Репозиторий Университета

© Springer Science+Business Media, LLC, part of Springer Nature 2020. We describe here the Oncobox method for scoring efficiencies of anticancer target drugs (ATDs) using high throughput gene expression data. The method rationale, design, and validation are given along with the examples of its practical applications in biomedicine. The method is based on the analysis of intracellular molecular pathways activation and measuring expressions of molecular target genes for every ATD under consideration. Using Oncobox method requires collection of normal (control) expression profiles and annotated databases of molecular pathways and drug target genes. Both microarray and RNA sequencing profiles are acceptable, although the latter type of data prevails in the most recent applications of this technique.

© Springer Science+Business Media, LLC, part of Springer Nature 2020. Intracellular molecular pathways (IMPs) control all major events in the living cell. IMPs are considered hotspots in biomedical sciences and thousands of IMPs have been discovered for humans and model organisms. Knowledge of IMPs activation is essential for understanding biological functions and differences between the biological objects at the molecular level. Here we describe the Oncobox system for accurate quantitative scoring activities of up to several thousand molecular pathways based on high throughput molecular data. Although initially designed for gene expression and mainly RNA sequencing data, Oncobox is now also applicable for quantitative proteomics, microRNA and transcription factor binding sites mapping data. The Oncobox system includes modules of gene expression data harmonization, aggregation and comparison and a recursive algorithm for automatic annotation of molecular pathways. The universal rationale of Oncobox enables scoring of signaling, metabolic, cytoskeleton, immunity, DNA repair, and other pathways in a multitude of biological objects. The Oncobox system can be helpful to all those working in the fields of genetics, biochemistry, interactomics, and big data analytics in molecular biomedicine.

© 2019 American Chemical Society. Various agents, including drugs as well as nonmolecular stimuli, induce alterations in the physicochemical properties of proteins in cell lysates, living cells, and organisms. These alterations can be probed by applying a stability- and solubility-modifying factor, such as elevated temperature, to a varying degree. As a second dimension of variation, drug concentration or agent intensity/concentration can be used. Compared to standard approaches where curves are fitted to protein solubility data acquired at different temperatures and drug concentrations, Proteome Integral Solubility Alteration (PISA) assay increases the analysis throughput by 1 to 2 orders of magnitude for an unlimited number of factor variation points in such a scheme. The consumption of the compound and biological material decreases in PISA by the same factor. We envision widespread use of the PISA approach in chemical biology and drug development.

© 2017 Elsevier Inc. The mitochondrial set of proteins is a dynamic system, crucial for multiple functions of this organelle. Differential expression of genes in various tissues, alternative splicing, post-translational modifications, turnover and spatial dynamics of proteins are the factors that influence mitochondrial proteomes increasing their versatility. A wide range of high-throughput proteomic approaches are extensively used for identification, quantification and functional assessment of human and other mammalian mitochondrial proteins. This article reviews the methods and approaches which can be utilized for achieving one or another specific goal in mitochondrial investigations, and the recent advances in application of proteomics to study the roles of mitochondria in tumorigenesis and cancer progression.