Upload
others
View
0
Download
0
Embed Size (px)
Citation preview
Computa(onal modelling of the regula(on of cell adhesion, a cri(cal step of EMT
• The current model predicts a role of signals from neighbouring cells (RPTP, FAT4 and DELTA), which
would now need to be explored experimentally. • SystemaEc analyses of single, double and triple perturbaEons on model components may generate
further testable predicEons. • Model will be extended to encompass cell populaEon dynamics to further invesEgate the role of the
microenvironment in the control of cell adhesion (use of EpiLog, a tool for the logical modelling of 2D grids of cells, hIp://epilog-‐tool.org).
Ricardo J. Pais, Claudine Chaouiya {rpais,chaouiya}@igc.gulbenkian.pt
Ins$tuto Gulbenkian de Ciência, Oeiras, Portugal
1. Savagner P. Curr Top Dev Biol. 112, 273–300 (2015). 2. Lamouille, S. et al. Nat. Rev. Mol. Cell Biol. 15, 178–96 (2014). 3. Farahani, E. et al. Carcinogenesis 35, 747–59 (2014). 4. Kawauchi T. Int. J. Mol. Sci. 13, 4564–4590 (2012). 5. Krakhmal N. V. et al. & Acta Naturae 7(2), 17–28 (2015). 6. Chaouiya, C. et al. Methods Mol. Biol. 808, 463–79 (2012). 7. Mendes, N. et al. arXiv:1411.3539 (2014).
This work was supported by the Fundação para a Ciência e Tecnologia (FCT grant PTDC/BEX-‐BCB/0772/2014). RP is funded by the FCT (grant SFRH/BD/52175/2013). CC is funded by the Fundação Calouste Gulbenkian. RP and CC further thank F. Janody and J. Carneiro for fruieul discussions.
Changes in cell adhesion properEes have been associated to Epithelial to Mesenchymal TransiEon (EMT)1-‐3. During EMT, epithelial cells lose the E-‐cadherin mediated cell-‐cell adhesion, increase cell–matrix (focal) adhesion and convert into mesenchymal cells with migratory capacity2,3. This process is thought to contribute for cancer invasion2,3. However, intermediate phenotypes with different adhesive properEes have been found in invasive cancers4,5. MulEple micro-‐environmental cues, signalling pathways and regulatory modules with crosstalk points and feedbacks regulate the cell adhesion status2-‐4. To understand how cell adhesion is governed, we use on a computaEonal modelling approach, building a logical model of the involved network under the control of relevant micro-‐environmental cues. Here, we present our modelling approach and some preliminary results of the model analysis.
Phenotypes depend on micro-‐environment; These plots provide the percentages of stable states corresponding to specific phenotypes, for different combinaEons of cell-‐cell contact signals and for wild-‐type and perturbed condiEons (alteraEons documented in tumour cells). The effect of cell-‐cell contact signals (RPTP and FAT4 ligands) is shown.
Cell-‐matrix adhesion (Boolean)
FOCAL_ADHESION = 1 IF ITGab & F-‐acEn_FA & !E-‐Cad:2 (high) 0 otherwise ( low)
,,,,
Challenging the model by comparing the phenotypes (stable states) reached from an epithelial state, with experimental observaEons on adhesive properEes and molecular alteraEons in mammalian epithelial cell lines exposed to various micro-‐environments or mutaEons.
HGF=1
Wnt=1
StarEng state
Published experimental data on epithelial cell lines
EGF addiEon collagen type I addiEon
EGF + collagen type I addiEon
HGF addiEon
Wnt addiEon
TGFb addiEon
KO of 120
b-‐Catenin/E-‐cadherin mutaEon
CK1 overexpression
CD44 overexpression
SRC overexpression
SimulaEons
Multi-valued Boolean
AcEvaEon
Slower processes
Dual
Inpu
t con
diEo
ns or p
erturbaE
ons (Fixed compo
nents)
EGF=1
ECM=1
ECM=1 & EGF=1
TGFb=1
p120=0
b-‐Cat_m=0
CK1=1
CD44=1
SRC=1
INTRODUCTION
LOGICAL MODELLING Discrete variables
CDH1 0 InacEve E-‐cadherin transcripEon 1 AcEve E-‐cadherin transcripEon
E-‐Cad << 0 Absence of E-‐cadherin protein 1 Low funcEonal E-‐cadherin 2 High funcEonal E-‐cadherin
Example: regulaEon of E-‐cadherin/catenins complex
Regulatory graph
Asynchronous vs priority classes (to discard irrelevant trajectories) Fast (1st class): processes occurring in a Eme scale of seconds Slow (2nd class): processes occurring in a Eme scale of minutes
Upda(ng scheme
Logical func(ons (Logical operators & (AND), | (OR), ! (NOT)) E-‐Cad = 2 if CDH1 & p120 & Rap1 E-‐Cad = 1 if CDH1 & Rap1 & !p120 E-‐Cad = 0 otherwise
CDH1 = 1 if !ZEB & ! SNAIL CDH1 = 0 otherwise
A logical model is defined by a regulatory graph, discrete variables associated to the nodes and logical func(ons defining the evoluEon of these variables6. Discrete dynamics are constructed following an updaEng scheme, e.g. the asynchronous dynamics includes all concurrent transiEons. ProperEes of interest relate to aXractors and their reachability proper(es. These are checked on State TransiEon Graph (STG) represenEng the states and trajectories.
hIp://ginsim.org
AB
STR
AC
TION
Model
Biological process
CELL ADHESION REGULATORY NETWORK
MODEL VALIDATION
References
Switching phenotypes upon changes of signals from neighbouring cells (RPTPL, FAT4 and DELTA), remaining inputs maintained constant, reflecEng a prototypic “tumoral” microenvironment (IL6 =1 Hypoxia=1 ECM=1 HGF=1 EGF=0). SimulaEons performed in GINsim under asynchronous update. Reachability probabiliEes in the case of mulE-‐stability were obtained by running 10 000 random simulaEons.
RPTP = 1
RPTP=FAT4=0 RPTP=0 & FAT4=1
RPTP=1
Wild-‐Type RPTP=0 & FAT4=1
RPTP=FAT4=0
DELTA=1
RPTP = 1 & DELTA=0
RPTP=FAT4=0 & DELTA=0 RPTP=DELTA=0 & FAT4=1
TGFb E1
RPTP=1 & DELTA=0
DELTA=1
p=0.7
p=0.3
Acknowledgements CONCLUSION / PROSPECTS
MODEL PREDICTIONS
Model outputs (readouts)
Cell-Cell Adhesion 0 No cell-‐cell adhesion 1 Low cell-‐cell adhesion 2 High cell-‐cell adhesion
0 Normal cell-‐ECM adhesion 1 Increased cell-‐ECM adhesion 2 Enhanced cell-‐ECM adhesion
Focal Adhesion Inputs (micro-‐environment)
Membrane protein
InhibiEon
Signalling cascade TranscripEon Factor Gene/RNA
Autocrine signal
The model includes 51 components and 121 interacEons. Growth factors (HGF and EGF), interleukin 6, hypoxia, ECM sEffness and signals from adjacent cells (DELTA, RPTP and FAT4 ligands) are input components (micro-‐environmental cues). The output components indicate the degrees of cell-‐to-‐cell and cell-‐matrix adhesion (readouts).
Focal Adhesion
Cell-‐Ce
ll Ad
hesio
n
MigraEon potenEal
MigraEon potenEal
Wild type stable states (unperturbed model), recapitulaEng cel l phenotypes with the corresponding values of internal components
Epithelial-like
Amoeboid-like Mesenchymal-like
Hybrid
Mesenchymal markers Epithelial markers
0
Cell phenotypes given by the model outputs
RPTP = 0 & FAT4 = 0
Distrib
uEon
of SS/ph
enotype
12 16
48
16 16
112
32
12
36
1 2
0 1
2
Images from ref 4
RPTP = 1 & FAT4 = * RPTP = 0 & FAT4 =1