2016 11-01 biomarker agora, copenhagen, alain van gool

Innovation in clinical molecular biomarkers: time for quality, not quantity

Prof Alain van Gool

Copenhagen 1 Nov 2016

A short story: Personalized medicine in melanoma

B-RAFV600E mutation Strong growth of cell Growth of tumor

• B-RAFV600E cells always grow and become cancer cells

• RAF inhibitors will block pathway, block cell growth and inhibit cancers that have a B-RAFV600E mutation

• 60% of melanoma patients have B-RAFV600E mutation

• Basis for a personalized medicine !

*

2 Alain van Gool, Biomarker Agora, Copenhagen, 1 Nov 2016

Biomarkers to support clinical development

• Within Schering-Plough 4 Lead Optimisation programs in ERK pathway (2009)

• Need for blood-based biomarker that indicated downstream effects of drugs:

• Inhibition ERK pathway (pharmacodynamic)

• Tumor inhibition (efficacy)

• Extensive transcriptomics profiling: IL-8 as promising candidate biomarker

Data for RAFi #4

RAFi

MEKi

ERKi

RA

Fi #

1

RA

Fi #

2

RA

Fi #

3

RA

Fi #

4

MEK

i #1

MEK

i #2

ERK

i #1


Validation study to confirm IL-8 in melanoma

Literature

{Yurkovetsky, et al. Clin Cancer Res, 2007}

Objectives: • Confirm elevated IL-8 in melanoma

• Develop IL-8 assays for clinical use



Stage 1 Stage 2 Stage 3 Stage 4

H&E staining; 20x

59 melanoma samples (tumor tissue (ffpe) + matching serum & plasma, stage I-IV, from two independent biobanks) + 40 healthy serum & plasma samples

1. Genetic analysis for BRAFV600E/D mutation in genomic DNA from tissue

2. IL-8 mRNA analysis in tissue samples by in situ hybridisation using bDNA probes (multiplexing with 12 ERK pathway response transcripts)

3. IL-8 protein analysis in tissue samples by immunohistochemistry (in parallel with 4 other ERK pathway response proteins, Ki67, Tunnel)

4. IL-8 protein analysis in matching plasma and serum by IL-8 immunoassay (3 formats: ELISA, Luminex, Mesoscale; singleplex and multiplex)

partial

OK

OK

?



Literature

{Yurkovetsky, et al. Clin Cancer Res, 2007}

Own data

{Unpublished, 2010}

Cause?

(6 months, 4 fte, USD 1.000.000)


Irreproducibility of data

{Freedman et al, PLOS Biology, 2015}

{2012} {2011} {2013} {2008} {2012}


Categories of errors leading to irreproducibility

{Freedman et al, PLOS Biology, 2015}


Lessons learned?

Particularly for this case: 1. Know sample history

• IL-8 protein appeared sensitive to freeze-thawing

2. Know all relevant information from the source (patient) • Tumor load may be too low for our patients

3. Do these type of expensive validation studies together ! • Share burden, increase power, ensure better data

If we want to innovate clinical molecular biomarkers, we need to increase quality, not quantity of our research.



Alain’s path 1989-now • Basis in molecular biology

• Academia, pharma, medical center, applied research institutes

• Biomarkers / Omics / technologies

• Mechanisms of disease

• Translational medicine

• Personalized healthcare

Senior Scientist Integrator Biomarkers

Scientific lead DTL-Technologies

Head EATRIS Biomarker Platform

Professor of Personalized Healthcare Head Radboud Center for Proteomics, Glycomics & Metabolomics Coordinator Radboud Technology Centers

https://www.google.nl/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&ved=0ahUKEwiLsvL0--jMAhWKWhQKHUFEBWMQjRwIBw&url=https://en.wikipedia.org/wiki/Leiden_University&bvm=bv.122448493,d.ZGg&psig=AFQjCNG2nD-SOcwwEdKmo9jecYe4fqRj-w&ust=1463844511999998

Exponential technology developments in laboratories

• Next generation sequencing

• DNA, RNA • Risk analysis and therapy selection

• Mass spectrometry • Proteins, metabolites • Monitoring of disease and treatment effects

• Imaging

• Non invasive images, real time

• Spatial view of intact organs and organisms

500

1000

1500

2000

m/z

5 10 15 20 25 30 35 40 Time [min]


A changing world: Getting digital


14

New data ! (generators, owners)


Ongoing: translate laboratory to society

• Point-of-care analysis of few biomarkers

• 1.000.000 signals per proteomics analysis


and many many many more …


Demo room

Biomarker innovation gaps !

Discovery Clinical

validation/confirmation

Diagnostic

test

Number of

biomarkers

Gap 1

Gap 2


• Too much biomarker discovery • Too little development to application

Biomarker innovation gaps: some numbers

~ 5 biomarkers/ working day

1 biomarker/ 1-3 years

1 biomarker/ 2-10 years

Eg Biomarkers in time: Prostate cancer May 2011: 2,231 biomarkers Nov 2012: 6,562 biomarkers Oct 2013: 8,358 biomarkers Nov 2014: 10,350 biomarkers Oct 2015: 11,856 biomarkers 31 Oct 2016: 14,461 biomarkers

Discovery Clinical

validation/confirmation

Diagnostic

test

Number of

biomarkers

Gap 1

Gap 2


Choice for biomarker scientists: discover or confirm?


Good example of multi-laboratory biomarker validation

3 biomarkers: • Aβ42 • T-Tau • P-Tau


Good example of multi-laboratory biomarker validation

31

Adoption of best biomarker practice ???

Share negative outcomes

Need to build biomarker validation pipelines

Standardisation, harmonisation, knowledge sharing needed in:

1. Assay development

2. Clinical validation

3. Application


Biomarker Development Center (NL)

NL Roadmap Molecular Diagnostics (2012) NL Grant 4.3M Eur (2014)

http://www.erasmusmc.nl/index.htm

Biomarker Development Center (NL)

NL Roadmap Molecular Diagnostics (2012) NL Grant 4.3M Eur (2014)

(+ )


Ongoing independent biomarker activities

Europe

USA

{Asadullah et al, Nature Reviews Drug Discovery, Dec 2015}


European infrastructures

@Radboudumc: Peggy Manders Gerhard Zielhuis

@Radboudumc: Peter Friedl Otto Boerman

@Radboudumc: Otto Boerman (Head Imaging Platform) Alain van Gool (Head Biomarker Platform)

@Radboudumc: Arnoud van der Maas Alain van Gool

@Radboudumc: Saskia de Wildt Paul Smits


The Good Biomarker Practice initiative

Join forces among Europe’s major academic infrastructures + industry to:

1. Establish “Good Biomarker Practice” guidelines

- on translational research, biomarker technologies, biobanking, data stewardship.

2. Efficiently execute high quality biomarker projects

- work together in clinical validation and development of probable biomarkers.


Critical component in biomarker R&D: Data {Wilkinson et al, Nature Scientific Data, 2016}

• Data capture • Data stewardship (FAIR)


FAIR data principles endorsed by G20


Think big, start ‘small’ National Technology Infrastructure (collective of 40+ partners in DTL)

Ruben Kok

Barend Mons

Alain van Gool

Jaap Heringa


Rich history of PPP in the Netherlands

(Centre for Translational Molecular Medicine) (Top Institute Pharma)

(BioMolecular Materials)

Public-private collaboration on diagnosis, drugs, devices (2006-2015)

42 Alain van Gool, BBMRI BIOS symposium, Amsterdam. 21 Sept 2016

Joining forces in Netherlands To drive personalized medicine & health research



https://youtu.be/MpMSkbu9YQg



1-11-2016 46

http://www.alzheimer-nederland.nl/

Health-RI Congress

1 December 2016 De Flint in Amersfoort Register: www.nlhealthresearch.nl

Acknowledgements

Hans Wessels Jolein Gloerich

Roel Tans Esther Willems

Maurice van Dael Jenneke Keizer

Dirk Lefeber Monique van

Scherpenzeel

Leo Kluijtmans Ron Wevers

Marcel Verbeek Lucien Engelen

Jan Kremer Bas Bloem

Nathalie Bovy Paul Smits

the Radboudumc Technology Centers

and many others

www.radboudumc.nl/personalizedhealthcare

www.radboudumc.nl/research/technologycenters

www.radboudresearchfacilities.nl

[email protected]

[email protected]

www.linkedIn.com

www.slideshare.net/alainvangool

Many collaborators and funders

Jan van der Greef Ben van Ommen

Ivana Bobeldijk Hans Princen

Lars Verschuren Marjan van Erk

Suzan Wopereis Heleen Wortelboer

Wessel Kraaij Ronald Mooi

Peter van Dijken Cyrille Krul

and many others

CarTarDis

Ruben Kok Barend Mons

Jaap Heringa Merlijn van Rijswijk and

many others

Anton Ussi Florence Bietrix

Laura Bermejo Andreas Scherer

Sulev Koks Marian Hajduch

Giovanni Migliaccio

and many others



2016 11-01 biomarker agora, copenhagen, alain van gool

Health & Medicine