Tomas Radivoyevitch, PhD Assistant Professor Epidemiology and Biostatistics Case Western Reserve...
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Tomas Radivoyevitch, PhDAssistant ProfessorEpidemiology and BiostatisticsCase Western Reserve University
Email: [email protected] Website: http://epbi-radivot.cwru.edu/
Integrative Cancer Integrative Cancer BiologyBiology
Emphasis is on the stochastic component of the model.
Is there something in the black box or are the input wires disconnected from the output wires such that only thermal noise is being measured? Do we have enough data?
Model components: (Deterministic = signal) + (Stochastic = noise)
Statistics EngineeringEmphasis is on the deterministic component of the model
We already know what is in the box, since we built it. The goal is to understand it well enough to be able to control it.
Increasing amounts of data/knowledge
Times are ChangingTimes are Changing
EXPERIMENTALBIOLOGY
COMPUTERMODELING
CONTROLTHEORY
models
control lawsdata
hypotheses
proposed clinical trial
validated process model development
control system design methods development
ICB GoalsICB Goals
Ultimate Goal: individualized, state feedback based clinical trialsUltimate Goal: individualized, state feedback based clinical trials
Metabolism of Metabolism of dNTPs + AnalogsdNTPs + Analogs
Metabolism of Metabolism of DNA + Drug-DNADNA + Drug-DNA
Damage DrivenDamage Drivenor or
S-phase DrivenS-phase Driven
dNTP demand dNTP demand is eitheris either
Focus on cancers Focus on cancers caused by DNA repair caused by DNA repair system failuressystem failures
DNA repairDNA repair
SalvageSalvage
De novoDe novo
Focus on Focus on nucleoside nucleoside analogsanalogs
CASE ICBP CASE ICBP Problem StatementProblem Statement
For Example:For Example:
UDP
CDP
GDP
ADP
dTTP
dCTP
dGTP
dATP
DNA
dUMP
ATP
De Novo De Novo dNTP dNTP SynthesisSynthesis
0 2 4 6 8 10
0.0
0.1
0.2
0.3
0.4
ADP.reductase
dATP (uM)
kcat
(1/
s)
0 200 400 600
0.0
0.1
0.2
0.3
0.4
ADP.reductase
ATP (uM)
kcat
(1/
s)
0 2 4 6 8 12
0.0
0.4
0.8
ADP.reductase
dGTP (uM)kc
at (
1/s)
0 5 10 15 20
0.0
0.1
0.2
0.3
0.4
GDP.reductase
dATP (uM)
kcat
(1/
s)
0 4000 8000
0.0
0.1
0.2
0.3
0.4
GDP.reductase
ATP (uM)
kcat
(1/
s)
0 1 2 3 4 5 6
0.0
0.4
0.8
GDP.reductase
dTTP (uM)
kcat
(1/
s)
0 1000 25000.
00.
40.
8
GDP.reductase
dGTP (uM)
kcat
(1/
s)
0 1 2 3 4 5
0.0
0.1
0.2
0.3
0.4
CDP.reductase
dATP (uM)
kcat
(1/
s)
0 1000 2500
0.0
0.1
0.2
0.3
0.4
CDP.reductase
ATP (uM)
kcat
(1/
s)
0 1 2 3 4 5
0.0
0.1
0.2
0.3
0.4
UDP.reductase
dATP (uM)
kcat
(1/
s)
0 1000 2000
0.0
0.1
0.2
0.3
0.4
UDP.reductase
ATP (uM)
kcat
(1/
s)
Data from Barry Data from Barry Cooperman’s group Cooperman’s group
Enzyme Activity Enzyme Activity ProfilesProfiles
Radivoyevitch T, Kashlan OB, Cooperman BS: Radivoyevitch T, Kashlan OB, Cooperman BS: Rational Polynomial Rational Polynomial Representation of Ribonucleotide Reductase Activity.Representation of Ribonucleotide Reductase Activity. BMC Biochemistry BMC Biochemistry 2005, 2005, 6:6:8.8.
Rational Polynomial Rational Polynomial Reaction SurfaceReaction Surface
Metabolism of Metabolism of dNTPs + AnalogsdNTPs + Analogs
Metabolism of Metabolism of DNA + Drug-DNADNA + Drug-DNA
Damage DrivenDamage Drivenor or
S-phase DrivenS-phase Driven
dNTP demand dNTP demand is eitheris either
Focus on cancers Focus on cancers caused by DNA repair caused by DNA repair system failuressystem failures
DNA repairDNA repair
SalvageSalvage
De novoDe novo
Focus on Focus on nucleoside nucleoside analogsanalogs
Case ICBP Case ICBP Problem StatementProblem Statement
ICB Model-Based ICB Model-Based Approaches to Therapeutic Approaches to Therapeutic
GainGain
Direct ApproachDirect Approach– IUdR metabolism applied to MMRIUdR metabolism applied to MMR--
cancerscancers Cell death surrogateAnti-cancer input agents
Treatment failure Treatment failure risk-state-transfer Approachrisk-state-transfer Approach– TEL-AML1 patients as guides for BCR-ABL patientsTEL-AML1 patients as guides for BCR-ABL patients
Cause of cancer
Determinant of treatment failure
Anti-cancer input agents
Model contents
Risk State TransferRisk State Transfer
TT: TEL-AML1 with HR : TEL-AML1 with HR tt : TEL-AML1 with CCR : TEL-AML1 with CCR tt : other outcome : other outcome
BB: BCR-ABL with CCR: BCR-ABL with CCR bb: BCR-ABL with HR: BCR-ABL with HR bb: censored, missing, : censored, missing,
or other outcome or other outcome
B
b
b
b
b
b
b
b
bb
bb
b
b
b
b
tt t
t
t
t
t t
ttt
tt
t
t
t
t
t
t
t
t
t
tt
t
t
t
t
t
t
tt
t
t
t
t
t
t
t
t
t
tt
t
t
tt
t
t
t
t
t
tt
tt
t
T
T
T
t
t
t
t
t
tt
t
tt
tt
t
tt
t
t
t
t
0 2 4 6 8 10 12 140
20
04
00
60
08
00
10
00
12
00
DNTS Flux (uM/hr)
DN
PS
Flu
x (u
M/h
r)
Model Sharing & Use Model Sharing & Use
Systems Biology Markup Language (SBML)Systems Biology Markup Language (SBML)– A standard for representing biochemical systemsA standard for representing biochemical systems
RR– Free statistics-oriented computational environmentFree statistics-oriented computational environment
BioconductorBioconductor– R packages primarily for DNA microarray data R packages primarily for DNA microarray data
analysesanalyses SBMLRSBMLR
– An SBML-R interface and model analysis toolAn SBML-R interface and model analysis tool
SBML model definition file
SBMLR model definition file
readSBML
saveSBMLreadSBML
saveSBML
model object of class SBML in R
getModelInfo
getModelInfo
Incidencematrix
(Model sharing)
(Model using)
SimulationsaveSBMLR
readSBMLR
saveSBMLR
readSBMLR
(Model editing)
“==“,Summary
“==“,Summary
simulate
simulate
MCA
(Model testing and summary methods)
library(SBMLR);library(odesolve)curto=readSBML(file.path(.path.package("SBMLR"), "models/curto.xml")) out1=simulate(curto,seq(-20,0,1))curto$species$PRPP$ic=50out2=simulate(curto,0:70)outs=data.frame(rbind(out1,out2));attach(outs) par(mfrow=c(2,1),cex.lab=1.5)plot(time,IMP,type="l",xlab="minutes",ylab="IMP (uM)")plot(time,HX,type="l",xlab="minutes",ylab="HX (uM)")
SBMLRSBMLR
-20 0 20 40 60
10
01
05
11
01
15
minutes
IMP
(uM
)
-20 0 20 40 60
78
91
01
1
minutes
HX
(uM
)
EXPERIMENTALBIOLOGY
COMPUTERMODELING
CONTROLTHEORY
models
control lawsdata
hypotheses
proposed clinical trial
validated process model development
control system design methods development
SummarySummary
The Present The Future
AcknowledgementsAcknowledgements
Comprehensive Cancer Center of Case Comprehensive Cancer Center of Case Western Reserve University and University Western Reserve University and University Hospitals of Cleveland (P30 CA43703) Hospitals of Cleveland (P30 CA43703)
American Cancer Society (IRG-91-022-09)American Cancer Society (IRG-91-022-09) Case Integrative Cancer Biology Program Case Integrative Cancer Biology Program
(P20 CA112963-01)(P20 CA112963-01) NIH Career Development Award (1K25 NIH Career Development Award (1K25
CA104791-01A1)CA104791-01A1) Thank you Thank you