Proteomics in personalized medicine and big data approaches DTL FOCUS meeting, Utrecht 29 Augustus 2016 Prof Alain van Gool

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

Senior Scientist Integrator Biomarkers

Scientific lead DTL-Technologies

Chair Biomarker Platform

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Principle of Personalized Medicine

Source: Chakma, Journal of Young Investigators, 16, 2009

• The right drug for right patient at right dose at right time • Companion diagnostics as key drivers of patient selection • = Precision medicine or Targeted medicine 2

Alain van Gool, DTL FOCUS meeting, 29 Aug 2016

Exponential technological developments • Next generation sequencing • DNA, RNA • Risk analysis and therapy selection m/z

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

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• Imaging • Non invasive images, real time • Spatial view of intact organs and organisms

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Alain van Gool, DTL FOCUS meeting, 29 Aug 2016

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Time [min]

Companion diagnostics Good examples personalized medicine in Oncology and Neurosciences (113 drug labels): •

Cyp450, Her2/neu, BRCA, BRAF, EGFR, EML4/ALK, etc

Emerging companion diagnostics, also linked to non-drug therapies: • Volker:

Intestinal surgery → XIAP →

Cord blood

• Beery twins:

Cerebral palsy →

SPR →

Diet 5HTP

• Wartman:

Leukemia →

FLT3 →

Sunitinib

• Gilbert:

Healthy →

BRCA →

Mas/Ovarectomy

• Snyder:

T2Diabetes →

GCKR, KCNJ11 →

Diet, exercise

• Lauerman:

Scotoma, leg →

JAK2 →

Aspirin

• Bradfield:

Healthy →

CDH1 →

Gastrectomy

Coming up: metabolic biomarkers, imaging biomarkers

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Alain van Gool, DTL FOCUS meeting, 29 Aug 2016

Approved protein biomarkers

• 217 in biomarker database • Double annotations • Good starting point Contact Lars Verschuren (TNO)

Approved protein biomarkers (LC-MS)

Advances in mass spectrometry • • • •

Mass spectrometry analysis of glycoproteins in human plasma 0,05 microliter analysis: detection of 1.000.000 signals in one scan (1,4 Gb) ~40.000 peptides of which >80% contain sugar modification To diagnose patients and identify new biomarkers Proof of principle study:

m/z

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{Hans Wessels, Monique van Scherpenzeel, Dirk Lefeber, Alain van Gool} 7

Alain van Gool, DTL FOCUS meeting, 29 Aug 2016

Time [min]

Biomarkers !?

MS enables innovation in protein biomarker diagnostics

Current diagnostic protein assays: • Mostly protein abundance • Often unknown epitope • Ignore diversity in proteoforms Potential novel biomarker analytes: • Post-translational modifications • Intact proteins • Protein complexes

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Alain van Gool, DTL FOCUS meeting, 29 Aug 2016

Targeted proteomics

Protein A isoform 1 Protein A isoform 2 Protein B

• Peptide-based • Sensitive quantitative analysis • Suitable for very complex samples

Nature Methods: Method of the year 2012

protein expression data {Jolein Gloerich, Alain van Gool} 9

Alain van Gool, DTL FOCUS meeting, 29 Aug 2016

Intact protein analysis Bottom-up proteomics

Top-down proteomics

{Hans Wessels, Alain van Gool} 10 Alain van Gool, DTL FOCUS meeting, 29 Aug 2016

New diagnostic glycoprotein biomarker • • • • • •

Rare metabolic disease cases (liver disease and dilated cardiomyopathy) Combination glycoproteomics and exome sequencing Identification of deficient enzyme in glycosylation pathway Outcome 1: Explanation of disease Outcome 2: Dietary intervention as succesful personalized therapy Outcome 3: Glyco -transferrin profile developed as diagnostic mass spec test

{Monique van Scherpenzeel, Dirk Lefeber} 11 Alain van Gool, DTL FOCUS meeting, 29 Aug 2016

Intact complexome proteins as new biomarker? • • • • •

Native tissue biopsies Isolate intact membrane complexes Separate and isolate complexes using native gels LC-MS/MS analysis of intact proteins Data analysis • • •

Tissue 1 (n=3)

Tissue 2 (n=3)

Subunit Subunit – tissue 1

Subunit – tissue 2

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{Hans Wessels, Susanne Arnold, Uli Brandt, Alain van Gool}

Identified protein sequence of subunit Deduce simulated sequences from database Determine fit with experimental data

Challenge: translate laboratory to society

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1.000.000 molecules per analysis

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• • •

Heart beat Steps / movement Glasses water/coffee

… but not all data is useful data !

However … Biomarker innovation gaps!

Number of biomarkers

Gap 1 Gap 2 Discovery

Clinical validation/confirmation

• Too much biomarker discovery • Too little development to application 15 Alain van Gool, DTL FOCUS meeting, 29 Aug 2016

Diagnostic test

Gap 3

Irreproducibility of data

{Freedman et al, PLOS Biology, 2015}

{2012}

16 Alain van Gool, DTL FOCUS meeting, 29 Aug 2016

{2011}

{2013}

{2012}

{2008}

Categories of errors leading to irreproducibility

{Freedman et al, PLOS Biology, 2015}

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Add to this: bad Data Stewardship

{Wilkinson et al, Nature Scientific Data, 2016}

80% of data is not FAIR:

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Findable, Accessible, Interoperable, Reusable

Build biomarker validation pipelines

Standardisation, harmonisation, knowledge sharing in: 1. Assay development 2. Clinical validation

NL Roadmap Molecular Diagnostics (2012)

NL Grant 4.3M Eur (2014)

www.biomarkerdevelopmentcenter.nl 19 Alain van Gool, DTL FOCUS meeting, 29 Aug 2016

(Netherlands)

Ongoing independent biomarker activities Europe

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

USA

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Nationale wetenschaps agenda

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16 routes Workshops April/May Advice to government

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Health RI

Downloadable at www.dtls.nl

Emerging Health Research Infrastructure community NL

www.dtls.nl 24 Alain van Gool, DTL FOCUS meeting, 29 Aug 2016

Acknowledgements Jolein Gloerich Hans Wessels Dirk Lefeber Monique Scherpenzeel Leo Kluijtmans Ron Wevers Lucien Engelen Nathalie Bovy Paul Smits Jan Kremer Bas Bloem the Technology Centers and many others [email protected] [email protected] www.linkedIn.com www.slideshare.net/alainvangool 25 Alain van Gool, DTL FOCUS meeting, 29 Aug 2016

Jan van der Greef Ben van Ommen Ivana Bobeldijk Hans Princen Lars Verschuren Marjan van Erk Suzan Wopereis Heleen Wortelboer Wessel Kraaij Peter van Dijken Cyrille Krul and many others

Many collaborators and funders

CarTarDis

www.radboudumc.nl/personalizedhealthcare www.radboudumc.nl/research/technologycenters www.radboudresearchfacilities.nl

Slide from: Alain van Gool, Eur Commission advice, 11 Sept 2012

Reasons for biomarker innovation gap • • • • • • • • •

Not one integrated pipeline of biomarker R&D Publication pressure towards high impact papers Lack of interest and funding for confirmatory biomarker studies Hard to organize multi-lab studies Biology is complex on organism level Data cannot be reproduced Bias towards extreme results Biomarker variability …

{Source: Prinz, Schlange, Asadullah, Nat Rev Drug Disc 2011}

{Source: John Ioannidis, JAMA 2011} 26