Additional file 1: Figure S1a. of Gastrin activates autophagy and increases migration and survival of gastric adenocarcinoma cells

Expression of CCKBR in gastric adenocarcinoma cells. AGS cells have low abundance of the CCKBR, MKN45 express the CCKBR endogenously and AGS-Gr cells are stably transfected with the CCKBR. S1b. Negative control images of the MKN45 cells stained for the CCKBR (phase contrast, Alexa 488, Draq5). Figure S2: Gastrin induces autophagy. AGS-Gr (a & b) cells treated with gastrin (10 nM), BafA1 (100 nM) and gastrin + BafA1 for 2 and 4 h. Protein expression of MAP1LC3B-II and SQSTM1 was analyzed by immunoblotting. The images shown represent one of three independent experiments. Graphs show mean +/- SEM (P- values: *** ≤ 0.01 **≤ 0.02, and * ≤ 0.05). Figure S3: Negative controls (primary antibodies omitted) for MAP1LC3B (Alexa 488) and SQSTM1 (Alexa 647). Figure S4: Gastrin mediated survival is dependent on autophagy. (a): A representative cytometric plots showing AGS-Gr cells treated with BafA1 and gastrin for 18 h. Cell viability was assessed using annexin V-PI staining and flow cytometric analyses. Blocking autophagy reduces gastrin mediated survival in AGS-Gr cells. (b): Cell viability assessed in AGS-Gr cells treated with gastrin (10 nM) for 6- 72 h. (c & d): Cells treated with gastrin (2 h) and subsequently treated with increasing concentrations of cisplatin. Viability was assessed at 24 and 72 h. Results show mean +/-SD (n=3, P-values: * ≤ 0.05 ** ≤ 0.01 *** ≤ 0.001). (e): AGS-Gr cells treated with HCQ for 8 h. Protein expression of MAP1LC3B-II and SQSTM1 was detected by immunoblotting. (f) Gastrin induced autophagy is dependent on ULK1: AGS-Gr cells treated with gastrin, BafA1 and ULK1 inhibitor SBI-0206965 (10 μM) for 4 h. Protein expression of MAP1LC3B-II and SQSTM1 was detected by immunoblotting. The immunoblots represent one of three independent experiments. Figure S5: Inhibition of gastrin induced autophagy by Comp C. AGS-Gr cells pretreated with Compound C (10 μM) for 12 h before adding BafA1 and gastrin (4 h). Protein expression of SQSTM1 is shown by immunoblotting. The blot represents one of two independent experiments. (DOCX 2504 kb

Prior knowledge network representing the cell fate decision network governing growth of AGS gastric adenocarcinoma cells.

<p>The network receives no external input but encompasses two outputs <i>Antisurvival</i> and <i>Prosurvival</i> (phenotypic readouts, colored in red for Antisurvival and green for Prosurvival). Activating regulations are denoted by green arrows, while red T arrows denote inhibition. Signaling component nodes (proteins, protein complexes or genes) associated with Boolean variables (taking the values 0, 1) are represented by ellipses, while rectangles depict nodes encoded with multilevel variables. Yellow nodes represent drug targets and are subjected to inhibitory perturbations during simulations.</p

Workflow of model construction and synergy prediction followed by experimental validation.

<p>We started with a signaling network built from general database and literature knowledge (upper left), which was refined with published experimental data on protein activities in AGS cells (upper right) to generate the logical model. Next, we generated a formally reduced version of the logical model, focusing on the drug target nodes and valid for systematic simulations of combinatorial inhibitions. Predicted synergies were challenged with observations from AGS cell growth experiments. Cartoons on the right refer to each of the Figs <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004426#pcbi.1004426.g002" target="_blank">2</a>–<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004426#pcbi.1004426.g005" target="_blank">5</a> further down.</p

Effects of combined inhibitors on cell growth.

<p>Synergistic (yellow) and non-synergistic (blue) combinations are shown both as predicted by model simulations (upper panel of boxes, value of model parameter “growth”) and as verified by cell growth experiments (lower panel of boxes; combinatorial indexes (synergy indicated by CI < 1) or “n” when non-synergy was observed).Synergy was proposed whenever the predicted growth for a combination of inhibitors was lower than the modeled effect of single drug perturbations, shown in the outer diagonal (grey, value of model parameter “growth”).</p

Reduced logical model obtained by semi-automated reduction of the comprehensive logical model shown in Fig 2.

<p>The reduced model encompasses all seven drug targets (yellow) and the two phenotypic outputs (red for Antisurvival and green for Prosurvival). In addition the ERK node (blue) had to be preserved to maintain dynamical consistency with the large model. Activating regulations are denoted by green arrows, while red T arrows denote inhibition. The blue arc with both arrow and T head (p38alpha to Antisurvival) indicates a dual regulation, i.e. activating and inhibiting, depending on context. In some contexts p38alpha inhibition will increase Antisurvival, while in others p38alpha inhibition will decrease Antisurvival (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004426#pcbi.1004426.s001" target="_blank">S1 Text</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004426#pcbi.1004426.s011" target="_blank">S7</a> and <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004426#pcbi.1004426.s012" target="_blank">S8</a> Tables). Note that after model reduction two members of the Wnt/β-catenin pathway, β-catenin and GSK3, became non-regulated and fixed at either the on-state (β-catenin) or off-state (GSK3).</p

Chemical inhibitors and their corresponding protein kinase targets.

<p>Chemical inhibitors and their corresponding protein kinase targets.</p

Experimentally confirmed synergies, where the effect of combining two inhibitors at half GI50 concentrations (violet) outperforms each of the single inhibitor at the full GI50 concentration.

<p>A) AKT inhibitor (green) and TAK1 inhibitor (blue). B) MEK inhibitor (blue) and AKT inhibitor (green). C) MEK inhibitor (green) and PI3K inhibitor (blue). D) PI3K inhibitor (green) and TAK1 inhibitor (blue). Cells growing in the absence of inhibitors are shown in red. One standard deviation is indicated by error bars. Inhibitors (and concentrations) used: MEK inhibitor PD0325901 (35 nM), TAK1 inhibitor (5Z)-7-oxozeaenol (0.5 μM), PI3K inhibitor PI103 (0.7 μM) and AKT inhibitor AKTi-1,2 (10 μM). See <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004426#sec011" target="_blank">Materials and Methods</a> and <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004426#pcbi.1004426.s001" target="_blank">S1 Text</a> for all growth curves of combinations of inhibitors, and dose-response curves of individual inhibitors.</p

SIK1 inhibits migration in AGS-G_R cells via suppression of MMP-9.

<p><b>A–B:</b> AGS-G_R cells (<b>A</b>) and MKN45 cells (<b>B</b>) were treated with gastrin, and phospho-LKB1 (Ser-428) protein levels determined by Western blot. The phospho-LKB1 bands from a representative experiment are shown. <b>C–D:</b> AGS-G_R cells (<b>C</b>) and MKN45 (<b>D</b>) were treated with gastrin, and phospho-SIK1 (Thr-182) protein levels determined by Western blot. The phospho-SIK1 bands from a representative experiment are shown. <b>E:</b> AGS-G_R cells transfected with siSIK1 or siCtr and real-time cell migration monitored (0–24 h). Results show one representative of three independent experiments (mean ±SD of three technical replicates). <b>F:</b> MMP-9 mRNA expression in cells transfected with pSIK1 and treated with gastrin. Results show one representative of three independent experiments, (mean ± SD).</p

ICER represses the level of <i>SIK1</i> mRNA and protein.

<p><b>A:</b> AGS-G_R cells were treated with gastrin and mRNA levels of ICER measured by qRT-PCR. Results shown are mean ± SEM of three independent biological experiments. <b>B:</b> AGS-G_R cells were transfected with ICER I, ICER IIγ or control expression plasmids, treated with gastrin (1 h) and mRNA levels of SIK1 measured by qRT-PCR. Results show one representative of three independent experiments; mean ± SD of three technical replicates. <b>C:</b> AGS-G_R cells were transfected with siRNAs, treated with gastrin and mRNA levels measured by qRT-PCR. Results show one representative of three independent experiments; mean ± SD of three technical replicates. <b>D:</b> SIK1 Western blot in cells transfected with siICER. A representative image is shown and quantified.</p

Gastrin-induced activation of SIK1.

<p><b>A:</b> AR42J cells were treated with gastrin and mRNA levels measured by qRT-PCR. Mean expression level relative to untreated cells is shown. Results show one representative of three independent biological experiments; mean ± SD of three technical replicates. <b>B:</b> SIK1 Western blot of gastrin treated AR42J cells. A representative image is shown and quantified <b>C:</b> AGS-G_R cells were treated with gastrin and mRNA levels measured by qRT-PCR. Mean ± SEM of three independent biological experiments is shown. <b>D:</b> SIK1 Western blot of gastrin treated AGS-G_R cells. A representative image is shown and the SIK1 bands from two independent experiments were quantified; results shown are mean intensities ±SD. <b>E:</b> SIK1 Western blot of gastrin treated MKN45 cells. The SIK1 bands from a representative experiment were quantified. <b>F:</b> Intracellular localization of endogenous CRTC2 protein (Red; CRTC2, blue; Draq-5-stained DNA). G: Intracellular localization of SIK1 protein. AGS-G_R cells transfected with pEGFP-SIK1.</p