A formal model for analyzing drug combination effects and its application in TNF-α-induced NFκB pathway

BACKGROUND: Drug combination therapy is commonly used in clinical practice. Many methods including Bliss independence method have been proposed for drug combination design based on simulations models or experiments. Although Bliss independence method can help to solve the drug combination design problem when there are only a small number of combinations, as the number of combinations increases, it may not be scalable. Exploration of system structure becomes important to reduce the complexity of the design problem. RESULTS: In this paper, we deduced a mathematical model which can simplify the serial structure and parallel structure of biological pathway for synergy evaluation of drug combinations. We demonstrated in steady state the sign of the synergism assessment factor derivative of the original system can be predicted by the sign of its simplified system. In addition, we analyzed the influence of feedback structure on survival ratio of the serial structure. We provided a sufficient condition under which the combination effect could be maintained. Furthermore, we applied our method to find three synergistic drug combinations on tumor necrosis factor α-induced NFκB pathway and subsequently verified by the cell experiment. CONCLUSIONS: We identified several structural properties underlying the Bliss independence criterion, and developed a systematic simplification framework for drug combiation desgin by combining simulation and system reaction network topology analysis. We hope that this work can provide insights to tackle the challenging problem of assessment of combinational drug therapy effect in a large scale signaling pathway. And hopefully in the future our method could be expanded to more general criteria

Comparing Signaling Networks between Normal and Transformed Hepatocytes Using Discrete Logical Models

Substantial effort in recent years has been devoted to constructing and analyzing large-scale gene and protein networks on the basis of “omic” data and literature mining. These interaction graphs provide valuable insight into the topologies of complex biological networks but are rarely context specific and cannot be used to predict the responses of cell signaling proteins to specific ligands or drugs. Conversely, traditional approaches to analyzing cell signaling are narrow in scope and cannot easily make use of network-level data. Here, we combine network analysis and functional experimentation by using a hybrid approach in which graphs are converted into simple mathematical models that can be trained against biochemical data. Specifically, we created Boolean logic models of immediate-early signaling in liver cells by training a literature-based prior knowledge network against biochemical data obtained from primary human hepatocytes and 4 hepatocellular carcinoma cell lines exposed to combinations of cytokines and small-molecule kinase inhibitors. Distinct families of models were recovered for each cell type, and these families clustered topologically into normal and diseased sets.National Institutes of Health (U.S.) (Grant GM68762)National Institutes of Health (U.S.) (Grant CA112967

Potential Molecular Targets of Oleanolic Acid in Insulin Resistance and Underlying Oxidative Stress: A Systematic Review

Oleanolic acid (OA) is a natural triterpene widely found in olive leaves that possesses antioxidant, anti-inflammatory, and insulin-sensitizing properties, among others. These OA characteristics could be of special interest in the treatment and prevention of insulin resistance (IR), but greater in-depth knowledge on the pathways involved in these properties is still needed. We aimed to systematically review the effects of OA on the molecular mechanisms and signaling pathways involved in the development of IR and underlying oxidative stress in insulin-resistant animal models or cell lines. The bibliographic search was carried out on PubMed, Web of Science, Scopus, Cochrane, and CINHAL databases between January 2001 and May 2022. The electronic search produced 5034 articles but, after applying the inclusion criteria, 13 animal studies and 3 cell experiments were identified, using SYRCLE’s Risk of Bias for assessing the risk of bias of the animal studies. OA was found to enhance insulin sensitivity and glucose uptake, and was found to suppress the hepatic glucose production, probably by modulating the IRS/PI3K/Akt/FoxO1 signaling pathway and by mitigating oxidative stress through regulating MAPK pathways. Future randomized controlled clinical trials to assess the potential benefit of OA as new therapeutic and preventive strategies for IR are warranted.Andalusia 2014-2020 European Regional Development Fund (ERDF) Operative Program B-AGR-287-UGR1

Modeling and Analysis of Signal Transduction Networks

Biological pathways, such as signaling networks, are a key component of biological systems of each living cell. In fact, malfunctions of signaling pathways are linked to a number of diseases, and components of signaling pathways are used as potential drug targets. Elucidating the dynamic behavior of the components of pathways, and their interactions, is one of the key research areas of systems biology. Biological signaling networks are characterized by a large number of components and an even larger number of parameters describing the network. Furthermore, investigations of signaling networks are characterized by large uncertainties of the network as well as limited availability of data due to expensive and time-consuming experiments. As such, techniques derived from systems analysis, e.g., sensitivity analysis, experimental design, and parameter estimation, are important tools for elucidating the mechanisms involved in signaling networks. This Special Issue contains papers that investigate a variety of different signaling networks via established, as well as newly developed modeling and analysis techniques

Investigation of the role of autocrine and paracrine growth factors in the survival and proliferation of chronic myeloid leukaemia stem and progenitor cells

Chronic myeloid leukaemia (CML) is a clonal myeloproliferative disorder arising in a haemopoietic stem cell (HSC) as a result of the reciprocal translocation between the long arms of chromosomes 9 and 22 (t9;22), leading to the formation of the fusion oncogene BCR-ABL. BCR-ABL has constitutive tyrosine kinase (TK) activity which drives, at least during the chronic phase (CP) of the disease, myeloid progenitor cells expansion through terminally differentiated cells and is necessary for the transformed phenotype. The introduction at the end of the last century of BCR-ABL TK inhibitors (TKI) has dramatically changed the management of newly diagnosed CP CML patients as the vast majority achieve deep molecular responses while enjoying good quality of life when treated with TKI. However about 20% of patients still show various degree of resistance to all currently available TKI while in those achieving deep responses, there is compelling evidence of persistent minimal residual disease demanding lifelong treatment which has obvious implications in terms of compliance, adverse events and costs. It is now known that the main reason for disease persistence in CML patients treated with TKI lies in the insensitivity of the most primitive CML leukaemia stem cell (LSC). More recent evidence has demonstrated that, in contrast to more mature leukaemic progenitor cells, CML LSC are not addicted to BCR-ABL kinase activity but rather rely on other stem cell intrinsic pathways for their survival. The main focus in the CML field is therefore to identify these pathways while also trying to exploit them therapeutically to achieve CML LSC eradication and as a result disease cure. Growth factor (GF) signals are known to provide survival cues to CML stem and progenitor cells (SPC) and potentially support their survival even in the presence of TKI. Moreover CML SPC are also known to produce higher levels of some GFs via an autocrine loop and support their survival and proliferation through this mechanism. In this thesis, the characterisation of the autocrine GF production by CML SPC was extended while also investigating the role of several GFs and downstream signals in survival, proliferation and self-renewal of CML SPC. Whenever possible, the consequences of therapeutic targeting of these signals on CML SPC survival and proliferation were also assessed in vitro. In particular the role of the intracellular janus kinase (JAK) 2, which relays several myeloid GF signals, such as those from interleukin (IL)-3 and granulocyte macrophage colony-stimulating factor (GM-CSF), in CML SPC survival and proliferation was investigated mainly because higher levels of autocrine expression of GM-CSF by CML SPC relative to normal were demonstrated, while autocrine IL-3 production by CML SPC had already been shown. Moreover the cognate receptor of both GM-CSF and IL-3 (CSF2RB) was also shown to be expressed at higher levels in CML SPC relative to their normal counterparts, further supporting investigations on the role of JAK2 in CML SPC biology. Indeed targeting JAK2 with small molecule inhibitors in CML SPC in vitro, particularly in the presence of maximal BCR-ABL TK inhibition, resulted in increased apoptosis, reduced proliferation and colony output of CML SPC. The JAK2 inhibitor plus TKI combination treatment, compared to either single agent, further reduced survival of the more primitive quiescent LSCs in vitro, while also reducing engraftment of primary CML CD34+ cells in vivo in immunocompromised hosts. Although a degree of toxicity to normal haemopoietic stem and progenitor cells (HSPC) was observed, this was not as great as seen in CML SPC, thus suggesting that a therapeutic window for using JAK2 inhibitors in CML patients might be present when a carefully selected concentration of these compounds is chosen. Tumour necrosis factor (TNF)-α was another GF shown to be produced in an autocrine fashion at higher levels by CML SPC relative to normal HSPC. Moreover its levels of production by CML SPC were not modulated by BCR-ABL TK activity. Using a small molecule TNF-α inhibitor and exogenous TNF-α, it was shown that autocrine TNF-α acts as a survival and proliferative signal in CML SPC. Moreover its role became even more important in the presence of TKI, as combining TNF-α inhibition with TKI led to high levels of apoptosis in CML CD34+ cells, including the more primitive quiescent population, while also causing increased apoptosis in a population enriched for CML LSCs based on its surface marker expression (CD34+ CD38-). Finally given the known importance of quiescence and self-renewal pathways in CML LSC persistence following TKI treatment, the role of transforming growth factor (TGF)-β1 and novel neurotransmitter mediated pathways in CML LSC quiescence and self-renewal was investigated based on the findings of a genome and epigenome-wide screen of primary CML LSCs and normal HSCs carried out in our laboratory. Using in vitro assays the putative role of the neuromediators norepinephrine and acethylcoline in CML LSC self-renewal was demonstrated. Moreover the role of TGF-β1 in inducing primary CML LSC quiescence mainly by modulating the AKT pathway was also demonstrated. Overall the work presented in this thesis has furthered our understanding of the role of both autocrine and paracrine known and novel regulators of haemopoiesis in several aspects of CML SPC biology such as their survival, proliferation and self-renewal. Furthermore the efficacy in eradicating CML SPC of therapeutic strategies targeting some of these GF signals has been explored in vitro, thus providing evidence supporting their subsequent testing in in vivo assays and in due course in clinical studies. It is hoped therefore that the work presented will contribute to devise novel therapeutic strategies to eradicate CML LSC and in turn lead to a cure for CML patients

Anti-inflammatory Activity of Plant Polyphenols 2.0

This book collects some recent scientific data on the role of polyphenols in various pathological contexts, ranging from viral infection to metabolic or chronic disorders such as diabetes and renal fibrosis. The included studies showed both in vitro and in vivo evidence concerning positive effects of polyphenols in inflammation, apoptosis, and oxidative stress. The investigated molecules include: verbascoside from Olea europea, curcumin from Curcuma longa, phenolic acids from Antirhea borbonica, and phlorotannins from marine algae. Finally, the main flavonoids present in the human diet and their anti-inflammatory and anti-cancer roles were also discussed. The scientific data confirm the importance of the plant kingdom, both marine and terrestrial, in the search for new compounds with potential benefits for humans

Osteoarthritis: From Molecular Pathways to Therapeutic Advances

In this book, we have reported the most recent discoveries and updates regarding molecular pathways in osteoarthritis. In particular, the advances regarding therapeutical options, from a molecular point of view, are largely discussed

Resistance is Futile: Physical Science, Systems Biology and Single-Cell Analysis to Understanding the Plastic and Heterogeneous Nature of Melanoma and Their Role in Non-Genetic Drug Resistance

Melanoma is the most deadly form of skin cancer due to its great metastatic potential. Targeted therapy that inhibits the BRAF-V600E driver mutation has shown impressive initial responses in melanoma patients. However, drug resistance, as the universal phenomenon for any cancer therapy, always limits treatment efficacy and compromises outcomes. As the early-step of resistance development, non-genetic mechanisms enable cancer cells to transition into a drug-resistant state in as early as a few days after drug treatment without alteration of the genome. This early mechanism is, to a large extent, due to the heterogeneous and highly plastic nature of tumor cells. Therefore, it imperative to understand the plastic and heterogeneous nature of the melanoma cells in order to identify combination therapies that can overcome resistance. In this thesis, we investigate these two fundamental natures of non-genetic drug resistance using BRAF inhibition of BRAF-mutant melanomas as the model system. These melanoma cells undergo multi-step, reversible drug-induced cell-state transitions from the original sensitive phenotype to a drug-resistant one. We first conducted bulk analysis to characterize the detailed kinetics of the entire transition from drug-sensitive state towards drug-resistant state, revealing expression changes of thousands of genes and extensive chromatin remodeling. A 3-step computational biology approach greatly simplified the complexity and revealed that the whole cell-state transition was controlled by a gene module activated within just the first three days of drug treatment, with the RelA transcription factor driving chromatin remodeling to establish an epigenetic program encoding long-term phenotype changes towards resistance. From there, a detailed mechanism connecting tumor epigenetic plasticity with non-genetic drug resistance was resolved through in-depth molecular biology experiments. The mechanism was validated in clinical patient samples. We further investigated heterogeneity by moving from bulk cellular studies to single-cell analysis. The single-cell view further revealed that two driving forces from both cell-state interconversions and phenotype-specific drug selection control the cell-state transition dynamics. The single-cell studies also pinpointed the signaling network hub, RelA, as the driver molecule of the initiation of the adaptive transition. These two competing driving forces were further quantitatively modeled via a thermodynamic-inspired surprisal analysis and a modified Fokker-Planck-type kinetic model. Finally, using integrated single-cell proteomic and metabolic technology I developed to characterize the early-stage signaling and metabolic changes upon initial drug responses, we further identified two distinct paths connecting drug-sensitive and drug-tolerant states. Melanoma cells exclusively traverse one of the two paths depending on the level of MITF in the drug-naïve cells. The two trajectories are associated with distinct signaling and metabolic susceptibilities and are independently druggable. In total, this thesis combines and synergizes various physical science and systems biology approaches together with several unique single-cell technologies and analysis to obtain a deep and comprehensive understanding of non-genetic drug resistance in cancer. The findings from this thesis provide several novel insights into the rational design of effective combination therapy for overcoming the development of resistance in response to cancer treatments.</p