Shambhala: a platform-agnostic data harmonizer for gene expression data.

Background: Harmonization techniques make different gene expression profiles and their sets compatible and ready for comparisons. Here we present a new bioinformatic tool termed Shambhala for harmonization of multiple human gene expression datasets obtained using different experimental methods and platforms of microarray hybridization and RNA sequencing.

Results: Unlike previously published methods enabling good quality data harmonization for only two datasets, Shambhala allows conversion of multiple datasets into the universal form suitable for further comparisons.

Glycan recognition by human blood mononuclear cells with an emphasis on dendritic cells.

Dendritic cells (DCs) play crucial roles in innate and adaptive immune response, for which reason targeting antigen to these cells is an important strategy for improvement of vaccine development. To this end, we explored recognition of DCs lectins by glycans. For selection of the glycan "vector", a library of 229 fluorescent glycoprobes was employed to assess interaction with the CD14CD16CD83 blood mononuclear cell population containing the DCs known for their importance in antigen presentation to T-lymphocytes.

A method of gene expression data transfer from cell lines to cancer patients for machine-learning prediction of drug efficiency.

Personalized medicine implies that distinct treatment methods are prescribed to individual patients according several features that may be obtained from, e.g., gene expression profile.

Data aggregation at the level of molecular pathways improves stability of experimental transcriptomic and proteomic data.

High throughput technologies opened a new era in biomedicine by enabling massive analysis of gene expression at both RNA and protein levels. Unfortunately, expression data obtained in different experiments are often poorly compatible, even for the same biologic samples. Here, using experimental and bioinformatic investigation of major experimental platforms, we show that aggregation of gene expression data at the level of molecular pathways helps to diminish cross- and intra-platform bias otherwise clearly seen at the level of individual genes.

Cutting Edge: Activation of STING in T Cells Induces Type I IFN Responses and Cell Death.

Stimulator of interferon genes (STING) was initially described as a sensor of intracellular bacterial and viral DNA and a promising adjuvant target in innate immune cells; more recently STING has also been shown to detect endogenous DNA and play a role in tumor immunity and autoimmune disease development. Thus far STING has been studied in macrophages and dendritic cells. In this study, to our knowledge we provide the first evidence of STING activation in T cells, in which STING agonists not only provoke type I IFN production and IFN-stimulated gene expression, mirroring the response of innate cells, but are also capable of activating cell stress and death pathways.

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.

VEGF blockade enhances the antitumor effect of BRAFV600E inhibition.

The development of resistance remains a major obstacle to long-term disease control in cancer patients treated with targeted therapies. In BRAF-mutant mouse models, we demonstrate that although targeted inhibition of either BRAF or VEGF initially suppresses the growth of BRAF-mutant tumors, combined inhibition of both pathways results in apoptosis, long-lasting tumor responses, reduction in lung colonization, and delayed onset of acquired resistance to the BRAF inhibitor PLX4720. As well as inducing tumor vascular normalization and ameliorating hypoxia, this approach induces remodeling of the extracellular matrix, infiltration of macrophages with an M1-like phenotype, and reduction in cancer-associated fibroblasts.

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.

Large-scale profiling of signalling pathways reveals an asthma specific signature in bronchial smooth muscle cells.

Background: Bronchial smooth muscle (BSM) cells from asthmatic patients maintain in vitro a distinct hyper-reactive ("primed") phenotype, characterized by increased release of pro-inflammatory factors and mediators, as well as hyperplasia and/or hypertrophy. This "primed" phenotype helps to understand pathogenesis of asthma, as changes in BSM function are essential for manifestation of allergic and inflammatory responses and airway wall remodelling.

Objective: To identify signalling pathways in cultured primary BSMs of asthma patients and non-asthmatic subjects by genome wide profiling of differentially expressed mRNAs and activated intracellular signalling pathways (ISPs).

Molecular pathway activation features linked with transition from normal skin to primary and metastatic melanomas in human.

Melanoma is the most aggressive and dangerous type of skin cancer, but its molecular mechanisms remain largely unclear. For transcriptomic data of 478 primary and metastatic melanoma, nevi and normal skin samples, we performed high-throughput analysis of intracellular molecular networks including 592 signaling and metabolic pathways. We showed that at the molecular pathway level, the formation of nevi largely resembles transition from normal skin to primary melanoma.

A method for predicting target drug efficiency in cancer based on the analysis of signaling pathway activation.

A new generation of anticancer therapeutics called target drugs has quickly developed in the 21st century. These drugs are tailored to inhibit cancer cell growth, proliferation, and viability by specific interactions with one or a few target proteins. However, despite formally known molecular targets for every "target" drug, patient response to treatment remains largely individual and unpredictable.

Combinatorial high-throughput experimental and bioinformatic approach identifies molecular pathways linked with the sensitivity to anticancer target drugs.

Effective choice of anticancer drugs is important problem of modern medicine. We developed a method termed OncoFinder for the analysis of new type of biomarkers reflecting activation of intracellular signaling and metabolic molecular pathways. These biomarkers may be linked with the sensitivity to anticancer drugs.

Molecular functions of human endogenous retroviruses in health and disease.

Human endogenous retroviruses (HERVs) and related genetic elements form 504 distinct families and occupy ~8% of human genome. Recent success of high-throughput experimental technologies facilitated understanding functional impact of HERVs for molecular machinery of human cells. HERVs encode active retroviral proteins, which may exert important physiological functions in the body, but also may be involved in the progression of cancer and numerous human autoimmune, neurological and infectious diseases.

Pathway activation strength is a novel independent prognostic biomarker for cetuximab sensitivity in colorectal cancer patients.

Cetuximab, a monoclonal antibody against epidermal growth factor receptor (EGFR), was shown to be active in colorectal cancer. Although some patients who harbor K-ras wild-type tumors benefit from cetuximab treatment, 40 to 60% of patients with wild-type K-ras tumors do not respond to cetuximab. Currently, there is no universal marker or method of clinical utility that could guide the treatment of cetuximab in colorectal cancer.

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.

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).

A systematic experimental evaluation of microRNA markers of human bladder cancer.

Background: MicroRNAs (miRNAs) are a class of small RNAs that regulate gene expression. They are aberrantly expressed in many human cancers and are potential therapeutic targets and molecular biomarkers.

Methods: In this study, we for the first time validated the reported data on the entire set of published differential miRNAs (102 in total) through a series of transcriptome-wide experiments.