Title: Modelling Cancer Growth
1Modelling Cancer Growth
- Philip K. Maini, Centre for Mathematical Biology,
Mathematical Institute, Oxford -
2mutations
Approx 1mm in diameter
3- Nutrient required
- Hypoxic core TAF (tumour
angiogenesis factors) - Avascular tumour Vascular tumour
- Invasion
- Tumour produces proteases digest ECM
- Competition
- Normal environment
Tumour
Normals
Add H
Gatenby Gawlinski Gap
4Acellular gap at the tumor-host interface in head
and neck cancer
5Hepatocytes
Metastatic tumor
6Tomas Alarcón (UCL)Helen Byrne (Nottingham)EU
RTN (5th Framework) Using mathematical
modelling and computer simulation to improve
cancer therapyAlarcón, Byrne, Maini, J.
Theor. Biol, 225, 257-274 (2003)
Prog. Biophys Mol. Biol., 85,
451-472 (2004)
J. Theor. Biol, 229, 395-411 (2004)
SIAM Multiscale Mod Sim.3,
440-475 (2005) Ribba, Marron, Agur, Alarcon,
Maini Bull. Math. Biol., 67 79-99 (2005)
7Cancer Growth
- Tissue Level Signalling (Tumour Angiogenesis
Factors) - Oxygen etc
- Cells
- Intracellular Cell cycle,
- Molecular elements
Partial Differential Equations
Automaton Elements
Ordinary differential equations
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12Tumour Growth
- First, work out distribution of 02 (nutrient)
- To do so, must consider vasculature metabolic
response - R radius
- flow rate
- H haematocrit
- Tw WSS
- P pressure (transmural)
- Haematocrit Pries et al,
1994 - At a bifurcation
-
-
Response to mechanical stimuli
Shrinkage (Pries et al 1988)
(rat mesentry)
(Fung 1993)
13Algorithm for structural adaptation
- Prescribed
- 2. Given initial network configuration, compute
flow rates - through and pressure drops across each vessel
using Kirchoffs - law.
- 3. Compute distribution of haematocrit.
- 4. Update radius of each vessel.
- 5. Compute viscosities (using H and R from 3 and
- 4 respectively).
- 6. Repeat until steady state reached.
Flow rate
14____________ O2 distribution____________
(adiabatic approx)
PO2 conc
?N for normal cell
?c for cancer cell
0 o.w
Nw normal to vessel wall
?b ?2 level in blood
P permeability
(at edge of domain, no flux
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16Automaton Rules
- 1. ?2 distribution determined by BVP.
- 2. Cells attempt to divide at each time step.
- 3. Normal cell if ?2lt threshold, cell dies
- ?2 gt threshold, cell
attempts to divide - Threshold ?1 if more normal than cancer
neighbours - ?T2 if more cancer than normal
neighbours - ?T2gt ?T1
- 4. Cancer cell if ?2gt threshold, cell attempts
to divide - Threshold ?T1 if more cancer than normal
neighbours - ?T2 if more normal than cancer
neighbours - ? T2 gt ?T1
175. Cancer cell if O2lt threshold
cell becomes
quiescent If it
remains quiescent for a certain length of time,
it dies.
6. Cells are sinks of O2 7. If O2 level is
such that a cell may divide, sample neighbourhood
for space. If more than one available space,
go to the one with largest O2 (Patel et al 2001).
If no space, die (Kansal et al, 2000)
18Cell Dynamics
- NxN automaton elements.
- State vector has 3 components
- Occupation normal cell/cancer cell/vessel/empty
- Cell status proliferative/quiescent
- Local ?2 conc
- We assume, for simplicity, vessel structures does
not evolve.
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23Conclusion
- Environmental heterogeneity decreases cancer cell
growth but may contribute to metastasis
24Possible application
- Doxorubicin treatment of non-Hodgkins lymphoma
(Ben Ribba, Zvia Agur, Tomas Alarcon, Philip
Maini, K Marron) - Structural adaptation vessels surrounded
- by NHL
leaky unstable - Nutrient diffusion
- -Drug pharmacokinetics in plasma
- pharmacodynamics kills proliferating
cells - tissue dynamics (adiabatic approx)
- AIM Explore different protocols of treatment
- (presently a 21-day cycle is employed)
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32Cancer-Proliferation
33Cell-Cycle Dynamics
- Why?
- nutrient demand
- hypoxia-induced quiescence
- drugs work only on cells in a certain part of
- their cell cycle.
- Cell Cycle
- Cyclin-dependent kinases (CDK)
- cyclins
-
- In G1 CDK activity is low because its
cyclin partners -
are missing - At finish Cdhl (and Cdc 20) concs are high
- degrade
cyclins.
2 families of proteins
34schematic
35Tyson Novak
- Model for G1/S transition
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39E2F transcription factor Take Tyson and Novak
modelincorporate inhibition by a Kz term
P27 conc in Cdhl
oxygen
Normals
Growth regulation
hypoxia
as m z
Cancer Cells
Hypothesis growth regulation
is lost
40Results
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46- Simulations show decrease in Cdk
- This is observed experimentally
47Growth regulation of p27?
Normals ?
- Growth factors p27
- If growth is arrested, p27 is upregulated
Cancer x
48Response to hypoxia (low O2)Expts on mouse
embryo fibroblasts
hypoxiaNormal cells G1
arrest Does not occur with p27 null mutants
49CONCLUSION
- x heterogeneities have a profound effect
- on tumour dynamics
- x effects of p27 possible mechanism
- x efficiency of drug treatments
- Future Directions
- VEGF
- HIF-1
- Elasticity
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51Role of Acidity
- Kieran Smallbone, David Gavaghan, Bob Gatenby, PKM
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53 T-tumour density V-vascular density
Glycolytic pathway
Blood flow removal
Avascular Case
elsewhere
Nondimensionalise
Necrotic core
Proliferation zone, T const
Outside tumour
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55Assume necrosis arises when
constantUsing experimentally
determined parameter values
necrotic core arises at
r 0.1 cm avascular case
56Vascular Case
elsewhere
57Tumour Growth No normal tissue
Avascular tumour always reaches a benign
steady stateVascular tumour is benign if
invasive if
(cf Greenspan 1972)
necrotic core
Proliferation
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59 Include normal tissue Normal cells die if
So, tumour will only advance if
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61Results
- Three regimes of growth
- If rate of acid removal is insufficient,
- exponential growth followed by auto-toxicity
- benign tumour
- Occurs in avasculars and vasculars if
- vascular tumour displays
sustained growth and invades - Very small tumour no growth (insufficient acid
production to include normal cell death)
62Experimental results (Gatenby)
63PH profiles in 6 directions
64Acid moves in direction of arrows
65Therapies
- Kill tumour cells or cut them out
- Anti-angiogenesis drugs drug delivery
- Treat normals?
66Therapies?
- Reduce vasculature in tumour
- tumour poisons itself
- Destroy membrane pumps transporting H ions from
tumour - Increase acidity!
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