Nikolay Borisov - Academia.edu (original) (raw)

Papers by Nikolay Borisov

www.molecularsystemsbiology.com Systems-level interactions between insulin–EGF networks amplify m... more www.molecularsystemsbiology.com Systems-level interactions between insulin–EGF networks amplify mitogenic signaling

Journal of Biological Chemistry, 2006

Grb2-associated binder 1 (GAB1) is a scaffold protein involved in numerous interactions that prop... more Grb2-associated binder 1 (GAB1) is a scaffold protein involved in numerous interactions that propagate signaling by growth factor and cytokine receptors. Here we explore in silico and validate in vivo the role of GAB1 in the control of mitogenic (Ras/MAPK) and survival (phosphatidylinositol 3-kinase (PI3K)/Akt) signaling stimulated by epidermal growth factor (EGF). We built a comprehensive mechanistic model that allows for reliable predictions of temporal patterns of cellular responses to EGF under diverse perturbations, including different EGF doses, GAB1 suppression, expression of mutant proteins, and pharmacological inhibitors. We show that the temporal dynamics of GAB1 tyrosine phosphorylation is significantly controlled by positive GAB1-PI3K feedback and negative MAPK-GAB1 feedback. Our experimental and computational results demonstrate that the essential function of GAB1 is to enhance PI3K/Akt activation and extend the duration of Ras/ MAPK signaling. By amplifying positive interactions between survival and mitogenic pathways, GAB1 plays the critical role in cell proliferation and tumorigenesis.

Molecular Systems Biology, 2009

Crosstalk mechanisms have not been studied as thoroughly as individual signaling pathways. We exp... more Crosstalk mechanisms have not been studied as thoroughly as individual signaling pathways. We exploit experimental and computational approaches to reveal how a concordant interplay between the insulin and epidermal growth factor (EGF) signaling networks can potentiate mitogenic signaling. In HEK293 cells, insulin is a poor activator of the Ras/ERK (extracellular signal-regulated kinase) cascade, yet it enhances ERK activation by low EGF doses. We find that major crosstalk mechanisms that amplify ERK signaling are localized upstream of Ras and at the Ras/Raf level. Computational modeling unveils how critical network nodes, the adaptor proteins GAB1 and insulin receptor substrate (IRS), Src kinase, and phosphatase SHP2, convert insulin-induced increase in the phosphatidylinositol-3,4,5-triphosphate (PIP 3) concentration into enhanced Ras/ERK activity. The model predicts and experiments confirm that insulin-induced amplification of mitogenic signaling is abolished by disrupting PIP 3-mediated positive feedback via GAB1 and IRS. We demonstrate that GAB1 behaves as a non-linear amplifier of mitogenic responses and insulin endows EGF signaling with robustness to GAB1 suppression. Our results show the feasibility of using computational models to identify key target combinations and predict complex cellular responses to a mixture of external cues.

To continue our research on systems biology of mitogenesis, we have developed and fitted accordin... more To continue our research on systems biology of mitogenesis, we have developed and fitted according to the experimental data a highly-branched network model of ERK activation in response to EGF stimulation. To produce a network with full number of possible complexes and reactions that may emerge during signal propagation, we used the rule- based software tool in systems biology, BioNetGen 2. Although our network model contains more than 650 complexes and 5500 reactions, we showed the ability the handle this complexity, even using the manual parameter fitting. Analyzing the results of model fitting, we discuss possible details of protein-protein interaction, such as preferable sites/domains for binding one another, sequestration of active enzymes via binding to huge protein complexes etc. Plans for experimental validation of modeling results are also considered. Keywords-systems biology, mitogenic cell signaling, rule- based network modeling, model fitting, protein-protein interaction

Journal of Clinical Oncology

e13143 Background: Anticancer Targeted Drugs (ATDs) specifically target one or a few types of tum... more e13143 Background: Anticancer Targeted Drugs (ATDs) specifically target one or a few types of tumor-related molecules in a cell. More than two hundred of ATDs were approved worldwide. They have different mechanisms of action and are effective for different cohorts of patients. However, many individual cases remain poorly responsive and it is of great importance to identify predictive markers of ATD efficacy. Our aim was to develop a platform enabling smart selection of the most efficient ATD therapies. Methods: We generated a second-opinion platform for clinical oncologists termed Oncobox. It is based on the analysis of gene expression profile of a cancer sample in comparison with the corresponding normal tissue biosamples in order to personalize selection of targeted drugs for individual cancer patients. Based on RNA-seq gene expression data, pathway activation levels are calculated and along with the concentrations of molecular target genes products used as predictors of tumor res...

Methods in molecular biology (Clifton, N.J.), 2017

Although modeling of activation kinetics for various cell signaling pathways has reached a high g... more Although modeling of activation kinetics for various cell signaling pathways has reached a high grade of sophistication and thoroughness, most such kinetic models still remain of rather limited practical value for biomedicine. Nevertheless, recent advancements have been made in application of signaling pathway science for real needs of prescription of the most effective drugs for individual patients. The methods for such prescription evaluate the degree of pathological changes in the signaling machinery based on two types of data: first, on the results of high-throughput gene expression profiling, and second, on the molecular pathway graphs that reflect interactions between the pathway members. For example, our algorithm OncoFinder evaluates the activation of molecular pathways on the basis of gene/protein expression data in the objects of the interest.Yet, the question of assessment of the relative importance for each gene product in a molecular pathway remains unclear unless one c...

Methods in molecular biology (Clifton, N.J.), 2017

We propose a biomathematical approach termed OncoFinder (OF) that enables performing both quantit... more We propose a biomathematical approach termed OncoFinder (OF) that enables performing both quantitative and qualitative analyses of the intracellular molecular pathway activation. OF utilizes an algorithm that distinguishes the activator/repressor role of every gene product in a pathway. This method is applicable for the analysis of any physiological, stress, malignancy, and other conditions at the molecular level. OF showed a strong potential to neutralize background-caused differences between experimental gene expression data obtained using NGS, microarray and modern proteomics techniques. Importantly, in most cases, pathway activation signatures were better markers of cancer progression compared to the individual gene products. OF also enables correlating pathway activation with the success of anticancer therapy for individual patients. We further expanded this approach to analyze impact of micro RNAs (miRs) on the regulation of cellular interactome. Many alternative sources provi...

Nature communications, Nov 16, 2016

Signalling pathway activation analysis is a powerful approach for extracting biologically relevan... more Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biol...

Cell Cycle, 2016

Responses to human cytomegalovirus (HCMV) infection are largely individual and cell type specific... more Responses to human cytomegalovirus (HCMV) infection are largely individual and cell type specific. We investigated molecular profiles in 2 primary cell cultures of human fibroblasts, which are highly or marginally sensitive to HCMV infection, respectively. We screened expression of genes and microRNAs (miRs) at the early (3 hours) stage of infection. To assess molecular pathway activation profiles, we applied bioinformatic algorithms OncoFinder and MiRImpact. In both cell types, pathway regulation properties at mRNA and miR levels were markedly different. Surprisingly, in the infected highly sensitive cells, we observed a "freeze" of miR expression profiles compared to uninfected controls. Our results evidence that in the sensitive cells, HCMV blocks intracellular regulation of microRNA expression already at the earliest stage of infection. These data suggest somewhat new functions for HCMV products and demonstrate dependence of miR expression arrest on the host-encoded factors.

Cell Cycle, 2016

MicroRNAs (miRs) are short noncoding RNA molecules that regulate expression of target mRNAs. Many... more MicroRNAs (miRs) are short noncoding RNA molecules that regulate expression of target mRNAs. Many published sources provide information about miRs and their targets. However, bioinformatic tools elucidating higher level impact of the established total miR profiles, are still largely missing. Recently, we developed a method termed OncoFinder enabling quantification of the activities of intracellular molecular pathways basing on gene expression data. Here we propose a new technique, MiRImpact, which enables to link miR expression data with its estimated outcome on the regulation of molecular pathways, like signaling, metabolic, cytoskeleton rearrangement, and DNA repair pathways. MiRImpact uses OncoFinder rationale for pathway activity calculations, with the major distinctions that (i) it deals with the concentrations of miRs-known regulators of gene products participating in molecular pathways, and (ii) miRs are considered as negative regulators of target molecules, if other is not specified. MiRImpact operates with 2 types of databases: for molecular targets of miRs and for gene products participating in molecular pathways. We applied MiRImpact to compare regulation of human bladder cancer-specific signaling pathways at the levels of mRNA and miR expression. We took 2 most complete alternative databases of experimentally validated miR targets-miRTarBase and DianaTarBase, and an OncoFinder database featuring 2725 gene products and 271 signaling pathways. We showed that the impact of miRs is orthogonal to pathway regulation at the mRNA level, which stresses the importance of studying posttranscriptional regulation of gene expression. We also report characteristic set of miR and mRNA regulation features linked with bladder cancer.

To continue our research on systems biology of mitogenesis, we have developed and fitted accordin... more To continue our research on systems biology of mitogenesis, we have developed and fitted according to the experimental data a highly-branched network model of ERK activation in response to EGF stimulation. To produce a network with full number of possible complexes and reactions that may emerge during signal propagation, we used the rule-based software tool in systems biology, BioNetGen 2. Although our network model contains more than 650 complexes and 5500 reactions, we showed the ability the handle this complexity, even using the manual parameter fitting. Analyzing the results of model fitting, we discuss possible details of protein-protein interaction, such as preferable sites/domains for binding one another, sequestration of active enzymes via binding to huge protein complexes etc. Plans for experimental validation of modeling results are also considered.

Radioprotection, 2001

Although great efforts had been made to improve the physical phantoms used for calibrating in viv... more Although great efforts had been made to improve the physical phantoms used for calibrating in vivo measurement systems, for technical reasons they can oniy provide a rough representation of human tissue. Substantial corrections m w t therefore be made to calibration factors obtained with such caiibration phantoms for extrapolation to a given individuai. These corrections are particularly crucial and delicate in low-energy in vivo measurement when absorption in tissue is significant. To improve caiibration for such special conditions, the posîibility has been raised of using voxelised numerical phantoms associated with Monte Carlo computing techniques. In the method described below, a mathematical phantom, consisting of a voxelised representation derived from scanner images is used, with a specially-designed interface making it possible to not only reconstruct widely-differing contamination confgurations and specify associated tissue compositions, but also automatically create an MCNP4b input file. After validation of the different sources and geometries, the complete procedure of reconstruction of the phantom and simulation of "'Am lung measurement was carried out using a tissue equivalent calibration phantom of the type commoniy used for lung calibration for actinides. The purpose of this work was to extend the use of this principle to the reconstruction of numerical phantoms on the basis of physiological data of individuak obtained from maguetic resonance and scanner images. The resulîs obtained and the current limitations of this approach in the context are discussed. Développement de fantômes numériques voxélisés associé au code Monte Carlo MCNP : application à la mesure anthroporadiamétrique.

Radiation Protection Dosimetry, 2003

This paper reports on a new utility for development of computational phantoms for Monte Carlo cal... more This paper reports on a new utility for development of computational phantoms for Monte Carlo calculations and data analysis for in vivo measurements of radionuclides deposited in tissues. The individual parameters of each worker can be acquired for an exact geometric representation of his or her anatomy, which is particularly important for low-energy gamma ray emitting sources such as thorium, uranium, plutonium and other actinides. The software discussed here enables automatic creation of an MCNP input data file based on computed tomography (CT) scanning data. The utility was first tested for low- and medium-energy actinide emitters on Livermore phantoms, the mannequins generally used for lung counting, in order to compare the results of simulation and measurement. From these results, the utility's ability to study uncertainties in in vivo calibration were investigated. Calculations and comparison with the experimental data are presented and discussed in this paper.

Monte Carlo Methods and Applications, 2000

www.molecularsystemsbiology.com Systems-level interactions between insulin–EGF networks amplify m... more www.molecularsystemsbiology.com Systems-level interactions between insulin–EGF networks amplify mitogenic signaling

Journal of Biological Chemistry, 2006

Grb2-associated binder 1 (GAB1) is a scaffold protein involved in numerous interactions that prop... more Grb2-associated binder 1 (GAB1) is a scaffold protein involved in numerous interactions that propagate signaling by growth factor and cytokine receptors. Here we explore in silico and validate in vivo the role of GAB1 in the control of mitogenic (Ras/MAPK) and survival (phosphatidylinositol 3-kinase (PI3K)/Akt) signaling stimulated by epidermal growth factor (EGF). We built a comprehensive mechanistic model that allows for reliable predictions of temporal patterns of cellular responses to EGF under diverse perturbations, including different EGF doses, GAB1 suppression, expression of mutant proteins, and pharmacological inhibitors. We show that the temporal dynamics of GAB1 tyrosine phosphorylation is significantly controlled by positive GAB1-PI3K feedback and negative MAPK-GAB1 feedback. Our experimental and computational results demonstrate that the essential function of GAB1 is to enhance PI3K/Akt activation and extend the duration of Ras/ MAPK signaling. By amplifying positive interactions between survival and mitogenic pathways, GAB1 plays the critical role in cell proliferation and tumorigenesis.

Molecular Systems Biology, 2009

Crosstalk mechanisms have not been studied as thoroughly as individual signaling pathways. We exp... more Crosstalk mechanisms have not been studied as thoroughly as individual signaling pathways. We exploit experimental and computational approaches to reveal how a concordant interplay between the insulin and epidermal growth factor (EGF) signaling networks can potentiate mitogenic signaling. In HEK293 cells, insulin is a poor activator of the Ras/ERK (extracellular signal-regulated kinase) cascade, yet it enhances ERK activation by low EGF doses. We find that major crosstalk mechanisms that amplify ERK signaling are localized upstream of Ras and at the Ras/Raf level. Computational modeling unveils how critical network nodes, the adaptor proteins GAB1 and insulin receptor substrate (IRS), Src kinase, and phosphatase SHP2, convert insulin-induced increase in the phosphatidylinositol-3,4,5-triphosphate (PIP 3) concentration into enhanced Ras/ERK activity. The model predicts and experiments confirm that insulin-induced amplification of mitogenic signaling is abolished by disrupting PIP 3-mediated positive feedback via GAB1 and IRS. We demonstrate that GAB1 behaves as a non-linear amplifier of mitogenic responses and insulin endows EGF signaling with robustness to GAB1 suppression. Our results show the feasibility of using computational models to identify key target combinations and predict complex cellular responses to a mixture of external cues.

To continue our research on systems biology of mitogenesis, we have developed and fitted accordin... more To continue our research on systems biology of mitogenesis, we have developed and fitted according to the experimental data a highly-branched network model of ERK activation in response to EGF stimulation. To produce a network with full number of possible complexes and reactions that may emerge during signal propagation, we used the rule- based software tool in systems biology, BioNetGen 2. Although our network model contains more than 650 complexes and 5500 reactions, we showed the ability the handle this complexity, even using the manual parameter fitting. Analyzing the results of model fitting, we discuss possible details of protein-protein interaction, such as preferable sites/domains for binding one another, sequestration of active enzymes via binding to huge protein complexes etc. Plans for experimental validation of modeling results are also considered. Keywords-systems biology, mitogenic cell signaling, rule- based network modeling, model fitting, protein-protein interaction

Journal of Clinical Oncology

e13143 Background: Anticancer Targeted Drugs (ATDs) specifically target one or a few types of tum... more e13143 Background: Anticancer Targeted Drugs (ATDs) specifically target one or a few types of tumor-related molecules in a cell. More than two hundred of ATDs were approved worldwide. They have different mechanisms of action and are effective for different cohorts of patients. However, many individual cases remain poorly responsive and it is of great importance to identify predictive markers of ATD efficacy. Our aim was to develop a platform enabling smart selection of the most efficient ATD therapies. Methods: We generated a second-opinion platform for clinical oncologists termed Oncobox. It is based on the analysis of gene expression profile of a cancer sample in comparison with the corresponding normal tissue biosamples in order to personalize selection of targeted drugs for individual cancer patients. Based on RNA-seq gene expression data, pathway activation levels are calculated and along with the concentrations of molecular target genes products used as predictors of tumor res...

Methods in molecular biology (Clifton, N.J.), 2017

Although modeling of activation kinetics for various cell signaling pathways has reached a high g... more Although modeling of activation kinetics for various cell signaling pathways has reached a high grade of sophistication and thoroughness, most such kinetic models still remain of rather limited practical value for biomedicine. Nevertheless, recent advancements have been made in application of signaling pathway science for real needs of prescription of the most effective drugs for individual patients. The methods for such prescription evaluate the degree of pathological changes in the signaling machinery based on two types of data: first, on the results of high-throughput gene expression profiling, and second, on the molecular pathway graphs that reflect interactions between the pathway members. For example, our algorithm OncoFinder evaluates the activation of molecular pathways on the basis of gene/protein expression data in the objects of the interest.Yet, the question of assessment of the relative importance for each gene product in a molecular pathway remains unclear unless one c...

Methods in molecular biology (Clifton, N.J.), 2017

We propose a biomathematical approach termed OncoFinder (OF) that enables performing both quantit... more We propose a biomathematical approach termed OncoFinder (OF) that enables performing both quantitative and qualitative analyses of the intracellular molecular pathway activation. OF utilizes an algorithm that distinguishes the activator/repressor role of every gene product in a pathway. This method is applicable for the analysis of any physiological, stress, malignancy, and other conditions at the molecular level. OF showed a strong potential to neutralize background-caused differences between experimental gene expression data obtained using NGS, microarray and modern proteomics techniques. Importantly, in most cases, pathway activation signatures were better markers of cancer progression compared to the individual gene products. OF also enables correlating pathway activation with the success of anticancer therapy for individual patients. We further expanded this approach to analyze impact of micro RNAs (miRs) on the regulation of cellular interactome. Many alternative sources provi...

Nature communications, Nov 16, 2016

Signalling pathway activation analysis is a powerful approach for extracting biologically relevan... more Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biol...

Cell Cycle, 2016

Responses to human cytomegalovirus (HCMV) infection are largely individual and cell type specific... more Responses to human cytomegalovirus (HCMV) infection are largely individual and cell type specific. We investigated molecular profiles in 2 primary cell cultures of human fibroblasts, which are highly or marginally sensitive to HCMV infection, respectively. We screened expression of genes and microRNAs (miRs) at the early (3 hours) stage of infection. To assess molecular pathway activation profiles, we applied bioinformatic algorithms OncoFinder and MiRImpact. In both cell types, pathway regulation properties at mRNA and miR levels were markedly different. Surprisingly, in the infected highly sensitive cells, we observed a "freeze" of miR expression profiles compared to uninfected controls. Our results evidence that in the sensitive cells, HCMV blocks intracellular regulation of microRNA expression already at the earliest stage of infection. These data suggest somewhat new functions for HCMV products and demonstrate dependence of miR expression arrest on the host-encoded factors.

Cell Cycle, 2016

MicroRNAs (miRs) are short noncoding RNA molecules that regulate expression of target mRNAs. Many... more MicroRNAs (miRs) are short noncoding RNA molecules that regulate expression of target mRNAs. Many published sources provide information about miRs and their targets. However, bioinformatic tools elucidating higher level impact of the established total miR profiles, are still largely missing. Recently, we developed a method termed OncoFinder enabling quantification of the activities of intracellular molecular pathways basing on gene expression data. Here we propose a new technique, MiRImpact, which enables to link miR expression data with its estimated outcome on the regulation of molecular pathways, like signaling, metabolic, cytoskeleton rearrangement, and DNA repair pathways. MiRImpact uses OncoFinder rationale for pathway activity calculations, with the major distinctions that (i) it deals with the concentrations of miRs-known regulators of gene products participating in molecular pathways, and (ii) miRs are considered as negative regulators of target molecules, if other is not specified. MiRImpact operates with 2 types of databases: for molecular targets of miRs and for gene products participating in molecular pathways. We applied MiRImpact to compare regulation of human bladder cancer-specific signaling pathways at the levels of mRNA and miR expression. We took 2 most complete alternative databases of experimentally validated miR targets-miRTarBase and DianaTarBase, and an OncoFinder database featuring 2725 gene products and 271 signaling pathways. We showed that the impact of miRs is orthogonal to pathway regulation at the mRNA level, which stresses the importance of studying posttranscriptional regulation of gene expression. We also report characteristic set of miR and mRNA regulation features linked with bladder cancer.

To continue our research on systems biology of mitogenesis, we have developed and fitted accordin... more To continue our research on systems biology of mitogenesis, we have developed and fitted according to the experimental data a highly-branched network model of ERK activation in response to EGF stimulation. To produce a network with full number of possible complexes and reactions that may emerge during signal propagation, we used the rule-based software tool in systems biology, BioNetGen 2. Although our network model contains more than 650 complexes and 5500 reactions, we showed the ability the handle this complexity, even using the manual parameter fitting. Analyzing the results of model fitting, we discuss possible details of protein-protein interaction, such as preferable sites/domains for binding one another, sequestration of active enzymes via binding to huge protein complexes etc. Plans for experimental validation of modeling results are also considered.

Radioprotection, 2001

Although great efforts had been made to improve the physical phantoms used for calibrating in viv... more Although great efforts had been made to improve the physical phantoms used for calibrating in vivo measurement systems, for technical reasons they can oniy provide a rough representation of human tissue. Substantial corrections m w t therefore be made to calibration factors obtained with such caiibration phantoms for extrapolation to a given individuai. These corrections are particularly crucial and delicate in low-energy in vivo measurement when absorption in tissue is significant. To improve caiibration for such special conditions, the posîibility has been raised of using voxelised numerical phantoms associated with Monte Carlo computing techniques. In the method described below, a mathematical phantom, consisting of a voxelised representation derived from scanner images is used, with a specially-designed interface making it possible to not only reconstruct widely-differing contamination confgurations and specify associated tissue compositions, but also automatically create an MCNP4b input file. After validation of the different sources and geometries, the complete procedure of reconstruction of the phantom and simulation of "'Am lung measurement was carried out using a tissue equivalent calibration phantom of the type commoniy used for lung calibration for actinides. The purpose of this work was to extend the use of this principle to the reconstruction of numerical phantoms on the basis of physiological data of individuak obtained from maguetic resonance and scanner images. The resulîs obtained and the current limitations of this approach in the context are discussed. Développement de fantômes numériques voxélisés associé au code Monte Carlo MCNP : application à la mesure anthroporadiamétrique.

Radiation Protection Dosimetry, 2003

This paper reports on a new utility for development of computational phantoms for Monte Carlo cal... more This paper reports on a new utility for development of computational phantoms for Monte Carlo calculations and data analysis for in vivo measurements of radionuclides deposited in tissues. The individual parameters of each worker can be acquired for an exact geometric representation of his or her anatomy, which is particularly important for low-energy gamma ray emitting sources such as thorium, uranium, plutonium and other actinides. The software discussed here enables automatic creation of an MCNP input data file based on computed tomography (CT) scanning data. The utility was first tested for low- and medium-energy actinide emitters on Livermore phantoms, the mannequins generally used for lung counting, in order to compare the results of simulation and measurement. From these results, the utility's ability to study uncertainties in in vivo calibration were investigated. Calculations and comparison with the experimental data are presented and discussed in this paper.

Monte Carlo Methods and Applications, 2000