Mechanistically detailed systems biology modeling of the HGF/Met pathway in hepatocellular carcinoma

Combining Multikinase Tyrosine Kinase Inhibitors Targeting the Vascular Endothelial Growth Factor and Cluster of Differentiation 47 Signaling Pathways Is Predicted to Increase the Efficacy of Antiangiogenic Combination Therapies

Angiogenesis is a critical step in tumor growth, development, and invasion. Nascent tumor cells secrete vascular endothelial growth factor (VEGF) that significantly remodels the tumor microenvironment through interaction with multiple receptors on vascular endothelial cells, including type 2 VEGF receptor (VEGFR2). The complex pathways initiated by VEGF binding to VEGFR2 lead to enhanced proliferation, survival, and motility of vascular endothelial cells and formation of a new vascular network, enabling tumor growth. Antiangiogenic therapies that inhibit VEGF signaling pathways were among the first drugs that targeted stroma rather than tumor cells. Despite improvements in progression-free survival and higher response rates relative to chemotherapy in some types of solid tumors, the impact on overall survival (OS) has been limited, with the majority of tumors eventually relapsing due to resistance or activation of alternate angiogenic pathways. Here, we developed a molecularly detailed computational model of endothelial cell signaling and angiogenesis-driven tumor growth to investigate combination therapies targeting different nodes of the endothelial VEGF/VEGFR2 signaling pathway. Simulations predicted a strong threshold-like behavior in extracellular signal-regulated kinases 1/2 (ERK1/2) activation relative to phosphorylated VEGFR2 levels, as continuous inhibition of at least 95% of receptors was necessary to abrogate phosphorylated ERK1/2 (pERK1/2). Combinations with mitogen-activated protein kinase/ERK kinase (MEK) and spingosine-1-phosphate inhibitors were found to be effective in overcoming the ERK1/2 activation threshold and abolishing activation of the pathway. Modeling results also identified a mechanism of resistance whereby tumor cells could reduce pERK1/2 sensitivity to inhibitors of VEGFR2 by upregulation of Raf, MEK, and sphingosine kinase 1 (SphK1), thus highlighting the need for deeper investigation of the dynamics of the crosstalk between VEGFR2 and SphK1 pathways. Inhibition of VEGFR2 phosphorylation was found to be more effective at blocking protein kinase B, also known as AKT, activation; however, to effectively abolish AKT activation, simulations identified Axl autophosphorylation or the Src kinase domain as potent targets. Simulations also supported activating cluster of differentiation 47 (CD47) on endothelial cells as an effective combination partner with tyrosine kinase inhibitors to inhibit angiogenesis signaling and tumor growth. Virtual patient simulations supported the effectiveness of CD47 agonism in combination with inhibitors of VEGFR2 and SphK1 pathways. Overall, the rule-based system model developed here provides new insights, generates novel hypothesis, and makes predictions regarding combinations that may enhance the OS with currently approved antiangiogenic therapies.

New targeted and epigenetic therapeutic strategies for the treatment of uveal melanoma

Uveal melanoma (UM) is a rare, genetically bland ocular malignancy with excellent local treatment options, but no disease-specific therapies are approved for use in the metastatic setting by the Food and Drug Administration. Metastatic UM (mUM) confers a prognosis of ~15 months. Unlike cutaneous melanoma, UM is poorly responsive to checkpoint inhibitors and cytotoxic chemotherapy highlighting the importance of clarifying vulnerable disease-specific mechanisms, such as cell cycle or metabolic pathways necessary for tumor growth and survival. The elucidation of signaling pathways downstream of the frequently mutated GNA GTPase such as PKC/MAPK/ERK/MEK, PI3K/AKT, and YAP-Hippo have offered potential targets. Potentially druggable epigenetic targets due to BAP1-mutated UM have also been identified, including proteins involved with histone deacetylation and DNA splicing. This review describes the preclinical rationale for the development of targeted therapies and current strategies currently being studied in clinical trials or will be in the near future.

Core cysteine residues in the Plasminogen-Apple-Nematode (PAN) domain are critical for HGF/c-MET signaling

The Plasminogen-Apple-Nematode (PAN) domain, with a core of four to six cysteine residues, is found in > 28,000 proteins across 959 genera. Still, its role in protein function is not fully understood. The PAN domain was initially characterized in numerous proteins, including HGF. Dysregulation of HGF-mediated signaling results in multiple deadly cancers. The binding of HGF to its cell surface receptor, c-MET, triggers all biological impacts. Here, we show that mutating four core cysteine residues in the HGF PAN domain reduces c-MET interaction, subsequent c-MET autophosphorylation, and phosphorylation of its downstream targets, perinuclear localization, cellular internalization of HGF, and its receptor, c-MET, and c-MET ubiquitination. Furthermore, transcriptional activation of HGF/c-MET signaling-related genes involved in cancer progression, invasion, metastasis, and cell survival were impaired. Thus, targeting the PAN domain of HGF may represent a mechanism for selectively regulating the binding and activation of the c-MET pathway.

Deciphering signal transduction networks in the liver by mechanistic mathematical modelling

In health and disease, liver cells are continuously exposed to cytokines and growth factors. While individual signal transduction pathways induced by these factors were studied in great detail, the cellular responses induced by repeated or combined stimulations are complex and less understood. Growth factor receptors on the cell surface of hepatocytes were shown to be regulated by receptor interactions, receptor trafficking and feedback regulation. Here, we exemplify how mechanistic mathematical modelling based on quantitative data can be employed to disentangle these interactions at the molecular level. Crucial is the analysis at a mechanistic level based on quantitative longitudinal data within a mathematical framework. In such multi-layered information, step-wise mathematical modelling using submodules is of advantage, which is fostered by sharing of standardized experimental data and mathematical models. Integration of signal transduction with metabolic regulation in the liver and mechanistic links to translational approaches promise to provide predictive tools for biology and personalized medicine.

Tumor Microenvironment of Hepatocellular Carcinoma: Challenges and Opportunities for New Treatment Options

The prevalence of liver cancer is constantly rising, with increasing incidence and mortality in Europe and the USA in recent decades. Among the different subtypes of liver cancers, hepatocellular carcinoma (HCC) is the most commonly diagnosed liver cancer. Besides advances in diagnosis and promising results of pre-clinical studies, HCC remains a highly lethal disease. In many cases, HCC is an effect of chronic liver inflammation, which leads to the formation of a complex tumor microenvironment (TME) composed of immune and stromal cells. The TME of HCC patients is a challenge for therapies, as it is involved in metastasis and the development of resistance. However, given that the TME is an intricate system of immune and stromal cells interacting with cancer cells, new immune-based therapies are being developed to target the TME of HCC. Therefore, understanding the complexity of the TME in HCC will provide new possibilities to design novel and more effective immunotherapeutics and combinatorial therapies to overcome resistance to treatment. In this review, we describe the role of inflammation during the development and progression of HCC by focusing on TME. We also describe the most recent therapeutic advances for HCC and possible combinatorial treatment options.

A text-based computational framework for patient -specific modeling for classification of cancers

Patient heterogeneity precludes cancer treatment and drug development; hence, development of methods for finding prognostic markers for individual treatment is urgently required. Here, we present Pasmopy (Patient-Specific Modeling in Python), a computational framework for stratification of patients using in silico signaling dynamics. Pasmopy converts texts and sentences on biochemical systems into an executable mathematical model. Using this framework, we built a model of the ErbB receptor signaling network, trained in cultured cell lines, and performed in silico simulation of 377 patients with breast cancer using The Cancer Genome Atlas (TCGA) transcriptome datasets. The temporal dynamics of Akt, extracellular signal-regulated kinase (ERK), and c-Myc in each patient were able to accurately predict the difference in prognosis and sensitivity to kinase inhibitors in triple-negative breast cancer (TNBC). Our model applies to any type of signaling network and facilitates the network-based use of prognostic markers and prediction of drug response.

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A text file describing biochemical systems is converted into an executable model

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Patient-specific models incorporate individual gene expression profiles

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In silico signaling dynamics can be utilized as prognostic biomarkers

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Personalized kinetic models are capable of predicting potential drug targets

c-Met-integrin cooperation: Mechanisms, tumorigenic effects, and therapeutic relevance

c-Met is a receptor tyrosine kinase which upon activation by its ligand, the hepatocyte growth factor, mediates many important signalling pathways that regulate cellular functions such as survival, proliferation, and migration. Its oncogenic and tumorigenic signalling mechanisms, greatly contributing to cancer development and progression, are well documented. Integrins, heterogeneous adhesion receptors which facilitate cell-extracellular matrix interactions, are important in biomechanically sensitive cell adhesion and motility but also modulate diverse cell behaviour. Here we review the studies which reported cooperation between c-Met and several integrins, particularly β1 and β4, in various cell models including many tumour cell types. From the various experimental models and results analysed, we propose that c-Met-integrin cooperation occurs via inside-out or outside-in signalling. Thus, either c-Met activation triggers integrin activation and cell adhesion or integrin adhesion to its extracellular ligand triggers c-Met activation. These two modes of cooperation require the adhesive function of integrins and mostly lead to cell migration and invasion. In a third, less conventional, mode of cooperation, the integrin plays the role of a signalling adaptor for c-Met, independently from its adhesive property, leading to anchorage independent survival. Recent studies have revealed the influence of endocytic trafficking in c-Met-integrin cooperation including the adaptor function of integrin occurring on endomembranes, triggering an inside-in signalling, believed to promote survival of metastatic cells. We present the evidence of the cooperation in vivo and in human tissues and highlight its therapeutic relevance. A better understanding of the mechanisms regulating c-Met-integrin cooperation in cancer progression could lead to the design of new therapies targeting this cooperation, providing more effective therapeutic approaches than c-Met or integrin inhibitors as monotherapies used in the clinic.

Systems biology of angiogenesis signaling: Computational models and omics

Angiogenesis is a highly regulated multiscale process that involves a plethora of cells, their cellular signal transduction, activation, proliferation, differentiation, as well as their intercellular communication. The coordinated execution and integration of such complex signaling programs is critical for physiological angiogenesis to take place in normal growth, development, exercise, and wound healing, while its dysregulation is critically linked to many major human diseases such as cancer, cardiovascular diseases, and ocular disorders; it is also crucial in regenerative medicine. Although huge efforts have been devoted to drug development for these diseases by investigation of angiogenesis‐targeted therapies, only a few therapeutics and targets have proved effective in humans due to the innate multiscale complexity and nonlinearity in the process of angiogenic signaling. As a promising approach that can help better address this challenge, systems biology modeling allows the integration of knowledge across studies and scales and provides a powerful means to mechanistically elucidate and connect the individual molecular and cellular signaling components that function in concert to regulate angiogenesis. In this review, we summarize and discuss how systems biology modeling studies, at the pathway‐, cell‐, tissue‐, and whole body‐levels, have advanced our understanding of signaling in angiogenesis and thereby delivered new translational insights for human diseases.

This article is categorized under:

Cardiovascular Diseases > Computational Models

Cancer > Computational Models

A systems biology model of junctional localization and downstream signaling of the Ang-Tie signaling pathway

The Ang–Tie signaling pathway is an important vascular signaling pathway regulating vascular growth and stability. Dysregulation in the pathway is associated with vascular dysfunction and numerous diseases that involve abnormal vascular permeability and endothelial cell inflammation. The understanding of the molecular mechanisms of the Ang–Tie pathway has been limited due to the complex reaction network formed by the ligands, receptors, and molecular regulatory mechanisms. In this study, we developed a mechanistic computational model of the Ang–Tie signaling pathway validated against experimental data. The model captures and reproduces the experimentally observed junctional localization and downstream signaling of the Ang–Tie signaling axis, as well as the time-dependent role of receptor Tie1. The model predicts that Tie1 modulates Tie2’s response to the context-dependent agonist Ang2 by junctional interactions. Furthermore, modulation of Tie1’s junctional localization, inhibition of Tie2 extracellular domain cleavage, and inhibition of VE-PTP are identified as potential molecular strategies for potentiating Ang2’s agonistic activity and rescuing Tie2 signaling in inflammatory endothelial cells.

Association between the HGF/c‑MET signaling pathway and tumorigenesis, progression and prognosis of hepatocellular carcinoma (Review)

Hepatocellular carcinoma (HCC) is one of the most aggressive and lethal malignancies with a rising incidence, and is characterized by rapid progression, frequent metastasis, late diagnosis, high postoperative recurrence and poor prognosis. Therefore, novel treatment strategies for HCC, particularly advanced HCC, are urgently required. The hepatocyte growth factor (HGF)/c‑mesenchymal‑epithelial transition receptor (c‑MET) axis is a key signaling pathway in HCC and is strongly associated with its highly malignant features. Available treatments based on HGF/c‑MET inhibition may prolong the lifespan of patients with HCC; however, they do not achieve the desired therapeutic effects. The aim of the present article was to review the basic knowledge regarding the role of the HGF/c‑MET signaling pathway in HCC, and examine the association between the HGF/c‑MET signaling pathway and the tumorigenesis, progression and prognosis of HCC.

Generation of osimertinib-resistant cells from epidermal growth factor receptor L858R/T790M mutant non-small cell lung carcinoma cell line

BACKGROUND

Lung cancer contributes to high cancer mortality worldwide with 80% of total cases diagnosed as non-small cell lung cancer (NSCLC). Epidermal growth factor receptor (EGFR) tyrosine kinase (TK) domain serves as a druggable target in NSCLC patients with exon 19 deletion and L858R mutation. However, patients eventually succumbed to resistance to first- and second-generation EGFR-TK inhibitors through activation of T790M mutation. Third-generation EGFR-TKI, Osimertinib exhibits high efficacy in patients with exon 19 deletion/L858R/T790M mutation but they experienced acquired resistance thereafter. Available treatment options in NSCLC patients remains a challenge due to unknown molecular heterogeneity responsible for acquired resistance to EGFR-TKI. In this study, we aim to generate Osimertinib-resistant (OR) cells from H1975 carrying L858R/T790M double mutation which can be used as a model to elucidate mechanism of resistance.

METHODS

OR cells were established via stepwise-dose escalation and limiting single-cell dilution method. We then evaluated Osimertinib resistance potential via cell viability assay. Proteins expression related to EGFR-signalling, epithelial to mesenchymal transition (EMT), and autophagy were analyzed via western blot.

RESULTS

OR cell lines exhibited increased drug resistance potential compared to H1975. Distinguishable mesenchymal-like features were observed in OR cells. Protein expression analysis revealed EGFR-independent signaling involved in the derived OR cells as well as EMT and autophagy activity.

CONCLUSION

We generated OR cell lines in-vitro as evidenced by increased drug resistance potential, increased mesenchymal features, and enhanced autophagy activity. Development of Osimertinib resistance cells may serve as in-vitro model facilitating discovery of molecular aberration present during acquired mechanism of resistance.

Obesity induced by high-fat diet is associated with critical changes in biological and molecular functions of mesenchymal stromal cells present in visceral adipose tissue

The mesenchymal stromal cells (MSCs) residing within the stromal component of visceral adipose tissue appear to be greatly affected by obesity, with impairment of their functions and presence of senescence. To gain further insight into these phenomena, we analyzed the changes in total proteome content and secretome of mouse MSCs after a high-fat diet (HFD) treatment compared to a normal diet (ND). In healthy conditions, MSCs are endowed with functions mainly devoted to vesicle trafficking. These cells have an immunoregulatory role, affecting leukocyte activation and migration, acute inflammation phase response, chemokine signaling, and platelet activities. They also present a robust response to stress. We identified four signaling pathways (TGF-β, VEGFR2, HMGB1, and Leptin) that appear to govern the cells' functions. In the obese mice, MSCs showed a change in their functions. The immunoregulation shifted toward pro-inflammatory tasks with the activation of interleukin-1 pathway and of Granzyme A signaling. Moreover, the methionine degradation pathway and the processing of capped intronless pre-mRNAs may be related to the inflammation process. The signaling pathways we identified in ND MSCs were replaced by MET, WNT, and FGFR2 signal transduction, which may play a role in promoting inflammation, cancer, and aging.

MET receptor in oncology: From biomarker to therapeutic target

First discovered in the 1984, the MET receptor tyrosine kinase (RTK) and its ligand hepatocyte growth factor or HGF (also known as scatter factor or SF) are implicated as key players in tumor cell migration, proliferation, and invasion in a variety of cancers. This pathway also plays a key role during embryogenesis in the development of muscular and nervous structures. High expression of the MET receptor has been shown to correlate with poor prognosis and resistance to therapy. MET exon 14 splicing variants, initially identified by us in lung cancer, is actionable through various tyrosine kinase inhibitors (TKIs). For this reason, this pathway is of interest as a therapeutic target. In this chapter we will be discussing the history of MET, the genetics of this RTK, and give some background on the receptor biology. Furthermore, we will discuss directed therapeutics, mechanisms of resistance, and the future of MET as a therapeutic target.

Charting the Fragmented Landscape of Drug Synergy

Even as the clinical impact of drug combinations continues to accelerate, no consensus on how to quantify drug synergy has emerged. Rather, surveying the landscape of drug synergy reveals the persistence of historical fissures regarding the appropriate domains of conflicting synergy models - fissures impacting all aspects of combination therapy discovery and deployment. Herein we chronicle the impact of these divisions on: (i) the design, interpretation, and reproducibility of high-throughput combination screens; (ii) the performance of algorithms to predict synergistic mixtures; and (iii) the search for higher-order synergistic interactions. Further progress in each of these subfields hinges on reaching a consensus regarding the long-standing rifts in the field.

Angiopoietin-Tie Signaling Pathway in Endothelial Cells: A Computational Model

The angiopoietin-Tie signaling pathway is an important vascular signaling pathway involved in angiogenesis, vascular stability, and quiescence. Dysregulation in the pathway is linked to the impairments in vascular function associated with many diseases, including cancer, ocular diseases, systemic inflammation, and cardiovascular diseases. The present study uses a computational signaling pathway model validated against experimental data to quantitatively study various mechanistic aspects of the angiopoietin-Tie signaling pathway, including receptor activation, trafficking, turnover, and molecular mechanisms of its regulation. The model provides mechanistic insights into the controversial role of Ang2 and its regulators vascular endothelial protein tyrosine phosphatase (VE-PTP) and Tie1 and predicts synergistic effects of inhibition of VE-PTP, Tie1, and Tie2 cleavage on enhancing the vascular protective actions of Tie2.