background

Prognostic and predictive blood-based biomarkers in patients with

advanced pancreatic cancer: Results from CALGB 80303

A.B. Nixon1, H. Pang1,2, M. Starr1, D. Hollis1,2, P.N. Friedman3, M.M. Bertagnolli4, H.L. Kindler3, R.M. Goldberg5, A.P. Venook6, H.I. Hurwitz1

1Duke University Medical Center; 2CALGB Statistical Office; 3University of Chicago Cancer Research Center; 4Brigham and Women's Hospital, Boston; 5University of

North Carolina, Chapel Hill; 6University of California, San Francisco

Background• Pancreatic cancer is the 4th leading cause of cancer-related death in the United

States1.

• Bevacizumab (Genentech/Roche) is a humanized monoclonal antibody against vascular endothelial growth factor A (VEGF A) and has been shown to provide clinical benefit in a number of tumor types including colon, glioblastoma, renal, and non-small cell lung cancer2.

• CALGB 80303 was a randomized Phase III Trial of gemcitabine plus bevacizumab versus gemcitabine plus placebo in patients with advanced pancreatic cancer.

• In this study, no clinical benefit was observed from the addition of bevacizumab3.

• Blood-based biomarker profiling to identify potential prognostic/predictive factors has been supported by several recent studies4-7.

1. Jemal A, et al. CA Cancer J Clin 2010; 60: 277-300.2. Bevacizumab (Avastin) resource center: http://www.avastin.com3. Kindler, HL, et al. JCO. 2010; 28:3617-22.4. Nixon, AB, et al. JCO. 2010; 28: (suppl; abstr e21009). 5. Miles, DW, et al. San Antonio Breast Cancer Symposium: December 8-12, 2010.6. Hanrahan EO, et al. JCO. 2010; 28: 193-201 7. Tran, HT, et al. JCO. 2011; 29 (suppl 7; abstr 334).

Objectives• To correlate baseline values of multiple plasma-based

angiogenic factors with the primary clinical outcome (Overall Survival) of CALGB 80303

– Identify univariate and multivariate prognostic markers• Predict outcome independent of treatment group

– Identify univariate and multivariate predictive markers• Predict outcome that is dependent upon treatment

– Identify patterns of correlation among analytes

Methods I• Clinical Study

– Patients with advanced or metastatic pancreatic adenocarcinoma were randomized to gemcitabine (1000 mg/m2) ± bevacizumab (10mg/kg)

– Treatment was continued until progression, adverse event, or withdraw of consent

– Median overall survival• Gemcitabine + placebo - 5.9 months (95% CI: 5.1,6.9)• Gemcitabine + bevacizumab - 5.8 months (95% CI: 4.9,6.6)

• Sample Collection and Handling– EDTA plasma, citrated plasma, serum, urine were processed at individual sites.– Samples were frozen and shipped for centralized storage at the CALGB

Pathology Coordinating Office (PCO).

Methods II• Laboratory Methods

– Samples were shipped from the PCO, thawed one time, precipitate removed, aliquoted, and re-frozen until assayed.

– Every sample tested was exposed to one freeze/thaw cycle.– Laboratory personnel were blinded throughout study.– Assays were performed in triplicate.– Samples were evaluated using a multiplex ELISA platform (SearchLight system,

Aushon Biosciences).

• Statistical Methods– Univariate Cox proportional hazards regression models were used for both

prognostic and predictive biomarker identification.– Multivariate Cox models were developed with leave-one-out cross validation

(LOOCV).– Bivariate models were used to identify two-analyte predictive models. – Spearman correlations were calculated across all pairs of analytes.

SearchLight Array Protocol

B B

B B

SA-HRP

SA-HRP

SA-HRPB B

B B

SA-HRP

SA-HRP

SA-HRP

SA-HRPB B

B B

SA-HRP

SA-HRP

SA-HRP

SA-HRPB B

B B

SA-HRP

Add Sample &Stds Add Detection Ab’s Add SA-HRP Reagent Add Substrate Image Plate

Spotted Capture Ab’s

The brightness of the spotted feature, captured by the cooled CCD camera, is indicative of the expression of the protein.The feature’s signal is analyzed using the PROarray Analyst Software to determine the amount of protein in each unknown sample.

Specific proteins are distinguished by their unique spotted position within the well.

-Figure adapted with permission from Aushon Biosciences (Billerica, MA)

Panel of Angiome AnalytesSoluble Angiogenic

FactorsMatrix-Derived

Angiogenic Factors

Markers of Coagulation

Markers of Vascular Activation and Inflammation

Ang-2 PEDF OPN CRP Gro-bFGF PlGF TGF1 PAI-1 Active ICAM-1HGF VEGF-A TGF2 PAI-1 Total IL-6IGFBP-1 VEGF-C TSP-2 IL-8IGFBP-3 VEGF-D MCP-1PDGF-AA sVEGFR-1 P-selectinPDGF-BB sVEGFR-2 SDF-1

VCAM-1

Standard ELISAs were run for IGF-1 and TGFRIII

Assay Performance

Analyte % Below LOD Analyte % Below

LODIGF-1 0.0 P-Selectin 0.1TGFRIII 0.0 VCAM-1 0.1Gro- 0.0 CRP 0.1IL-6 0.0 VEGF-D 0.2HGF 0.0 PAI-1 act 0.2MCP-1 0.0 PAI-1 tot 0.3OPN 0.0 SDF-1 0.4sVEGFR-2 0.0 Ang-2 0.4

TSP-2 0.0 sVEGFR-1 0.5

IGFBP-1 0.0 VEGF-A 2.4IGFBP-3 0.0 PDGF-BB 3.0ICAM-1 0.0 IL-8 3.1PEDF 0.0 VEGF-C 8.3TGF1 0.0 PlGF 12.2TGF2 0.0 bFGF 23.4PDGF-AA 0.1

Analyte % CV Analyte % CVTGFRIII 2.6 ICAM-1 14.4IGF-1 3.7 IGFBP-1 14.5P-Selectin 7.5 PEDF 14.7IGFBP-3 7.9 ANG-2 14.7HGF 8.1 sVEGFR-2 14.9TSP-2 8.8 TGF2 15.2SDF-1 9.4 PDGF-AA 17.7VCAM-1 10.0 VEGF-A 17.9PAI-1tot 10.1 VEGF-C 19.0MCP-1 10.4 bFGF 20.1VEGF-D 10.7 PlGF 22.1IL-6 10.7 OPN 23.0PAI-1 act 11.3 GRO- 24.3PDGF-BB 12.2 IL-8 24.7TGF1 12.5 CRP 27.3sVEGFR-1 13.3

Limits of Detection Coefficients of Variation

Patient CharacteristicsOverall (whole

population) Overall (EDTA population)

Gem + Placebo

Gem +Bev

No. % No. % No. % No. % No. of patients 602 328 159 169 Age, years

Median 64.1 64.0 65.5 63.1 Range 26.3 - 88.7 35.8 - 84.2 35.8 - 83.7 35.9 - 84.2

Gender male 55 55 48 62 Race white 88 89 91 88 ECOG PS

0 37 40 39 40 1 52 50 53 48 2 11 10 8 12

Extent of disease Locally

adv. 12 12 12 12

Metastatic 88 88 88 88 

Median OS (range) 5.9 (5.3 - 6.5) 6.1 (5.5 - 6.9) 6.3 (5.1 - 8.0) 5.9 (5.0 - 7.0)

Median PFS (range) 3.5 (3.0 - 3.8) 3.8 (3.3 - 4.0) 3.5 (2.4 - 4.2) 3.8 (3.5 - 4.6)

Correlation of Analytes at BaselineCluster Dendrogram

Correlation of Analytes at BaselineCluster Dendrogram

Correlation of Analytes at BaselineCluster Dendrogram

Prognostic Marker Analysis

Univariate Prognostic Markers Gemcitabine + Placebo (OS)

< median > median < med vs> med

p-value# Median Survival 95% CI Median

Survival 95% CI Hazard ratio 95% CI

IGFBP-1* 1.2e-10 9.2 (7.3,9.9) 4.3 (3.1,5.7) 1.7 (1.2,2.4)ICAM-1* 7.8e-08 8.4 (6.1,9.7) 4.8 (3.5,6.8) 1.4 (1.01,1.90)Ang2* 1.5e-07 9.6 (7.7,10.4) 4.6 (3.3,5.8) 2.4 (1.7,3.3)CRP* 6.9e-07 9.7 (8.1,10.6) 3.8 (2.9,4.8) 2.3 (1.6,3.1)IL-8 1.3e-05 8.7 (6.1,9.7) 5.0 (3.5,6.9) 1.3 (0.98,1.86)TSP-2* 7.0e-05 9.0 (6.8,9.7) 4.6 (3.3,5.6) 1.6 (1.1,2.1)VCAM-1* 2.1e-04 9.0 (6.7,9.7) 4.8 (3.6,5.9) 1.6 (1.2,2.3)PAI1-act 4.3e-04 8.1 (6.7,9.2) 4.8 (3.4,5.9) 1.3 (0.94,1.77)IGF-1* 0.0012 4.2 (3.3,5.7) 8.8 (6.8,9.7) 0.70 (0.51,0.96)

* significant in both gemcitabine + placebo & gemcitabine + bevacizumab cohorts# from Cox regression using continuous analyte values

Univariate Prognostic Markers Gemcitabine + Placebo (OS)

< median > median < med vs> med

p-value# Median Survival 95% CI Median

Survival 95% CI Hazard ratio 95% CI

IGFBP-1* 1.2e-10 9.2 (7.3,9.9) 4.3 (3.1,5.7) 1.7 (1.2,2.4)ICAM-1* 7.8e-08 8.4 (6.1,9.7) 4.8 (3.5,6.8) 1.4 (1.01,1.90)Ang2* 1.5e-07 9.6 (7.7,10.4) 4.6 (3.3,5.8) 2.4 (1.7,3.3)CRP* 6.9e-07 9.7 (8.1,10.6) 3.8 (2.9,4.8) 2.3 (1.6,3.1)IL-8 1.3e-05 8.7 (6.1,9.7) 5.0 (3.5,6.9) 1.3 (0.98,1.86)TSP-2* 7.0e-05 9.0 (6.8,9.7) 4.6 (3.3,5.6) 1.6 (1.1,2.1)VCAM-1* 2.1e-04 9.0 (6.7,9.7) 4.8 (3.6,5.9) 1.6 (1.2,2.3)PAI1-act 4.3e-04 8.1 (6.7,9.2) 4.8 (3.4,5.9) 1.3 (0.94,1.77)IGF-1* 0.0012 4.2 (3.3,5.7) 8.8 (6.8,9.7) 0.70 (0.51,0.96)

* significant in both gemcitabine + placebo & gemcitabine + bevacizumab cohorts# from Cox regression using continuous analyte values

Univariate Prognostic Markers for Gemcitabine + Bevacizumab (OS)

< median > median < med vs> med

p-value# Median Survival 95% CI Median

Survival 95% CI Hazard ratio 95% CI

TSP-2* 2.6e-08 6.1 (5.2,7.4) 5.7 (4.1,7.1) 1.3 (0.9,1.7)

CRP* 2.7e-08 7.4 (5.9,9.5) 4.6 (3.5,5.8) 1.9 (1.4,2.6)

IL-6 1.4e-07 8.4 (7.0,9.7) 3.8 (3.1,4.8) 2.3 (1.7,3.2)

IGFBP-1* 8.3e-07 8.0 (6.5,9.7) 4.1 (3.2,5.3) 2.2 (1.6,3.0)

Ang2* 1.7e-06 7.0 (5.5,15.0) 4.8 (3.8,6.5) 1.4 (1.1,2.0)

ICAM-1* 2.7e-04 6.8 (5.5,8.3) 5.0 (4.0,6.8) 1.5 (1.1,2.0)

VCAM-1* 0.0012 7.1 (5.5,8.1) 5.3 (4.1,6.5) 1.5 (1.1,2.0)

IGF-1* 0.0019 4.7 (3.7,5.8) 7.1 (5.8,8.3) 0.68 (0.50,0.92)

* significant in both gemcitabine + placebo & gemcitabine + bevacizumab cohorts# from Cox regression using continuous analyte values

Univariate Prognostic Markers for Gemcitabine + Bevacizumab (OS)

< median > median < med vs> med

p-value# Median Survival 95% CI Median

Survival 95% CI Hazard ratio 95% CI

TSP-2* 2.6e-08 6.1 (5.2,7.4) 5.7 (4.1,7.1) 1.3 (0.9,1.7)

CRP* 2.7e-08 7.4 (5.9,9.5) 4.6 (3.5,5.8) 1.9 (1.4,2.6)

IL-6 1.4e-07 8.4 (7.0,9.7) 3.8 (3.1,4.8) 2.3 (1.7,3.2)

IGFBP-1* 8.3e-07 8.0 (6.5,9.7) 4.1 (3.2,5.3) 2.2 (1.6,3.0)

Ang2* 1.7e-06 7.0 (5.5,15.0) 4.8 (3.8,6.5) 1.4 (1.1,2.0)

ICAM-1* 2.7e-04 6.8 (5.5,8.3) 5.0 (4.0,6.8) 1.5 (1.1,2.0)

VCAM-1* 0.0012 7.1 (5.5,8.1) 5.3 (4.1,6.5) 1.5 (1.1,2.0)

IGF-1* 0.0019 4.7 (3.7,5.8) 7.1 (5.8,8.3) 0.68 (0.50,0.92)

* significant in both gemcitabine + placebo & gemcitabine + bevacizumab cohorts# from Cox regression using continuous analyte values

Multivariate Prognostic Markers Gem + Placebo & Gem + Bevacizumab

Models p-value HR 95% CI N (cens) Median Survival 95% CI N (cens) Median

Survival 95% CI

GP 4.5e-5 2.0 (1.4,2.7) 79 (0) 3.3 (2.6,4.6) 79 (1) 7.3 (5.8,8.6)

GB 2.9e-6 2.1 (1.5,2.8) 85 (1) 3.6 (2.6,4.7) 83 (0) 7.2 (5.8,9.7)

Model for GP: IGFBP-1, CRP, PDGF-AA, PAI-1 tot, PEDFModel for GB: IGFBP-1, IL-6, PDGF-AA, PDGF-BB, TSP-2

Multivariate prognostic models for OS were developed using a leave-one-out cross validated Cox Proportional Hazard model.

GP: gemcitabine + placeboGB: gemcitabine + bevacizumabN: eventscens: number censoredSurvival expressed in months

Multivariate Prognostic Models

Gemcitabine + BevacizumabGemcitabine + Placebo

(IGFBP-1, CRP, PDGF-AA, PAI-1 tot, PEDF) (IGFBP-1, IL-6, PDGF-AA, PDGF-BB, TSP-2)Months

Sur

viva

l Pro

babi

lity

0 10 20 30 400.

00.

20.

40.

60.

81.

0

Kaplan-Meier Plot for GB

Months

Sur

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0 10 20 30 40

0.0

0.2

0.4

0.6

0.8

1.0

Kaplan-Meier Plot for GP

Low RiskHigh Risk

Median OS(months)

7.33.3

HR

2.0

Months

Sur

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0 10 20 30 40

0.0

0.2

0.4

0.6

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Kaplan-Meier Plot for OPN <median and SDF-1B >median

95% CI

(5.8,8.6)(2.6,4.6)

Low RiskHigh Risk

Median OS(months)

7.23.6

HR

2.1

Months

Sur

viva

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0 10 20 30 40

0.0

0.2

0.4

0.6

0.8

1.0

Kaplan-Meier Plot for OPN <median and SDF-1B >median

95% CI

(5.8,9.7)(2.6,4.7)

Predictive Marker Analysis

Univariate Predictive Markers

Gem + Placebo Gem + Bev

Analyte p-value# cutoff HR 95% CI Median Survival 95% CI Median

Survival 95% CI

Ang-2 0.035 <median 1.4 (1.02,1.92) 9.6 (8.1,10.6) 7.0 (5.7,8.7)

SDF-1 0.027 <median 1.4 (1.04,1.94) 8.4 (6.3,9.7) 5.4 (4.8,7.4)

VEGF-D0.035 > Q1 1.3 (1.04,1.74) 6.9 (5.7,9.0) 5.8 (4.8,7.1)

0.033 < Q1 0.6 (0.39,0.96) 5.4 (3.6,9.4) 6.5 (5.0,11.0)

#p-values are uncorrected and represent log-rank tests comparing the two treatment arms

Univariate Predictive Markers

<median>median

<median>median

<Q1>Q1

Ang-2

SDF-1

VEGF-D

Favors PlaceboFavors BevAng2 <med >med

SDF-1b <med >med

VEGF-D <Q1 >Q1

0.4 0.6 0.8 1 1.2 1.4 1.6 1.81.0 1.2 1.4 1.6 1.80.4 0.6 0.8Hazard Ratio

Months

Sur

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l Pro

babi

lity

0 10 20 30 40

0.0

0.2

0.4

0.6

0.8

1.0

Kaplan-Meier Plot for OPN <median and SDF-1B >median

Months

Sur

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babi

lity

0 10 20 30 40

0.0

0.2

0.4

0.6

0.8

1.0

Kaplan-Meier Plot for ANG-2 <median and SDF-1B <median

Gem+Placebo Gem+Bev

Analyte p-value# HR 95% CI N Median Survival 95% CI N Median

Survival 95% CI

SDF-1OPN

>med<med 0.0073 0.55 (0.35,0.85) 39 5.1 (3.2,8.1) 43 9.0 (5.8,13.4)

SDF-1Ang-2

<med<med 0.0005 2.2 (1.4,3.4) 46 10.4 (8.6,15.0) 42 6.7 (4.9,7.9)

SDF-1<medAng-2 <med

SDF-1>medOPN <med

Bivariate Predictive Markers

Gem + PlaceboGem + Bev

#p-values are uncorrected and represent log-rank tests comparing the two treatment arms

Gem + PlaceboGem + Bev

Conclusions• Angiome analyses were technically robust

• Multiple factors with strong prognostic importance were identified– Factors were similar in the gemcitabine + placebo &gemcitabine + bev group

• Several markers predicted for potential benefit or lack of benefit from bevacizumab

• Results need confirmation before being applied to clinical practice

• Inclusion of multi-analyte angiome analyses in other trials is warranted

Acknowledgments• We thank all the patients, and their families and caregivers, who

participated in the parent protocol and in the correlative science sub-study

• We thank the investigators and their study teams

• We thank the members of the Pathology Coordinating Office at CALGB

• We thank all the members of the Duke/CALGB Molecular Reference Lab and the team at Aushon Biosciences for assay development

• This study was sponsored by a grant from the CALGB foundation