Pathway Based Analysis of Mutation Data Is Efficient for Scoring Target Cancer Drugs.

Despite the significant achievements in chemotherapy, cancer remains one of the leading causes of death. Target therapy revolutionized this field, but efficiencies of target drugs show dramatic variation among individual patients. Personalization of target therapies remains, therefore, a challenge in oncology.

Pathway Instability Is an Effective New Mutation-Based Type of Cancer Biomarkers.

DNA mutations play a crucial role in cancer development and progression. Mutation profiles vary dramatically in different cancer types and between individual tumors. Mutations of several individual genes are known as reliable cancer biomarkers, although the number of such genes is tiny and does not enable differential diagnostics for most of the cancers.

Bioinformatics Meets Biomedicine: OncoFinder, a Quantitative Approach for Interrogating Molecular Pathways Using Gene Expression Data.

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.

Mathematical Justification of Expression-Based Pathway Activation Scoring (PAS).

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.

Early stage of cytomegalovirus infection suppresses host microRNA expression regulation in human fibroblasts.

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.

MiRImpact, a new bioinformatic method using complete microRNA expression profiles to assess their overall influence on the activity of intracellular molecular pathways.

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.

Signaling pathways activation profiles make better markers of cancer than expression of individual genes.

Identification of reliable and accurate molecular markers remains one of the major challenges of contemporary biomedicine. We developed a new bioinformatic technique termed OncoFinder that for the first time enables to quantatively measure activation of intracellular signaling pathways basing on transcriptomic data. Signaling pathways regulate all major cellular events in health and disease.

Novel robust biomarkers for human bladder cancer based on activation of intracellular signaling pathways.

We recently proposed a new bioinformatic algorithm called OncoFinder for quantifying the activation of intracellular signaling pathways. It was proved advantageous for minimizing errors of high-throughput gene expression analyses and showed strong potential for identifying new biomarkers. Here, for the first time, we applied OncoFinder for normal and cancerous tissues of the human bladder to identify biomarkers of bladder cancer.

Oncofinder, a new method for the analysis of intracellular signaling pathway activation using transcriptomic data.

We propose a new biomathematical method, OncoFinder, for both quantitative and qualitative analysis of the intracellular signaling pathway activation (SPA). This method is universal and may be used for the analysis of any physiological, stress, malignancy and other perturbed conditions at the molecular level. In contrast to the other existing techniques for aggregation and generalization of the gene expression data for individual samples, we suggest to distinguish the positive/activator and negative/repressor role of every gene product in each pathway.

Signaling pathway cloud regulation for in silico screening and ranking of the potential geroprotective drugs.

The major challenges of aging research include absence of the comprehensive set of aging biomarkers, the time it takes to evaluate the effects of various interventions on longevity in humans and the difficulty extrapolating the results from model organisms to humans. To address these challenges we propose the in silico method for screening and ranking the possible geroprotectors followed by the high-throughput in vivo and in vitro validation. The proposed method evaluates the changes in the collection of activated or suppressed signaling pathways involved in aging and longevity, termed signaling pathway cloud, constructed using the gene expression data and epigenetic profiles of young and old patients' tissues.

The OncoFinder algorithm for minimizing the errors introduced by the high-throughput methods of transcriptome analysis.

The diversity of the installed sequencing and microarray equipment make it increasingly difficult to compare and analyze the gene expression datasets obtained using the different methods. Many applications requiring high-quality and low error rates cannot make use of available data using traditional analytical approaches. Recently, we proposed a new concept of signalome-wide analysis of functional changes in the intracellular pathways termed OncoFinder, a bioinformatic tool for quantitative estimation of the signaling pathway activation (SPA).

Scaffolding protein Grb2-associated binder 1 sustains epidermal growth factor-induced mitogenic and survival signaling by multiple positive feedback loops.

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.

Trading the micro-world of combinatorial complexity for the macro-world of protein interaction domains.

Membrane receptors and proteins involved in signal transduction display numerous binding domains and operate as molecular scaffolds generating a variety of parallel reactions and protein complexes. The resulting combinatorial explosion of the number of feasible chemical species and, hence, different states of a network greatly impedes mechanistic modeling of signaling systems. Here we present novel general principles and identify kinetic requirements that allow us to replace a mechanistic picture of all possible micro-states and transitions by a macro-description of states of separate binding sites of network proteins.

Signaling through receptors and scaffolds: independent interactions reduce combinatorial complexity.

After activation, many receptors and their adaptor proteins act as scaffolds displaying numerous docking sites and engaging multiple targets. The consequent assemblage of a variety of protein complexes results in a combinatorial increase in the number of feasible molecular species presenting different states of a receptor-scaffold signaling module. Tens of thousands of such microstates emerge even for the initial signal propagation events, greatly impeding a quantitative analysis of networks.