Software pipelines for RNA-Seq, ChIP-Seq and germline variant calling analyses in common workflow language (CWL).

Automating data analysis pipelines is a key requirement to ensure reproducibility of results, especially when dealing with large volumes of data. Here we assembled automated pipelines for the analysis of High-throughput Sequencing (HTS) data originating from RNA-Seq, ChIP-Seq and Germline variant calling experiments. We implemented these workflows in Common workflow language (CWL) and evaluated their performance by: i) reproducing the results of two previously published studies on Chronic Lymphocytic Leukemia (CLL), and ii) analyzing whole genome sequencing data from four Genome in a Bottle Consortium (GIAB) samples, comparing the detected variants against their respective golden standard truth sets.

Dissecting miRNA-Gene Networks to Map Clinical Utility Roads of Pharmacogenomics-Guided Therapeutic Decisions in Cardiovascular Precision Medicine.

MicroRNAs (miRNAs) create systems networks and gene-expression circuits through molecular signaling and cell interactions that contribute to health imbalance and the emergence of cardiovascular disorders (CVDs). Because the clinical phenotypes of CVD patients present a diversity in their pathophysiology and heterogeneity at the molecular level, it is essential to establish genomic signatures to delineate multifactorial correlations, and to unveil the variability seen in therapeutic intervention outcomes. The clinically validated miRNA biomarkers, along with the relevant SNPs identified, have to be suitably implemented in the clinical setting in order to enhance patient stratification capacity, to contribute to a better understanding of the underlying pathophysiological mechanisms, to guide the selection of innovative therapeutic schemes, and to identify innovative drugs and delivery systems.

Invariable Ribosome Stoichiometry During Murine Erythroid Differentiation: Implications for Understanding Ribosomopathies.

Heterogeneity of the main ribosomal composition represents an emerging, yet debatable, mechanism of gene expression regulation with a purported role in ribosomopathies, a group of disorders caused by mutations in ribosomal protein genes (RPs). Ribosomopathies, mysteriously relate with tissue-specific symptoms (mainly anemia and cancer predisposition), despite the ubiquitous expression and necessity of the associated RPs. An outstanding question that may shed light into disease pathogenicity and provide potential pharmacological interventions, is whether and how the ribosomal composition is modified during, the highly affected by RP mutations, process of erythroid differentiation.

A Risk-Stratification Machine Learning Framework for the Prediction of Coronary Artery Disease Severity: Insights From the GESS Trial.

Our study aims to develop a data-driven framework utilizing heterogenous electronic medical and clinical records and advanced Machine Learning (ML) approaches for: () the identification of critical risk factors affecting the complexity of Coronary Artery Disease (CAD), as assessed via the SYNTAX score; and () the development of ML prediction models for accurate estimation of the expected SYNTAX score. We propose a two-part modeling technique separating the process into two distinct phases: (a) a binary classification task for predicting, whether a patient is more likely to present with a non-zero SYNTAX score; and (b) a regression task to predict the expected SYNTAX score accountable to individual patients with a non-zero SYNTAX score. The framework is based on data collected from the GESS trial (NCT03150680) comprising electronic medical and clinical records for 303 adult patients with suspected CAD, having undergone invasive coronary angiography in AHEPA University Hospital of Thessaloniki, Greece.

The GEnetic Syntax Score: a genetic risk assessment implementation tool grading the complexity of coronary artery disease-rationale and design of the GESS study.

Background: Coronary artery disease (CAD) remains one of the leading causes of mortality worldwide and is associated with multiple inherited and environmental risk factors. This study is designed to identify, design, and develop a panel of genetic markers that combined with clinical and angiographic information, will facilitate the creation of a personalized risk prediction algorithm (GEnetic Syntax Score-GESS). GESS score could be a reliable tool for predicting cardiovascular risk for future adverse events and for guiding therapeutic strategies.

Sequence variation, common tissue expression patterns and learning models: a genome-wide survey of vertebrate ribosomal proteins.

Ribosomal genes produce the constituents of the ribosome, one of the most conserved subcellular structures of all cells, from bacteria to eukaryotes, including animals. There are notions that some protein-coding ribosomal genes vary in their roles across species, particularly vertebrates, through the involvement of some in a number of genetic diseases. Based on extensive sequence comparisons and systematic curation, we establish a reference set for ribosomal proteins (RPs) in eleven vertebrate species and quantify their sequence conservation levels.

The histone methyltransferase inhibitor A-366 enhances hemoglobin expression in erythroleukemia cells upon co-exposure with chemical inducers in culture.

Background: Erythroleukemia is caused by the uncontrolled multiplication of immature erythroid progenitor cells which fail to differentiate into erythrocytes. By directly targeting this class of malignant cells, the induction of terminal erythroid differentiation represents a vital therapeutic strategy for this disease. Erythroid differentiation involves the execution of a well-orchestrated gene expression program in which epigenetic enzymes play critical roles.

Pharmacogenomic Testing to Guide Personalized Cancer Medicine Decisions in Private Oncology Practice: A Case Study.

Innovative tumor profiling methodologies are utilized to elucidate the pharmacogenomic landscape of tumor cells in order to support the molecularly guided delivery of therapeutics. Indeed, improved clinical outcomes are achieved in oncology practice by providing the physicians with expert-guided, standardized, and easily interpretable knowledge, translated from molecular profiling analysis to support clinical decision-making. However, there is still limited utilization of the technology especially in small private oncology practices.

Data on the expression of SRPK1a in mammals.

SRPK1 is an evolutionary conserved protein kinase that specifically phosphorylates its substrates at serine residues located within arginine-serine-rich (RS) domains. We have previously reported the existence of a second less abundant isoform in humans, SRPK1a, which is formed from alternative splicing of the gene and contains an insertion of 171 amino acids at its N-terminal domain (Nikolakaki et al., 2001).

InterMineR: an R package for InterMine databases.

Summary: InterMineR is a package designed to provide a flexible interface between the R programming environment and biological databases built using the InterMine platform. The package offers access to the flexible query builder and the library of term enrichment tools of the InterMine framework, as well as interoperability with other Bioconductor packages. This facilitates automation of data retrieval tasks as well as downstream analysis with existing statistical tools in the R environment.

Uncovering the pharmacological response of novel sesquiterpene derivatives that differentially alter gene expression and modulate the cell cycle in cancer cells.

The present study aimed to assess the pharmacological anticancer profile of three natural and five synthetic sesquiterpenes developed by total chemical synthesis. To this end, their properties at the cellular and molecular level were evaluated in a panel of normal and cancer cell lines. The results obtained by performing cytotoxicity assays and gene expression analysis by reverse transcription-quantitative polymerase chain reaction showed that: i) Among the sesquiterpene derivatives analyzed, VDS58 exhibited a notable anticancer profile within attached (U-87 MG and MCF-7) and suspension (K562 and MEL-745) cancer cell cultures; however, U-87 MG cells were able to recover their proliferation capacity rapidly after 48 h of exposure; ii) gene expression profiling of U-87 MG cells, in contrast to K562 cells, showed a transient induction of cyclin-dependent kinase inhibitor 1A (CDKN1) expression; iii) the expression levels of transforming growth factor β1 (TGFB1) increased after 12 h of exposure of U-87 MG cells to VDS58 and were maintained at this level throughout the treatment period; iv) in K562 cells exposed to VDS58, TGFB1 expression levels were upregulated for 48 h and decrease afterwards; and v) the re-addition of VDS58 in U-87 MG cultures pretreated with VDS58 resulted in a notable increase in the expression of caspases (CASP3 and CASP9), BCL2‑associated agonist of cell death (BAD), cyclin D1, CDK6, CDKN1, MYC proto-oncogene bHLH transcription factor (MYC), TGFB1 and tumor suppressor protein p53.