Al B. Benson III, MD, FACP Professor of Medicine Associate Director for Clinical Investigations

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

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

Prognostic versus Predictive Markers

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

Standard therapy Responders and Patients

Not Predisposed to Toxicity

All patients with same diagnosis

Alternate therapy non-responders

and toxic responders

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

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

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

Prevalence of Alterations

0

20

40

60

80

100

18qL0H 17pL0H p53overexpr.

p21waf1

expr.8pL0H

Pre

vale

nce

(%

95

%C

I)

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

CancerOutcome

Lymph node status

Distant metastasis Surgical technique

Patient biology

Tumor biology

Access to care

Standard therapy Responders and Patients

Not Predisposed to Toxicity


Alternate therapy non-responders

and toxic responders

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


• 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


• Marker-driven Treatment Strategy – Stratification– Treatment assignment

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%)

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

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

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*


LV LV5-FU infusion* 5-FU infusion*LV LV5-FU infusion* 5-FU infusion*


LV LV5-FU infusion* 5-FU infusion*


LV LV5-FU infusion* 5-FU infusion*LV LV5-FU infusion* 5-FU infusion*

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

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

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

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

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

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

Intergroup Adjuvant Colon CancerINT 0035 (E 2284)

Observation

Levamisole

5-FU / levamisole

S

U

R

G

E

R

Y

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

Analysis of Molecular Markers in Patients with Stage III Colon Cancer

Watanbe T, et al. N Engl J Med 344(16);1196-1206, 2001

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

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

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

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

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

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

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

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%

QUASAR RESULTS: Recurrence Score, T Stage, and MMR Deficiency are Key Independent Predictors

of Recurrence in Stage II Colon Cancer

Multivariate Analysis

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

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.

Potential Biomarkers:Methods of Testing

• EGFR protein expression

• EGFR gene copy number

• K-ras gene mutations

• EGFR ligands and phosphorylation

Copyright © American Society of Clinical Oncology

Amado, R. G. et al. J Clin Oncol; 26:1626-1634 2008

Fig 1. CONSORT diagram



Fig 2. Progression-free survival by treatment within KRAS groups



Fig 3. Subset analyses of progression-free survival in the KRAS wild-type group



Fig 4. Waterfall plots showing maximum percent decrease in target lesions (blinded central radiology)



Fig 5. Kaplan-Meier curves for overall survival by treatment and KRAS status



Fig A1. (A) Progression-free survival and (B) overall survival by KRAS status among patients receiving panitumumab after progression on best supportive care alone

Al B. Benson III, MD, FACP Professor of Medicine Associate Director for Clinical Investigations

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