2016 08-22 Radboud Grand Round, Nijmegen, Alain van Gool

‘Personalized Health(care) doe je samen’

Prof Alain van Gool +

Radboud Grand Round 22 Augustus 2016

My path 1989-now

• Molecular biology

• Mechanisms of disease

• Biomarkers

• Omics / technologies

• 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

2 Alain van Gool, Radboudumc Grand Rounds, 22 Aug 2016

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

Consider individual differences in life science research

3


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

Principle of Personalized Medicine

4

• The right drug for right patient at right dose at right time • Molecular biomarkers as key drivers of patient selection • = Precision medicine or Targeted medicine


Example: 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 !


Personalized medicine in melanoma

Treat patients with

B-RAFV600E mutation Inhibit growth of cell

Patients live longer Tumors disappear Cells stop growing

B-RAF inhibitor


Emerging Personalized / Precision / Targeted Medicine

2010:

5% of drugs in pipeline had companion diagnostic biomarker test

2015:

80%

50%


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Optimal Personalized / Precision / Targeted Medicine

People are more than linear pathways

{Source: Barabási 2007 NEJM 357; 4}

• People are different • Different systems and networks • Different risk factors • Different preferences


Societal need in efficient personalized health(care)

{Source: prof Jan Kremer}

Towards cost effective care, less cure


Highest need in efficient personalized health(care)

It’s personal !

‘I want to stay healthy.’ ‘If not, how do I get healthy?’


3 key aspects of personalized health(care)

‘I want to stay healthy. If not, how do I get healthy?’

1. What to measure?

2. How much can it change?

3. What should be the follow-up for me?


1. What to measure?

Exponential technological developments • 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]


Crash course in molecular biology

DNA, protein, cell, tissue, system biology


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 • Diagnose 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:

{Hans Wessels, Monique van Scherpenzeel, Dirk Lefeber, Alain van Gool} Biomarkers !?


Innovation in protein biomarker diagnostics

Current diagnostic protein assays:

• Mostly protein abundance

Emerging:

• Post-translational modifications

• Intact proteins

• Protein complexes


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}



Intact protein analysis

Bottom-up proteomics

Top-down proteomics

{Hans Wessels, Alain van Gool}

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

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

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

Uric acid Human samples

Plasma, CSF (urine) Controls vs. patient

QTOF Mass Spectrometry

- Reverse phase liquid chromatography - Positive and negative mode - Features

XCMS Alignment Peak comparison > 10,000 Features

Next generation metabolic screening

Xanthine

Whole Exome Sequencing

{Leo Kluijtmans, Ron Wevers (TML) + Genetica}

Challenge: translate laboratory to society

• Heart beat • Steps / movement • Glasses water/coffee • 1.000.000 molecules per analysis


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New data (generators, owners)


https://www.google.nl/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&ved=0ahUKEwiCtoa38dTOAhXF2xoKHa-4AKIQjRwIBw&url=https://www.flickr.com/photos/philips_newscenter/albums/72157647098220647/&bvm=bv.129759880,d.d2s&psig=AFQjCNFvo2ckn1lyFQaSdHRflHAPCqnyRA&ust=1471950479842655

What does my DNA tell me?

23% chance blond hair 3.1% Neanderthaler DNA


Genetic risk lung cancer → don’t smoke !

What does my DNA tell me?

No expected adverse reaction to Warfarin


Need for optimal quality in health biomarker analyses

Test, interpret, advice

“Post-traumatic Test Syndrome” ?


Try-outs at REshape Center of Health(care) Innovation

Lucien Engelen

… but not all data is useful data !



1. What to measure?




healthy disease disease + treatment


Subgroups

100%

Individual

Population


Past

Present

Future

Personalized health(care) model Personalized Intervention

of patients-like-me Personal thresholds of persons-like-me

Big Biomarker Data

Molecular Non-molecular Environment …

Ho

meo

sta

sis

A

llo

sta

sis

D

isease

Time

Disease

Health

Selfmonitoring

Adapted from Jan van der Greef, TNO

Personal profile

Personalized health

Personalized medicine




1. What to measure?





Personal profile data

Knowledge

Understanding

Decision

Action


Daily views of molecular system biologists β-cell Pathology

gluc Risk factor

{Source: Ben van Ommen, TNO}

therapy


Translation is key in Personalized Healthcare !

“I’m afraid you’re

suffering from an

increased IL-1β and

an aberrant miR843

expression”

Adapted from:

?



Translating Personalized Health(care) in society

We need a personalized data-driven GPS for health

• Monitor on background

• Alert when you are at risk

• Advice what to do


http://www.google.nl/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&ved=0CAcQjRxqFQoTCJ6kuJXIvcYCFYFcFAodO2oP3A&url=http://arstechnica.com/apple/2014/03/ios-in-the-car-becomes-carplay-coming-to-select-dashboards-this-year/&ei=TsSVVZ7FO4G5UbvUveAN&bvm=bv.96952980,d.d24&psig=AFQjCNHK-5180CQ5Wim0GGTOe8N0tIZRIQ&ust=1435964869551370

Translational medicine using simulation + feedback

Simulating YOUR health + Personalized advice + Feedback


Personalized Healthcare @ Radboudumc :

Focus on the end user: the patient / citizen


Patient

Radboud Personalized Healthcare

A significant impact

on healthcare

Molecule

Population


Personalized Healthcare @ Radboudumc

People are different Stratification by multilevel diagnosis

+ Patient’s preference of treatment

Exchange experiences in care communities Select personalized therapy

Population

Man

Molecule

41 Alain van Gool, Radboudumc Grand Rounds, 22 Aug 2016 www.radboudumc.nl/Research/Pages/PersonalizedHealthcare

Be proud of what we achieve !


Research themes and institutes

www.radboudumc.nl/Research/Themes/Pages/default.aspx

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Orientation across the spectrum from molecule to man to population

Ori

enta

tio

n a

cro

ss

the

spec

tru

m o

f d

isea

ses

PI

Research theme

Te

chn

olo

gy

C

ente

rs

Research support by Technology Centers

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www.radboudumc.nl/research/technologycenters

Radboudumc Technology Infrastructure

Get organised:

1. What technological expertise do we have and should we have ?

2. How should we organise this ?

3. How will we communicate this ?


www.radboudumc.nl/research/technologycenters 46

Genomics

Bioinformatics

Animal studies

Stem cells

Translational neuroscience

Image-guided treatment

Imaging

Microscopy

Biobank

Health economics

Mass Spectrometry

Radboudumc Technology

Centers

Investigational products

Clinical studies

EHR data analysis

Statistics

Human performance

Data stewardship

Molecule

Flow cytometry

3D lab

About 280 dedicated people working in 19 Technology Centers, ~1800 users (internal, external), ~150 consortia www.radboudumc.nl/research/technologycenters/ 47

• Proteins • Metabolites • Drugs • PK-PD • Preclinical

• Clinical

• Behavioural • Preclinical

• Animal facility • Systematic review

• Cell analysis • Sorting

• Pediatric • Adult • Phase 1, 2, 3, 4

• Vaccines • Pharmaceutics • Cyclotron • Radio-isotopes • Malaria parasites

• Management • Analysis • Sharing • Cloud computing

• DNA • RNA

• Internal • External

• Early HTA • Evidence-

based surgery • Field lab

• Statistics • Biological • Structural

• Preclinical • Clinical

• Economic viability

• Decision analysis

• Experimental design • Biostatistical advice

• Electronic Health Records

• Transmural translation

• Best practice

• In vivo • Functional

diagnostics

• iPSC • Organoids

• 3D imaging • 3D printing • Virtual reality

Working with/within other networks Region, nation, Europe, world

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Peggy Manders Gerhard Zielhuis

Peter Friedl Otto Boerman

Alain van Gool (Scientific Lead Technologies)

RADBOUD RESEARCH FACILITIES

Otto Boerman (Head Imaging Platform) Alain van Gool (Head Biomarker Platform)

Via DTL

Grootschalige Wetenschappelijke Infrastructuur

Acknowledgements

Ron Wevers

Jolein Gloerich

Hans Wessels

Dirk Lefeber

Monique Scherpenzeel

Leo Kluijtmans

Lucien Engelen

Nathalie Bovy

Paul Smits

Maroeska Rovers

Bas Bloem

the 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

Lars Verschuren

Marjan van Erk

Peter van Dijken

Heleen Wortelboer

Wessel Kraaij

Peter Wielinga

Ronald Mooij

Suzan Wopereis

and many others

CarTarDis


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

2016 08-22 Radboud Grand Round, Nijmegen, Alain van Gool

Health & Medicine

Transcript of 2016 08-22 Radboud Grand Round, Nijmegen, Alain van Gool