Computational drug prediction in hepatoblastoma by integrating pan-cancer transcriptomics with pharmacological response.

Background And Aims: Hepatoblastoma (HB) is the predominant form of pediatric liver cancer, though it remains exceptionally rare. While treatment outcomes for children with HB have improved, patients with advanced tumors face limited therapeutic choices. Additionally, survivors often suffer from long-term adverse effects due to treatment, including ototoxicity, cardiotoxicity, delayed growth, and secondary tumors.

β-catenin perturbations control differentiation programs in mouse embryonic stem cells.

The Wnt/β-catenin pathway is involved in development, cancer, and embryonic stem cell (ESC) maintenance; its dual role in stem cell self-renewal and differentiation is still controversial. Here, by applying an system enabling inducible gene expression control, we report that moderate induction of transcriptionally active exogenous β-catenin in β-catenin null mouse ESCs promotes epiblast-like cell (EpiLC) derivation . Instead, in wild-type cells, moderate chemical pre-activation of the Wnt/β-catenin pathway promotes EpiLC derivation.

A toxicogenomic data space for system-level understanding and prediction of EDC-induced toxicity.

Endocrine disrupting compounds (EDCs) are a persistent threat to humans and wildlife due to their ability to interfere with endocrine signaling pathways. Inspired by previous work to improve chemical hazard identification through the use of toxicogenomics data, we developed a genomic-oriented data space for profiling the molecular activity of EDCs in an in silico manner, and for creating predictive models that identify and prioritize EDCs. Predictive models of EDCs, derived from gene expression data from rats (in vivo and in vitro primary hepatocytes) and humans (in vitro primary hepatocytes and HepG2), achieve testing accuracy greater than 90%.

ThETA: transcriptome-driven efficacy estimates for gene-based TArget discovery.

Summary: Estimating efficacy of gene-target-disease associations is a fundamental step in drug discovery. An important data source for this laborious task is RNA expression, which can provide gene-disease associations on the basis of expression fold change and statistical significance. However, the simply use of the log-fold change can lead to numerous false-positive associations.

Author Correction: Impaired mitophagy links mitochondrial disease to epithelial stress in methylmalonyl-CoA mutase deficiency.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Impaired mitophagy links mitochondrial disease to epithelial stress in methylmalonyl-CoA mutase deficiency.

Deregulation of mitochondrial network in terminally differentiated cells contributes to a broad spectrum of disorders. Methylmalonic acidemia (MMA) is one of the most common inherited metabolic disorders, due to deficiency of the mitochondrial methylmalonyl-coenzyme A mutase (MMUT). How MMUT deficiency triggers cell damage remains unknown, preventing the development of disease-modifying therapies.

Publisher Correction: Prioritizing target-disease associations with novel safety and efficacy scoring methods.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The TRAPP complex mediates secretion arrest induced by stress granule assembly.

The TRAnsport Protein Particle (TRAPP) complex controls multiple membrane trafficking steps and is strategically positioned to mediate cell adaptation to diverse environmental conditions, including acute stress. We have identified the TRAPP complex as a component of a branch of the integrated stress response that impinges on the early secretory pathway. The TRAPP complex associates with and drives the recruitment of the COPII coat to stress granules (SGs) leading to vesiculation of the Golgi complex and arrest of ER export.

Prioritizing target-disease associations with novel safety and efficacy scoring methods.

Biological target (commonly genes or proteins) identification is still largely a manual process, where experts manually try to collect and combine information from hundreds of data sources, ranging from scientific publications to omics databases. Targeting the wrong gene or protein will lead to failure of the drug development process, as well as incur delays and costs. To improve this process, different software platforms are being developed.

The Golgi complex in disease and therapy.

The Golgi complex occupies a strategic position in the endomembrane system and acts not only as a key trafficking and sorting station and a vital biosynthetic center for glycoproteins and lipids, but also as an active signaling hub. As such, the Golgi complex participates in the establishment and maintenance of cell compartmentalization and in general, cell processes such as cell growth and apoptosis. The different functions of the Golgi complex are executed by composite molecular machineries that have been exhaustively dissected over the last three decades.

Analysis of genetic markers by random amplified polymorphic DNA polymerase chain reaction (RAPD-PCR).

RAPD-PCR is a new technique that, starting from genomic DNA allows, with the use of a single primer of "random" base composition to amplify a variable number of sequences that can give important informations if analyzed for linkage studies, gene mapping or phylogenetic purposes. In order to detect the possible application of this simple way of DNA-fingerprinting in individual identification and in cell lineages characterization we analyzed human and non-human Primates DNA. Six different single primers of variable length were used and resulted in individual or specific electrophoretic patterns.