level microsatellite instability*Bevacizumab continued for an additional 6 months
Stratify:Disease stage
(IIA or IIB)Microsatellite stability
(stable vs MSI)18q LOH
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E5202 Trial Design: Sample Submission
• Tumor and normal tissue sample required for enrollment– Samples must be formalin-fixed paraffin blocks or
unstained histologic sections – Submission time points are crucial
• Received no later than 50 days following surgery• Received within 5 days of trial registration
– Surgeons at participating institutions should be aware of timeline in order to introduce patients to trial
• Critical given timeline of tissue collection
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E5202 Correlative Studies
• Correlate tumor biologic characteristics with survival of patients treated with test regimens– Microsatellite stability
– 18q LOH
• All tissue from study to be archived by ECOG coordinating center and assessed for biologic characteristics by MD Anderson laboratories
• Tissue from studies will be archived for future assessment
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Deficient Mismatch Repair as a Predictive Marker for Lack of Benefit from 5-FU based Chemotherapy in
Adjuvant Colon Cancer
DJ Sargent, S Marsoni, SN Thibodeau, R Labianca, SR Hamilton, V Torri, G Monges, C
Ribic, A Grothey, S Gallinger
ASCO 2008
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David Kerr1, Richard Gray2, Philip Quirke3, Drew Watson4, Greg Yothers5, Ian Lavery6, Mark Lee4, Michael O'Connell5, Steven Shak4, Norman Wolmark5 and the Genomic Health
& QUASAR Colon Teams
A quantitative multi-gene RT-PCR assay for prediction of recurrence in stage II colon cancer:
Selection of the genes in 4 large studies and results of the independent, prospectively-designed
QUASAR validation study
1. University of Oxford, Oxford, UK; 2. Birmingham Clinical Trials Unit, Birmingham, UK; 3. Leeds Institute of Molecular Medicine, Leeds, UK; 4. Genomic Health, Inc., Redwood City, CA; 5. National Surgical Adjuvant Breast and Bowel Project, Pittsburgh, PA; 6. Cleveland Clinic Foundation, Cleveland, OH
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The Need for Individualized Therapy in Stage II Colon Cancer
• The challenge: Which stage II colon cancer patients should be treated with adjuvant chemotherapy?– 75-80% cured with surgery alone, but no method to identify them– Absolute benefit of chemotherapy is small and no consensus in
guidelines on who to treat– Chemotherapy has significant toxicity
• Today, decision to give chemotherapy subjectively based on:– Clinical/pathologic markers of risk which are inadequate
• Not informative for majority of patients
– Patient age, co-morbidities, preferences
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Colon Cancer Technical Feasibility
Development StudiesSurgery Alone
NSABP C-01/C-02 (n=270)
CCF (n = 765)
Selection of Final Gene List & Algorithm
Development Studies Surgery + 5FU/LV
NSABP C-04 (n=308)
NSABP C-06 (n=508)
Clinical Validation Study – Stage II Colon Cancer
QUASAR (n=1,436)
Test Prognosis and Treatment Benefit
Development and Validation of a Multi-Gene RT-PCR Colon Cancer Assay
Validation of Analytical Methods
• NSABP and CCF Collaborations - 761 genes studied in 1,851 patients to select genes which predict recurrence and/or differential 5FU/LV benefit
• Clinical Validation of final assay in a large, prospectively-designed independent study
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p=0.004
0%
5%
10%
15%
20%
25%
30%
35%
0 10 20 30 40 50 60 70
Recurrence Score
Ris
k o
f re
cu
rre
nc
e a
t 3
ye
ars
QUASAR RESULTS: Colon Cancer Recurrence Score Predicts Recurrence Following Surgery
STROMALFAP
INHBABGN
CELL CYCLEKi-67
c-MYCMYBL2
REFERENCEATP5EGPX1PGK1UBB
VDAC2
GADD45B
RECURRENCE SCORECalculated from Tumor
Gene Expression
Prospectively-Defined Primary Analysis in Stage II Colon Cancer (n=711)
Group Risk (by Kaplan-Meier) 12% 18% 22%
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QUASAR RESULTS: Recurrence Score, T Stage, and MMR Deficiency are Key Independent Predictors
of Recurrence in Stage II Colon Cancer
Multivariate Analysis
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Summary and Conclusions• The prospectively-defined continuous Recurrence Score has been
validated as a predictor of recurrence in stage II colon cancer patients following surgery, and provides independent value beyond standard measures of risk
• A separate score, based on a distinct set of 6 genes, was not validated for prediction of differential 5FU/LV benefit
• The continuous RS provides individualized assessment of recurrence risk and will have the greatest clinical utility when used in conjunction with T stage and Mismatch Repair (MMR/MSI), particularly for the majority of patients for whom those markers are uninformative (~70% of pts)
• This is the first demonstration that a prospectively defined gene expression assay can independently predict recurrence in colon cancer
Implications for Clinical Practice
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EGF-induced Signal Transduction and Tumorigenesis
• Epidermal growth factor receptor (EGFR)
– A large tyrosine kinase growth factor receptor
• Natural ligands
– TGF-, EGF
• Potential to block multiple steps in the signal transduction process– Extracellular surface– Intracellular targets
XX
Invasion/metastasis
ProliferationSurvival/anti-apoptosis
Angiogenesis
MAPK
MEK
Gene transcriptionCell-cycle progression
PI3-K
RAS RAF
SOS
GRB2
PTEN AKTSTAT
pY
K KpY
M
G1S
G2
EGF
pY
p27
XXXXXX
EGFR Anti-EGFR(+)XX
Perez-Soler R. Oncologist. 2004;9:58-67.
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Potential Biomarkers:Methods of Testing
• EGFR protein expression
• EGFR gene copy number
• K-ras gene mutations
• EGFR ligands and phosphorylation
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Copyright © American Society of Clinical Oncology
Amado, R. G. et al. J Clin Oncol; 26:1626-1634 2008
Fig 1. CONSORT diagram
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Copyright © American Society of Clinical Oncology
Amado, R. G. et al. J Clin Oncol; 26:1626-1634 2008
Fig 2. Progression-free survival by treatment within KRAS groups
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Copyright © American Society of Clinical Oncology
Amado, R. G. et al. J Clin Oncol; 26:1626-1634 2008
Fig 3. Subset analyses of progression-free survival in the KRAS wild-type group
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Copyright © American Society of Clinical Oncology
Amado, R. G. et al. J Clin Oncol; 26:1626-1634 2008
Fig 4. Waterfall plots showing maximum percent decrease in target lesions (blinded central radiology)
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Copyright © American Society of Clinical Oncology
Amado, R. G. et al. J Clin Oncol; 26:1626-1634 2008
Fig 5. Kaplan-Meier curves for overall survival by treatment and KRAS status
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Copyright © American Society of Clinical Oncology
Amado, R. G. et al. J Clin Oncol; 26:1626-1634 2008
Fig A1. (A) Progression-free survival and (B) overall survival by KRAS status among patients receiving panitumumab after progression on best supportive care alone
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