Lecture at the Biomarker development Center conference on biomarker validation in Rotterdam, outlining opportunities in translational biomarkers but also steps that need to be taken still.

1. Translational biomarkers,
time for quality, not quantity
Professor Personalized Healthcare
Head Translational Metabolic Laboratory
Alain van Gool

2. www.radboudumc.nl

3. Diagnostics is the GPS for Personalized Healthcare
“we create personalized diagnostics”
3 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

4. 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]
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5. Increase in genome diagnostics
Agilent V4  V5
0
100
200
300
400
500
600
700
january
februari
march
april
may
june
july
august
september
october
november
december
january
februari
march
april
may
june
july
august
september
october
november
december
january
februari
march
april
may
june
july
august
september
october
november
december
january
februari
march
april
may
june
july
2013
(n=1,533)
2014
(n=4,213)
2015
(n=5,964)
Q1-Q2 2016
(n=3,543)
#clinicalexomes/month
Outsourcing to BGI
Agilent V4
Hiseq2000
2016:
8000 exomes
at
Human Genetics Nijmegen (Lisenka Vissers, Marcel Nelen, Han Brunner et al)
5 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

6. Added value of WES
Total number of patients
with a possible diagnosis: 41
Diagnostic yield WES in retrospective cohort (n=150)
Whole Exome Sequencing testing
Total number of tests: 150 (x3)
Average #tests/patient: 1
Genetic cause identified: 44
Standard GENETIC testing
Total number of tests: 810
Average #tests/patient: 5.4 (1-28)
Genetic cause identified: 11
Human Genetics Nijmegen (Lisenka Vissers, Marcel Nelen, Han Brunner et al)
6 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

7. Functional Omics platforms in Translational Metabolic Lab
Research Biomarkers Diagnostics
Translational Metabolic Laboratory (www.youtube.com/watch?v=yhLbuX0H7rg)
Targeted proteomics
Glycopeptidomics
500
1000
1500
2000
m/z
5 10 15 20 25 30 35 40 Time [min]
Metabolomics
400
600
800
1000
1200
1400
m/z
10 20 30 40 50 60 Time [min]
Bottom-up proteomics
Glycomics
Top-down proteomics
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8. 3.Proteinglycosylation
Activatedsugars
ER/Golgi
TissuespecificGlycoCODE
Cytosol
1. Novel genetic Factors
Carbohydrate
metabolism
Nucleotide
metabolism
Amino acid
metabolism
Lipid
metabolism
Energy
metabolism
Carbohydrate
metabolism
Nucleotide
metabolism
Amino acid
metabolism
Lipid
metabolism
Energy
metabolism
Carbohydrate
metabolism
Nucleotide
metabolism
Amino acid
metabolism
Lipid
metabolism
Energy
metabolism
2.MetabolicNetworks
Center for Disorders of Glycosylation
Genomics & Glycomics / Glycoproteomics
Am J Hum Gen 2009; Cell & Brain 2010; PLosGenetics 2011
Ann Neurol 2012; Nature Genetics 2012; New Eng J Med 2014
Chem Biol 2015; Nature Genetics 2016
Dirk Lefeber
Monique van Scherpenzeel

9. Analyse protein glycosylation at different levels
1. Intact
glycoproteins
3. Free glycans
2. Glycopeptides
500
750
1000
1250
1500
1750
m/z
10 15 20 25 30 35 40 Time [min]
Glycopeptide spectrum
Nanochip-PGC-QTOF
Nanochip-C8-QTOF
9 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

10. 10 Alain van Gool, HUPO, Dublin, 20 Sept 2017
Genomics & Glycomics
SLC8A6
GlycoModelC
ontrol(n=40)
SLC
10A
7-C
D
G
(n=4)
O
therC
D
G
-II(n=21)
-150
-100
-50
0
50
100
P33
P32
P17
P39
Modelvalues
99 patients; 47 without known gene defect
- Glycomics profiling on 99
- Intact transferrin glycoprofiling on 99
- Whole Exome Sequencing for 32 cases
PGM1: New Eng J Med 2014
Man1B1: Brain 2014
More subtle changes: here
(manuscript in prep)

11. Moving to glycoproteins as biomarkers
Gene
Protein
N-Glycosylation
11 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

12. Comprehensive glycopeptide profiling
• Mass spectrometry analysis of glycoproteins in human plasma
• 1/20 microliter analysis: detection of 1.000.000 signals in one scan (1,4 Gb)
• ~40.000 peptides of which >80% contain sugar modification
• Potential to screen patients and identify new biomarkers?
500
1000
1500
2000
m/z
5 10 15 20 25 30 35 40 Time [min]
Proof of principle study:
Biomarkers !?
12 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

13. Comprehensive glycopeptide profiling workflow
{Hans Wessels, Anouk Suppers, Maurice van Dael, Monique van Scherpenzeel, Dirk Lefeber}

14. Comprehensive glycopeptide profiling workflow
Comprehensive QC analytics

15. Glycopeptide profiling cohort study
• 40 Controls
• 118 Patients with known CDG-II gene defects
• 30 Patients with unknown gene defect
• 12 Patient controls (normal Transferrin)
• 44 Technical analyses
- Sample stability (protein & peptide level)
- Inter & intra essay variability
- Reproducibility
- Different blood collection tubes (EDTA, Na-Heparin, Li-Heparin, Serum)
• Patient and control samples were analyzed by glycopeptide profiling,
glycomics, and Transferrin Q-TOF MS.
• Patient WES data available.
{Hans Wessels, Maurice van Dael, Anouk Suppers, Monique van Scherpenzeel, Alain van Gool , Dirk Lefeber: manuscript in prep}
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16. High diagnostic value of glycopeptide profiles
16 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

17. Performance Glycopeptide profiling versus Glycomics
GlycomicsGlycopeptide
profiling
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18. Translate to intact glycoprotein diagnostic test
{Dirk Lefeber, Monique van Scherpenzeel}
• 12 families with liver disease and dilated cardiomyopathy (5-20 years)
• Specific sugar loss of serum transferrin identified via glycoproteomics
• Genetic defect in glycosylation enzyme (PGM1) identified via exome sequencing
• Outcome 1: Explanation of disease
• Outcome 2: Dietary intervention as succesful personalized therapy
• Outcome 3: Glycoprofile of intact transferrin protein as diagnostic test
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19. 19 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

20. However … 3 innovation gaps !
innovation
1. Research to research
2. Research to diagnostics
3. Research to society
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21. 1. Irreproducibility of data
{Freedman et al, PLOS Biology, 2015}
{2012} {2011} {2013} {2008}{2012}
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22. Categories of errors leading to irreproducibility
{Freedman et al,
PLOS Biology, 2015}
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23. 2. Critical component in biomarker R&D: Data
{Wilkinson et al,
Nature Scientific Data, 2016}
Need to increase quality in:
• Data capture
• Data stewardship (FAIR)
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24. DATA STEWARDSHIP: INTEROPERABILITY IS KEY
If data are interoperable … … analytics provide new knowledge
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25. Community building towards FAIR proteomics data
25 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

26. However … 3 innovation gaps !
innovation
1. Research to research
2. Research to diagnostics
3. Research to society
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27. 1. 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
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28. 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
Nov 2016: 14,481 biomarkers
Oct 2017: 15,463 biomarkers
Discovery Clinical
validation/confirmation
Diagnostic
test
Number of
biomarkers
Gap 1
Gap 2
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29. Choice for biomarker scientists: discover or confirm?
29 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

30. Good example of multi-laboratory biomarker validation
3 biomarkers:
• Aβ42
• T-Tau
• P-Tau
30 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

31. Good example of multi-laboratory biomarker validation
31
Adoption of best biomarker practice ???

32. 2. Need for innovation in protein biomarker diagnostics
Current diagnostic protein assays:
• Mostly protein abundance
• Often unknown epitope of detection
• Ignore occurence of proteoforms
Room for innovation !
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33. Moving towards intact protein biomarker analysis
Epitope / fragment analysis
Intact protein analysis
33 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

34. Intact protein analysis
{Hans Wessels, Roel Tans}
Top-down proteomics
Towards a routine application of Top-Down
approaches for label-free discovery workflows.
Schmit PO, et al. J Proteomics. 2017 Aug 27.
34 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

35. However … 3 innovation gaps !
innovation
1. Research to research
2. Research to diagnostics
3. Research to society
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36. 1. Translation is key in Personalized Healthcare
Personal profile data
Knowledge
Understanding
Decision
Action
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37. 37
2. Selfmonitoring
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38. Challenge: translate laboratory to society
• Point-of-care analysis of
few biomarkers
• 1.000.000 signals per
proteomics analysis
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39. Translation is key in Personalized Healthcare
“I’m afraid you’re
suffering from an
increased IL-1β and
an aberrant miR843
expression”
Adapted from:
?
39 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

40. Moving forward from quantity to quality
innovation
1. Research to research
2. Research to diagnostics
3. Research to society
40 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

41. 1. Focus on the end user: the patient / citizen
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42. 2. Progress through collaboration
(local)
(European)
(Netherlands)
(global)
42 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

43. Build biomarker validation pipelines
Standardisation, harmonisation,
knowledge sharing in:
1. Assay development
2. Clinical validation
www.biomarkerdevelopmentcenter.nl
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44. Ongoing independent biomarker activities
Europe
USA
{Asadullah et al, Nature Reviews Drug Discovery, Dec 2015}
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45. Collaboration towards Good Biomarker Practices
{van Gool et al, Nature Reviews Drug Discovery, Apr 2017}
COST action CA16113
http://clinimark.eu
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46. Collaboration towards a Netherlands X-omics Initiative
www.x-omics.nl
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47. Collaboration towards nationwide programs
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48. And learn from other fields!
48 Alain van Gool, BDC conference, Rotterdam, 06 Oct 2017

49. Acknowledgments
Translational Metabolic Laboratory
Hans Wessels
Anouk Suppers
Maurice van Dael
Dirk Lefeber
Monique van Scherpenzeel
Nurulamin Bin Abu Bakar
Roel Tans
Esther Willems
Wynand Alkema
Jenneke Keizer-Garritsen
Jolein Gloerich
Ron Wevers
Alain van Gool
and others
Pierre-Olivier Schmit
Kristina Marx
Stuart Pengelley
Gary Kruppa
Collaborators/funders
Human Genetics Nijmegen
Marcel Nelen
Alexander Hoischen
Lisenka Vissers
Christian Gillisen
Han Brunner
and others
alain.vangool@radboudumc.nl
www.linkedIn.com/in/alainvangool
www.slideshare.net/alainvangool
CarTarDis
Irene Keularts
Hans Scheffer
and others