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Unformatted text preview: Effect of pore size on vascularization 58 Effect of pore size on vascularization 59 Effect of pore size on vascularization 60 Model predictions vs. experimental results 61 Summary • Computational model of vascularization in polymer
scaffolds • The model predicts the effect of pore size on vessel
growth •
• Model predictions match in vivo experimental data • The model can be applied to examine strategies to
accelerate vascularization Illustrates clinical barrier of vascularizing engineered
constructs 62 Case study: VEGF pathway in tumor angiogenesis 63 VEGF family: target for cancer therapy
Vascular Endothelial Growth Factor (VEGF) •
•
•
•
•
•
• Potent regulator of angiogenesis
Acts in response to many stimuli, including hypoxia
Stimulates
cell proliferation,
migration, and
survival Targeted in cancer
therapies •
drawing by Florence Wu VEGF family: target for cancer therapy adapted from Kut et al., Br J Cancer, 2007 65 VEGF family: prime for systems biology modeling VEGFB167
VEGFB186
VEGFB
PlGF1
PlGF
PlGF2 VEGFA>121
PlGF2
VEGFB186 VEGFA121
VEGFA145
VEGFA165
VEGFA189
VEGFA
VEGFA209 VEGFA165 VEGFA145
VEGFB167 VEGFA165
VEGFC VEGFB186 VEGFC
VEGFD
PlGF2
PlGF2 GAG s1 11 22 33 N
N
1
2
Neuropilins VEGF receptors
Objective: to develop a moleculardetailed computational model of VEGF
and predict the effect of therapeutics that target the VEGF pathway Methods: Multiscale wholebody compartment model
TUMOR Tumor Cells Interstitial
space
Abluminal endothelium Permeability BLOOD Luminal endothelium Plasma Clearance Luminal endothelium NORMAL Abluminal endothelium Stefanini et al., 2008; Stefanini et al., 2010; Finley et al., 2011 Lymph
flow Interstitial
space
Muscle Fibers 67 Methods: VEGFVEGFR molecular interactions
121 121 121 121 121 121 121 165 + + + + + + + + + +
N 11 121 11 N 11 11 11 N N N 11 N 11 11 121 121 121 + + N +
N N 11 165 165 165 165 + + + N + 22 121 22 165 165 22 N 165 + +
N N 22 165 + 22 165 22 N + +
11 + +
11 N N 11 11 11 N +
N N 22 165 11 N 165
11 121 121 α2macroglobulin 11 121
165 165 + N 165 + 165 + A 121 A 165 + 11 + GAG 165 165 +
N N 11 A 165 A Model predicts the concentrations
of all molecular species in each compartment 11 Methods: Model equations and numerical methods
System is described by 154 ordinary differential equations
d [V165 ]N
N
= qV 165 − koN ,V 165,MEBM [V165 ]N [ M EBM ]N + koNf ,V 165,MEBM [V165 M EBM ]N
n
f
dt
− koN ,V 165,MPBM [V165 ]N [ M PBM ]N + koNf ,V 165,MPBM [V165 M PBM ]N
n
f
− koN ,V 165,MECM [V165 ]N [ M ECM ]N + koNf ,V 165,MECM [V165 M ECM ]N
n
f
−k [V165 ]N [ R1 ]N + k N
on ,V 165, R1 N
off ,V 165 R1 [V165 R1 ]N − koN ,V 165,R 2 [V165 ]N [ R2 ]N + koNf ,V 165 R 2 [V165 R2 ]N
n
f
− koN ,V 165,N 1[V165 ]N [ N1 ]N + koNf ,V 164 N 1[V165 N1 ]N
n
f
my
− koN ,,V 1o5,N 1[V165 ]N [ N1 ]N ,myo + koNf,my1o65 N 1[V165 N1 ]N ,myo
n6
f ,V − koN ,V 165, A [V165 ]N [ A]N + koNf ,V 165 A [V165 A]N
n
f
⎛ k L + k S NB ⎞ [V ]
U
BN S
165 N
−⎜
+ k pV NB B [V165 ]B − kdeg [V165 ]N
⎟
UN
UN UP
⎝
⎠ K AV ,N
NB
pV Secretion
Binding
Lymphatics
Permeability
Degradation
Clearance
Insertion
Internalization
69 Methods: Model parameters
• Parameters governing molecular interactions based on
experimental data • Receptor density is based on in vitro and in vivo data • Secretion ratio of VEGF165:VEGF121 is from published literature
• 92:8 for muscle ﬁbers
• 90:10 for endothelial cells
• 50:50 for tumor cells • VEGFneutralizing agents are:
• Bevacizumab (Avastin, Genentech)
• Aﬂibercept (VEGF Trap, Regeneron)
121 + 165 + A A 121 165 A A Block Formation of
VEGF/VEGFR
Complexes 70 Model...
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This note was uploaded on 01/20/2014 for the course BME 410 taught by Professor Han during the Spring '08 term at USC.
 Spring '08
 Han
 Biomedical Engineering

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