network modeling of protein-protein interactions to identify and prioritize candidate biomarkers
DESCRIPTION
A presentation from the 2014 Thomson Reuters MetaCore/MetaBase Systems Biology Symposium "Applications of Systems Biology Approaches in Drug Discovery & Development."TRANSCRIPT
NETWORK MODELING OF PROTEIN-PROTEIN INTERACTIONS TO IDENTIFY AND PRIORITIZE CANDIDATE BIOMARKERS
Walter J. Jessen, Ph.D.
Systems Biologist, Data Scientist
Covance Informatics
June 25th, 2014
ONE OF THE WORLD'S LARGEST AND MOST COMPREHENSIVE DRUG DEVELOPMENT SERVICES COMPANIES
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• 12,000 employees in 60 countries• Lead Optimization (toxicology, pharmacology, etc)• Preclinical Development• Clinical Services• Commercialization Services• Biorepository Services• Antibody Products (custom development, online store)
Covance has helped pharmaceutical and biotech companies develop one-third of all prescription
medicines in the market today
INTRODUCTION
SYSTEMS BIOLOGY AND BIOINFORMATICS
• Exposure to a wide range of disease biology
• Very interested in the etiology of disease and what goes wrong at a pathway level
• Many opportunities to work with large amounts of diverse data
1. Identification(find, focus or refine)
2. Prioritization (ranking, statistical enrichment)
3. Confirmation(overlaps with existing knowledge)
4. Discovery(developing new hypotheses)
INTRODUCTION
As a laboratory services provider, Covance offers over 740 validated assays
~500 human analytes ~240 analytes in multiple species, including human
5 Central Labs •CAP/CLIA certified•Good Clinical Practice(GCP) compliant
Companion Diagnostics• Currently supports ~20
proprietary client programs
Translational Biomarker Services•SOP-based research environment •Follows “Good Research Practices”
INTRODUCTION
BioPathways visualizes all Covance assay analytes and antibody products onto pathways
INTRODUCTION
In addition to simply making it easier to help clients find products and services that Covance offers, displaying validated biomarker assays on biological pathways allows for the potential "repurposing" of existing biomarkers:• from one disease context to another• from markers useful only in limited research
settings to candidate markers with clinical utility
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Reduces time and costs associated with assay identification and development
BioPathways benefits our clients
INTRODUCTION
HELP SUPPORT THE DEVELOPMENT OF A BIOMARKER STRATEGY
A deeper dive: biomarker identification and prioritization for internal clients
Typically, very little information is provided and data is needed ASAP for teams to respond to client inquiries:
• Drug target• Therapeutic area
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Identify drug target connections and establish disease context to construct network models
INTRODUCTION
Use two types of network models to support client programs and drive decision-making
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DrugTarget
Associatedgenes
Marker(s)
From Through To
DrugTarget
Associated genes
1. Linear model
2. Radial model
INTRODUCTION
Construction of these context-dependent networks enables the identification of
candidate biomarkers
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Working examples using network modeling
INTRODUCTION
1. Example 1: applied to a psuedo-client project
2. Example 2: applied to a biomarker research project
• Client work is confidential; instead, simulate a project based on previously published research.
• Pharmacodynamic (PD) biomarker identification and prioritization for an experimental cancer drug.
• Identification and validation of a diagnostic biomarker for neurodegenerative disease (autophagy)
LINEAR MODEL
RADIAL MODEL
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Human Mouse models
Bioinformatics/Biostatistics
CCHMC (Cincinnati, OH)Nancy Ratner, Jianqiang Wu, Tilat Rizvi
Foundation Jean Dausset (Paris, France)Marco Giovannini, Jan Manent
CCHMC (Cincinnati, OH)Bruce Aronow, Walter Jessen, Sergio Kaiser
University of Alabama (Birmingham, AL)Grier Page, Tapan Mehta
CCHMC (Cincinnati, OH)Nancy Ratner, Shrya Miller, Atira Hardiman
MGH/Harvard (Boston, MA)Anat Stemmer-Rachamimov
University of Florida (Gainseville, FL)Margaret Wallace
L’Hospitalet de Llobregat (Barcelona, Spain)Concepcion Lazaro, Eduard Serra
INTRODUCTION LINEAR MODEL
Example 1: simulate a project based on previously published research.
Background: Neurofibromatosis Type 1 (NF1)RAS activation stimulates downstream signaling
Downward J, Cancer: A tumor gene’s fatal flaws. Nature. 2009 Nov 5;462(7269):44-5.
Canonical Ras effector pathway a.k.a. MAP kinase activity pathway
Canonical Ras effector pathway a.k.a. MAP kinase activity pathway
• Genetic disease• Most common hereditary tumor predisposition
syndrome (prevalence 1:3500)• Causes tumors to grow along peripheral nerves• NF1 encodes neurofibromin, a RAS-GAP
(tumor suppressor)• Reduced NF1 expression causes increased
Ras activationDermal neurofibroma95% patients affected
Plexiform neurofibroma25% affected
MPNST 10-13% affected
INTRODUCTION LINEAR MODEL
No effective treatments exist
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Study focus: identify pathways for tumorigenesis and malignancy conserved between 8 mouse NF1 models and human NF1 tumors
Jessen et al. MEK inhibition exhibits efficacy in human and mouse neurofibromatosis tumors. J Clin Invest. 2013 Jan 2;123(1):340-7.
***
*
Data highlighted altered transcriptional regulation of
Raf/MEK/ERK signaling
****
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Have negative regulators suppressed ERK signaling?
Paraffin tissue sections: brown staining indicates detection of active (p)-ERK
Despite increased expression of negative regulators, ERK activation is maintained in NF1 neurofibromas and MPNSTs
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Empirical Formula: C16H14F3IN2O4
Perform preclinical trials with the MEK inhibitor PD0325901 in mouse models
• An orally bioavailable, selective and nonATP-competitive MEK inhibitor
• Derivative of ci-1040 developed by Pfizer
• Inhibits both MEK isoforms: MEK1 & MEK2
• Currently in cancer clinical trials
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PD0325901 reduces p-ERK and inhibits MPNST cell growth
A-D. p-ERK absent 30 mins after treatment (10 mg/kg)E. Dose response on 5 MPNST cell lines (active at [nM])F. Significantly reduced tumor volume (by day 5)G. MPNST xenograft survival doubled 3 months post treatment
INTRODUCTION LINEAR MODEL
PD0325901 shrinks tumors in >80% of mice testedand maintains MEK inhibition in neurofibromas
Supports MEK signaling as an important clinical target in NF1
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Analyze expression of 2 negative regulators: SPRY4 and DUSP6
How to model the question
MEK1/2NF1-associated genes SPRY4, DUSP6
IDENTIFY AND PRIORITIZE BIOMARKERS FOR PD0325901 IN NF1
1. Linear model DrugTarget
Associatedgenes
Marker(s)
From Through To
Data sources used to provide context:• MetaCore• ToppGene at CCHMC (integrates HPRD, GWAS, CTD…)• DisGeNET (a database of gene-disease associations)• Text mine PubMed directly for associations
INTRODUCTION LINEAR MODEL
Target
First-degree proteins
Second-degree proteins
3 in
tera
ctio
ns
2
inte
ract
ion
s1
inte
ract
ion
1 target
16 first-degreeproteins
downstream of MEK1/2
115 second-degreeproteins
downstream of MEK1/2
MetaCore algorithm: shortest-path (maximum number of steps: 3)
Contextualize the network: interactions specific to peripheral nerves
15 biomarker candidates
181818 CLS assay analyte
Marker(s)
LEGEND
Secreted proteins not shown
19
IndexNetwork symbol
NameNetwork object
Entrez ID
StepNumber of
interactionsBack / Up / Down
CLS assay
Integrity biomarker
Secreted protein
1 EGFR Epidermal growth factor receptor
Receptor with enzyme activity 1956 1 1 / 1 / 18 Y Genomic;
Proteomic N
2 APOE Apolipoprotien E Receptor ligand 348 2 3 / 3 / 0 YBiochemical;
Genomic; Proteomic
Y
3 B-Raf Serine/threonine-protein kinase B-raf Protein kinase 673 2 2 / 8 / 2 Y Genomic;
Proteomic N
4 APOC3 Apolipoprotein C-III Transporter 345 2 2 / 2 / 0 YBiochemical;
Genomic; Proteomic
Y
5 MMP-2 72 kDa type IV collagenase Metalloprotease 4313 2 2 / 2 / 1 Y Genomic;
Proteomic N
6 LPL Lipoprotein lipaseGeneric binding protein 4023 2 2 / 2 / 1 Y Genomic;
Proteomic N
7 IL-6 Interleukin-6 Receptor ligand 3569 2 1 / 1 / 1 Y Genomic; Proteomic Y
8 Activin Inhibin Receptor ligand 3624 2 1 / 7 / 3 Y Genomic; Proteomic Y
9 APOA4 Apolipoprotein A-IV Receptor ligand 337 2 1 / 1 / 1 Y Genomic; Proteomic Y
10 Midkine Midkine Receptor ligand 4192 2 1 / 6 / 2 N Genomic; Proteomic Y
11 GDNF Glial cell line-derived neurotrophic factor Receptor ligand 2668 2 2 / 2/ 4 N Genomic;
Proteomic Y
12 GM-CSFGranulocyte-macrophage colony-stimulating factor
Receptor ligand 1437 2 2 / 4/ 1 NBiochemical;
Genomic; Proteomic
Y
13 PCSK9 Proprotein convertase subtilisin/kexin type 9
Generic protease 255738 2 1 / 1 / 1 N Genomic;
Proteomic Y
14 Follistatin FollistatinGeneric binding protein 10468 2 1 / 1 / 1 N Genomic;
Proteomic Y
15 APOA5 Apolipoprotein A-V Transporter116519 2 1 / 1 / 1 N Genomic;
Proteomic Y
Summary
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*
****
• Top biomarker candidate is APOE • 3 interactions back to first-degree proteins
downstream of MEK1/2• CLS assay exists• APOE is secreted• Component of the initial
data set
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Example 2: Covance biomarker research project
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Alzheimer’s Neurofibrillary
Tangles Tau Fibrils
Alzheimer’s A-Beta Plaques
Parkinson’s Nigral Lewy Body
immunostain
Parkinson’s Nigral Lewy Bodies
H&E stain
Huntington’sHuntingtin Protein
Alzheimer’sCongophilic Angiopathy
Alzheimer’s Congophilic Angiopathy
Parkinson’s CorticalLewy Bodies
Protein aggregation: common theme in major neurodegenerative diseases
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Macroautophagy: a regulated mechanism for clearance of sub-cellular contents
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Macroautophagy is: • Inducible (e.g. starvation, stress response)• Clears cellular components• May be impaired in neurodegenerative diseases
How can autophagy be used therapeutically?• Inducible: a number of drugs can turn on the process
Biomarkers of autophagy:• Intracellular
(maturation of LC3)• Can we establish an
extracellular marker?• Present in CSF?
INTRODUCTION LINEAR MODEL RADIAL MODEL
IS THERE A SECRETED PROTEIN ASSOCIATED WITH AUTOPHAGY THAT CAN BE USED AS A BIOMARKER?
DrugTarget
Associated genes
2. Radial model
Autophagy-associated genes
• 60 genes/proteins in MetaCore (GO:0006914)• Auto-expand algorithm to see neighboring interactions
Process of autophagy
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How to model the question
NPC2: predicted secreted autophagy biomarker
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MetaCore algorithm: auto-expand (125); evaluate large multi-node network
Contextualize the network: interactions specific to the brain
24
2424 Secreted protein
Associated gene (seeds)
LEGEND
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Niemann-Pick Disease Type C2 (NPC2)• Component of lysosome that binds cholesterol
• Mutant forms are unable to bind lipids causingcholesterol aggregation in cells
Niemann-Pick’s disease• Leads to neurological degeneration
starting early in life
• Causes dementia (similarities with AD)
NPC2 mRNA expression levels change with drug treatments that are linked to autophagy• Is protein expressed?
• Is it secreted?
• Utility as biomarker?
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Drugs used to manipulate autophagy
Tested Drug Therapeutic Use Autophagy Action Mechanism
Yes 3-Ma Anti-cancer Inhibitor PI3K
Yes Amitriptyline (AMI) Antidepressant Inducer SNRI, PI3K
Yes Citalopram Antidepressant Inducer SSRI
Yes Loperamide Anti-diarrheal InducerBlocks Ca2+
channels
No Rapamycin* Immunosuppresssant InducermTOR receptor
proteins
Tested 4 standard compounds for autophagy
Antidepressant compounds attractive:• Induce autophagy• Penetrate the brain
Study: Increase NPC2 mRNA levels (12, 72 hrs)
We tested between 12 and 72 hrs
NPC2 protein present in media at 24 hrs
* toxic compound
INTRODUCTION LINEAR MODEL RADIAL MODEL
Neuropsychopharmacology. 2011 Jul;36(8):1754-68.
24 hour AMI treatment in vitro
0uM 1uM 10uM [AMI]
Induction
24hr NPC2 (CM)
0uM 1uM 10uM [AMI]
6h (top) or 24h (bottom) LC3 (Lys)
15kDa -
Shi
ft in
siz
ein
dica
ting
mat
urat
ion
NPC2 Signal Difference
0
20
40
60
80
100
120
140
24 hour
Treatment Length
% C
han
ge
of
Co
ntr
ol
1uM
10uM
Microtubule-associated protein light chain 3 (LC3) is widely used to monitor autophagy:
15kDa -
NPC2 protein is secreted in response to AMI-induced autophagy
20kDa -
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Eureka: AMI treatment in vivo
Control Treated
Dosed rats 24 hours and 1 hour priorto collecting samples.
NPC2 protein levels increase in rat CSF in response to AMI-induced autophagy
10ul CSF + 10ul CSF + conj. beads beads alone
IP of NPC2 from rat CSF using anti-NPC-2 conjugated DynaBeads
IP specific for NPC2 in rat CSF
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17% increase
Summary
• NPC2 may be useful as a soluble biomarker for macroautophagy
• AMI induces autophagy in human H4 neuroglioma cells• NPC2 secretion was observed in a time- and dose-
dependent manner• NPC2 can be immunoprecipitated from rat CSF• NPC2 levels increase in rat CSF in response to AMI-
induced autophagy
Next steps• Analyze protein levels of NPC2 and LC3 in brain lysate• Increase sample size for in vivo treatment
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Protocol Development: Robert Martone ** Covance Translational Biomarker Services Neuroscience Lead,
now at St. Jude Children's Research Hospital
Cell Culture: Steve Hatch
Animal Dosing: Elizabeth Eberle
Dot Blotting: Jordan Jensen
Western Blotting: Marsha Farkaly, Audra Kuebler
General Lab Techniques/Troubleshooting:Nancy Jackson, Marci Copeland, Erika Troksa
Pathway Analysis: Walter Jessen
INTRODUCTION LINEAR MODEL RADIAL MODEL
Acknowledgements: NPC2 biomarker research project
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DrugTarget
Associatedgenes
Marker(s)
From Through To
1. Identification and prioritization of PD biomarkers for aMEK inhibitor in NF1: top candidate APOE
2. Identification of a diagnostic biomarker for macroautophagy: NPC2 Drug
Target
Associated genes
INTRODUCTION LINEAR MODEL RADIAL MODEL SUMMARY
Two examples identifying and/or prioritizing candidate biomarkers based on content- and context-dependent relationships to drug targets and diseases