Systems biology approach suggests new miRNAs as phenotypic stability factors in the epithelial-mesenchymal transition

Abstract

The epithelial-mesenchymal transition (EMT) is a cellular programme on which epithelial cells undergo a phenotypic transition to mesenchymal ones acquiring metastatic properties such as mobility and invasion. TGF-β signalling can promote the EMT process. However, the dynamics of the concentration response of TGF-β-induced EMT is not well explained. In this work, we propose a logical model of TGF-β dose dependence of EMT in MCF10A breast cells. The model outcomes agree with experimentally observed phenotypes for the wild-type and perturbed/mutated cases. As important findings of the model, it predicts the coexistence of more than one hybrid state and that the circuit between TWIST1 and miR-129 is involved in their stabilization. Thus, miR-129 should be considered as a phenotypic stability factor. The circuit TWIST1/miR-129 associates with ZEB1-mediated circuits involving miRNAs 200, 1199, 340, and the protein GRHL2 to stabilize the hybrid state. Additionally, we found a possible new autocrine mechanism composed of the circuit involving TGF-β, miR-200, and SNAIL1 that contributes to the stabilization of the mesenchymal state. Therefore, our work can extend our comprehension of TGF-β-induced EMT in MCF10A cells to potentially improve the strategies for breast cancer treatment.

Keywords: epithelial–mesenchymal transition; miRNAs; modelling.

Figure 1.

Proposed regulatory network of TGF-β-driven EMT. Elliptic and rectangular nodes represent multi-valued and Boolean components, respectively. Nodes in grey and white denote the input (Ex_TGFB) and the output (EMT) of the network, respectively. Epithelial markers in the network are represented by blue, while mesenchymal markers are in yellow. Green arrows represent activatory interactions and hammer-head arcs denote inhibitory ones. The rectangular node in purple represents hyaluronic acid (HA). This figure was generated using GINsim 3.0.0b.

Figure 2.

Wild-type results of the model. Each line represents a steady state of the model. Yellow, orange, and red cells represent inactive, intermediate, and active states of the components, respectively. White, light green, green, dark green, and very dark green denote levels of the input Ex_TGFB corresponding to absence, low, intermediate, high, and very high concentration, respectively. The model phenotypes are interpreted according to the output state (EMT): inactive, intermediate, and high values of the EMT node represent epithelial (dark blue), hybrid (half coloured cells) and mesenchimal (dark yellow) phenotypes, respectively.

Figure 3.

Analysis of lower input active level. In HTG, most-left states represent initial states of the simulation, whereas most-right ones denote final states. Arrows representing transitions between the states are labelled with the updated components. Plus and minus signs indicate that the component is increasing or decreasing its activity level, respectively. Blue and yellow transient states denote that incoming transitions are related to E and M phenotypes, respectively. The number of states that compose each transient is shown. (a) We observed that the unperturbed SNAIL1 circuit generated trajectories where the final state was only the E state. The HTG shows that SNAIL1 transient oscillations can also contribute to stabilize the E state. The depicted 16 states show that the system can oscillate between E and H states until it finally remains at the E state. (b) LoF of SNAIL1 self-inhibition triggers the transition to the H state destabilizing the E state.

Figure 4.

Perturbation analysis of TWIST1/miR-129 circuit for intermediate level with active input. Dark red, red, orange and yellow colours denote the model component levels highest, high, intermediary and inactivation, respectively. (a) LoF of the interactions which compose the TWIST1/miR-129 circuit. The results show the loss of the H state with the absence of TWIST1. (b) The perturbations of the TWIST1/miR-129 circuit show that the bistable switches TWIST1 OFF/miR-200 ON and TWIST1 ON/miR-129 OFF control the bistability between the H states found in figure 2 for the intermediate level of Ex_TGFB. (c) LoF of miR-200, miR-1199, GRHL2, and miR-340 destabilize the H state in the presence of activated TWIST1. (d) Under Ex_TGFB OFF and using H as the initial state with activated miR-129, the system transits to the E state, whereas using the H state with activated TWIST1 the system does not transit to the E state.

Figure 5.

Perturbation analysis of TGFB/SNAIL1/miR-200 circuit with off input. The colours yellow, orange, and red denote the model component levels: off, intermediary, and high, respectively. (a) LoF of the circuit interactions leads to the loss of stability of the M state. (b) According to the network, TGFB can only be activated through ZEB1 activation that, in turn, inhibits miR-200 and miR-190, inducing the circuit functionality. Once TGFB is activated, it sustains the ZEB1 activation via SNAIL1 inducing the M state even with Ex_TGFB OFF.

Figure 6.

Stepwise process of the model dynamics via activation of multiple circuits. HTGs are displayed as in figure 3. The simulations were performed for $E{x}_{\mathrm{TGFB}}=2$. (a) The initial state E (considering active SNAIL1) induces a bistability between the E and H (with the presence of miR-129) states. (b) Subsequently, the initial state H (considering active TWIST1) triggers another bistability between the H states. (c) Considering the H state with the presence of TWIST1 and additional activation of ZEB1 as the initial condition, the simulation showed another multistability between H and M states. (d) Up and down arrows represent up and downregulation, respectively. Yellow and blue colours denote E and M markers. The induction of SNAIL1/miR-34 circuit by Ex_TGFB triggers bistable switches that control the transition E to H. The activation of SNAIL1 induces the functionality of TWIST1/miR-129 circuit. The switch TWIST1 OFF/miR-129 ON stabilizes one of the H states, whereas its counterpart (TWIST1 ON/miR-129 OFF) triggers the transition to another H state which is stable due to miR-200-miR-1199-GRHL2-miR-340-ZEB1 circuits. Active TWIST1 can induce ZEB1 and subsequently inactivate miR-200, GRHL2, miR-1199 and miR-340 and inducing the transition to the M state which is sustained by TGFB/miR-200/SNAIL1, ESRP1/CD44s/ZEB1 and HAS2/HA/ZEB1 circuits.

Figure 7.

Schematic comparison between model and experimental observations. (a) The high level of Ex_TGFB induces a transition from the E to the H state with activated miR-129. (b) The very high level of Ex_TGFB induces a direct transition from the E to the M state. (c) The model reproduces the experimental approach by Zhang et al. [8] where epithelial cells are treated with concentrations of 0.5, 1 and 2 ng/ml of exogenous TGF-β. Following the treatment, the stable phenotypes agree with the stable states found in the model dynamics. The disagreement related to the lower level of Ex_TGFB is explained in the Discussion of the paper.