Towards Next Generation Life Science

a case study

Prof. Alain van Gool

Netherlands Organisation for Applied Scientific Research (TNO)

Radboud University Nijmegen Medical Centre

Radboud University Nijmegen

DTL Next Generation Life Sciences Workshop

Utrecht, 23 October 2013

Next Generation Life Science through Open Innovation Networks

2

(Source: Model TNO’s Holst Center) Old New

Features of an Open Innovation Network

3

Pharma cies

Biobanks

Analytical

laboratories

Diagnostic cies

D

C

B A

Others

Access to a network of relevant scientists, reagents and technologies

Access to relevant markets and secondary networks

Flexible use of expertise and capabilities in network under standardised agreements

Funding for joined and bilateral projects

Accelerated translation of knowledge to innovation

C1

C2

C3

C..

Technology 1

Technology 2

Technology 3

Technology ..

Eg for biomarker R&D:

Outline

4

Backgrounds

TNO

Radboudumc

Biomarker Development Center

Next Generation Life Science

Case study

Identification of microRNA targets for miRNA-based cancer therapeutics

Radboudumc Urology

InteRNA

Radboud Proteomics Centre

TNO System Biology

TNO = Netherlands Organisation for Applied Scientific Research Mission = to drive ideas to reach their full market value.

We partner with:

Governmental & regulatory organisations

Universities

Pharma, chemical and food companies

International consortia

Knowledge

development

Knowledge

application

Knowledge

exploitation

Develop

fundamental

knowledge

With

universities

With

partners

With

customers

Embedded in the

market

TNO TNO Triskelion

5 Biomarker Europe Summit 2013, GTC BIO, Berlin

10 October 2013

Alain van Gool

TNO

Facts &Figures: Founded in 1932 Member of EARTO Non-for-profit research institute ~3500 employees

19 sites in Netherlands + 18 sites/countries globally Funding: • Government (NL) • Contract research (world) • Public-private partnerships (world) 7 main themes

www.tno.nl

6 Biomarker Europe Summit 2013, GTC BIO, Berlin

10 October 2013

Alain van Gool

TNO in European public-private partnerships

Healthy Living

Defence, Safety & Security

Transport & Mobility

Information Society

Industrial Innovation

Energy

Built Environment

Participation in EU projects: (Jan 2013)

260 projects (3100 partners)

Roles of TNO:

Technical expertise

Focus on applications

PPP management skills

(in 10% role as coordinator)

32% success rate

(average FP7 is 21%)

Biomarker Europe Summit 2013, GTC BIO, Berlin

10 October 2013

Alain van Gool

Year 1

Applying lessons learned across fields

Biomarker Europe Summit 2013, GTC BIO, Berlin

10 October 2013

Alain van Gool

e.g. System Biology @TNO

Year 2

Year 3

Radboudumc • Mission: “To have a significant impact on healthcare” • Strategic focus on Personalized Healthcare • Core activities:

• Patient care • Research • Education

• 11.000 colleagues • 50 departments • 3.000 students • 1.000 beds (ambition to close 500 by improving

healthcare) • First academic centre outside US to fully implement EPIC

Radboudumc Technology Infrastructure Preclinical Imaging Centre (PRIME) DTL Microscopic Imaging Centre (MIC) DTL Centre for Molecular and Biomolecular Informatics (CMBI) DTL Genetics DTL Centre for Proteomics, Glycomics and Metabolomics DTL Centraal Dierenlaboratorium (CDL) Translationeel Malaria Onderzoek Translational research and cellular therapy Flow cytometry Clinical Research Centre Nijmegen (CRCN) Radboud Biobank

Translational Neuroscience Unit (TNU) Medical Innovation and Technology expert Centre (MITeC)

Centre for Proteomics, Glycomics & Metabolomics

Radboud

Proteomics

Center

Radboud

Metabolomics

Group

Radboud

Glycomics

Facility

Research Biomarkers Diagnostics

Mass spectrometry – NMR based, 16 dedicated fte, part of diagnostic laboratory (Department Laboratory Medicine), close interaction with Radboudumc scientists and external partners

Biomarker Development Center

• A focus on application of innovation, not on biomarker discovery or new technologies

• The innovation is a clinically validated and applicable biomarker test method

• Bring together available state-of-the art biomarker expertise in an industrial process flow

• Sponsors and end-users define objectives (a.o. pharma, diagnostics, patients)

• Shared biomarker R&D in Open Innovation Network based on Public-Private-Partnership

Shared knowledge, technologies

and objectives

Accelerate biomarker development

Focus

Emerging

Discovery Clinical validation

and confirmation

Diagnostic

application

Number of

biomarkers

Experimental

Discovery

Assay kit

development

Assay

development Early Late

Academia

(discovery)

Industry

(development)

Shared R&D in biomarkers:

1. Assay development of (diagnostic) biomarkers

2. Clinical biomarker validation (quantification/confirmation, multicenter)

Leading to standardised clinical applications

Biomarker Development Center (Netherlands)

STW perspectief application

Biomarker Development Center

Public-private partnership 4 years

Project budget 4.3M Eur

Close interactions with:

- Clinicians (biomarker application)

- Industry (+ 0.94MEur cash + 1.24MEur kind)

- Patient stakeholder associations

Outline

15

Backgrounds

TNO

Radboudumc

Biomarker Development Center

Next Generation Life Science

Case study

Identification of microRNA targets for miRNA-based cancer therapeutics

Radboudumc Urology

InteRNA

Radboud Proteomics Centre

TNO System Biology

Next Generation Life Sciences - Case study

16

Department Urology

Dr. Gerard Verhaegh

Prof Jack Schalken Dr. Iman Schultz

Dr. Paula van Noort

Joined development of miRNA-based cancer therapeutics in prostate cancer

Tumor metastasis and EMT

EMT characterized by :

- altered cell morphology

- breakdown of cell junctions

- increased motility / invasion

Tumor metastasis

involves Epithelial to

Mesenchymal

Transition (EMT)

Mechanism of Action

Target genes

Identification

of EMT

targeting

miRNAs

Inhibition of

Invasion &

Metastasis

InteRNA’s miRNA target identification/validation platform

18 © InteRNA Technologies B.V.

State-of-the-art genomics/sequencing

technologies

&

bioinformatics

Novel miRNAs

In vivo PoC

&

(Pre-)Clinical development

Functional screening with library of known & novel

miRNAs

miRNA drug candidates

Downstream biology

&

identification of biomarkers

Mechanism of Action

IP

IP

InteRNA’s unique library of 1100 miRNA sequences serves as product engine

19 © InteRNA Technologies B.V.

Validated platform for rapid identification of therapeutic miRNAs

miRBase v16

(Sanger)

Proprietary to

InteRNA

550 100 450

Lentiviral-based miRNA overexpression library

Functional assays

Drug candidates

EMT Targeting microRNAs

• 1120 miRNAs screened (InteRNA library)

• Identification of miRNAs

increasing

EMT LUC reporter

miR-a miR-b miR-c miR-d miR-e0.00

0.20

0.40

0.60

0.80

1.00

Rela

tiv

e T

um

or

Cell

Inv

asio

n

Inhibition of Cell Invasion

0

20

40

60

80

100

p = 0.033

miR-d control Lu

ng

met

asta

tic

bu

rde

n (

%)

miR-d

control

Inhibition of Metastasis

Next Generation Life Sciences - Case study Current data insufficient to reliably identify bona-fide miRNA targets

Need to improve understanding of effect miRNA on cancer cell metastasis

Need to combine transcriptomics, proteomics and dedicated bioinformatics

Join forces in ZonMW-DTL project proposal

Department Urology

Dr. Gerald Verhaegh

Prof Jack Schalken Dr. Iman Schultz

Dr. Paula van Noort

Dr. Jolein Gloerich

Prof. Alain van Gool

Dr. Lars Verschuren

Dr. Thomas Kelder

Dr. Marijana Radonjic

biology miRNA

proteomics bioinformatics

Proteomics approach

• Bottom-up proteomics (shotgun)

• Protein identification

• Differential protein expression profiling

Established (>300 projects done)

• Targeted proteomics

• Absolute/relative quantitation

Emerging (5 projects ongoing)

• Top-down proteomics

• Intact protein characterization

• Differential PTM analysis

New

Example of cellular proteome profiling project

Results

Samples

Up regulated

Down regulated

Differential analysis

-10

-5

0

5

10∞

∞

Results

Gene ontology: cellular localization

• 3,824 proteins identified in a sample (98% cell specific)

• 2,550 proteins quantified and used for differential analysis

• 178 proteins differentially expressed due to treatment:

(138 up, 40 down)

Conclusions

Project with TNO

Q: how does proteome cell line x look like?

Q: First look at effect treatment on proteome (feasibility)

→ GeLC-MS approach

1. Quantify 2. Integrate with

prior knowledge

4. Link to health benefit 5. Improved (personalized)

interventions

(Omics assays, Physiology,

Anthropometry, Imaging,

Challenge tests, etc.)

System Biology analysis @TNO: Workflow

LIFESTYLE

NUTRITION

PHARMA

3. Integrate, map and

understand relationships

Martina Kutmon, Chris Evelo, Thomas Kelder

Open source software: http://projects.bigcat.unimaas.nl/cytargetlinker/

CyTargetLink: Regulatory Interaction Networks

• Network data integration, analysis

and visualization

• Cytoscape App

26

Martina Kutmon

strategy to identify miRNA targets

Phenotypic confirmation

Western Blot 3’ UTR assay RT qPCR

Homing

Migration

Cytoskeleton

Cell movement

Invasion

Cell death

Apoptosis

Control cells

miRNA-d over Expressed cells Target

prediction

Experimental Validation

Transcriptomics

(RNA-Seq)

Proteomics

(LC-MS/MS)

Data Integration

Joined

CyTargetLink

Acknowledgements

Lars Verschuren

Thomas Kelder

Marijana Radonjic

Jildau Bouwman

Ben van Ommen

and others

Gerald Verhaegh

Jack Schalken

alain.vangool@tno.nl, alain.vangool@radboudumc.nl

Jolein Gloerich

Hans Wessels

Ron Wevers

Dirk Lefeber

Leo Kluitmans

and others

Iman Schultz

Paula van Noort

Martina Kutmon

Chris Evelo

Rainer Bischoff

Theo Luider

Ron Wevers

and others