Department 1

Biomarkers for personalizedanti-cancer therapyRianne Fijten

Department 2

Introduction

Drug 3

Drug 2

Drug 1

PersonalizedTreatment

Standard Treatment

Cancer Treatment

Genetic Profiling

Drug sensitivity

Choose best drug

Trial and error

Cured

Not cured

Higher chance

on being cured

By predefined biomarkers for drug sensitivity

Department 3

Research Question

Can biomarkers be defined for personalized anti-cancer therapy with use of predictive modeling of drug sensitivity?

Department 4

Project

NCI60 drug sensitivity

panel

Available data types

• Panel of tumor derived cell lines corresponding to diverse tissue types, which has been subject to extensive molecular phenotypic and pharmacological characterization

• Data:

– baseline (untreated) metabolic and transcriptional profiles from 58 cell lines

– Growth inhibition data from an array of 118 drugs

1. Cavill et al. 2009 PloS Comp

Department 5

Project

NCI60 drug sensitivity

panel

Available data types

Patient tumor profiling data • Chemotherapy responses of individual cancer patients

1. Cavill et al. 2009 PloS Comp

1

Department 6

Project

NCI60 drug sensitivity

panel

Available data types

Defining biomarkers

for drug sensitivity

Methodology

1. Cavill et al. 2009 PloS Comp

1

• Drug-sensitivity associated pathways

• Biomarkers: Most important genes or metabolites in those pathways

Department 7

Project

NCI60 drug sensitivity

panel

Available data types

Development of predictive

models

Defining biomarkers

for drug sensitivity

Methodology

1. Cavill et al. 2009 PloS Comp

1

Department 8

Project

NCI60 drug sensitivity

panel

Available data types

Patient tumor profiling data

Development of predictive

models

Defining biomarkers

for drug sensitivity

Testing predictive

models

Methodology

1. Cavill et al. 2009 PloS Comp

1

1

Department 9

Project

NCI60 drug sensitivity

panel

Available data types

Patient tumor profiling data

Development of predictive

models

Defining biomarkers

for drug sensitivity

Testing predictive

models

Possibly clinical use

Aspired outcome

Methodology

Happy patients

1. Cavill et al. 2009 PloS Comp

1

1

Department 10

See you in London!

• Are there questions?