Long-read transcriptome sequencing of CLL and MDS patients uncovers molecular effects of mutations.

Mutations in splicing factor 3B subunit 1 () frequently occur in patients with chronic lymphocytic leukemia (CLL) and myelodysplastic syndromes (MDSs). These mutations have different effects on the disease prognosis with beneficial effect in MDS and worse prognosis in CLL patients. A full-length transcriptome approach can expand our knowledge on mutation effects on RNA splicing and its contribution to patient survival and treatment options.

Cancer drug sensitivity estimation using modular deep Graph Neural Networks.

Computational drug sensitivity models have the potential to improve therapeutic outcomes by identifying targeted drugs components that are tailored to the transcriptomic profile of a given primary tumor. The SMILES representation of molecules that is used by state-of-the-art drug-sensitivity models is not conducive for neural networks to generalize to new drugs, in part because the distance between atoms does not generally correspond to the distance between their representation in the SMILES strings. Graph-attention networks, on the other hand, are high-capacity models that require large training-data volumes which are not available for drug-sensitivity estimation.

Depletion of TBC1D4 Improves the Metabolic Exercise Response by Overcoming Genetically Induced Peripheral Insulin Resistance.

The Rab-GTPase-activating protein (RabGAP) TBC1D4 (AS160) represents a key component in the regulation of glucose transport into skeletal muscle and white adipose tissue (WAT) and is therefore crucial during the development of insulin resistance and type 2 diabetes. Increased daily activity has been shown to be associated with improved postprandial hyperglycemia in allele carriers of a loss-of-function variant in the human TBC1D4 gene. Using conventional Tbc1d4-deficient mice (D4KO) fed a high-fat diet, we show that moderate endurance exercise training leads to substantially improved glucose and insulin tolerance and enhanced expression levels of markers for mitochondrial activity and browning in WAT from D4KO animals.

Neurofibromin 1 controls metabolic balance and Notch-dependent quiescence of murine juvenile myogenic progenitors.

Patients affected by neurofibromatosis type 1 (NF1) frequently show muscle weakness with unknown etiology. Here we show that, in mice, Neurofibromin 1 (Nf1) is not required in muscle fibers, but specifically in early postnatal myogenic progenitors (MPs), where Nf1 loss led to cell cycle exit and differentiation blockade, depleting the MP pool resulting in reduced myonuclear accretion as well as reduced muscle stem cell numbers. This was caused by precocious induction of stem cell quiescence coupled to metabolic reprogramming of MPs impinging on glycolytic shutdown, which was conserved in muscle fibers.

IsoTools: a flexible workflow for long-read transcriptome sequencing analysis.

Motivation: Long-read transcriptome sequencing (LRTS) has the potential to enhance our understanding of alternative splicing and the complexity of this process requires the use of versatile computational tools, with the ability to accommodate various stages of the workflow with maximum flexibility.

Results: We introduce IsoTools, a Python-based LRTS analysis framework that offers a wide range of functionality for transcriptome reconstruction and quantification of transcripts. Furthermore, we integrate a graph-based method for identifying alternative splicing events and a statistical approach based on the beta-binomial distribution for detecting differential events.

Deletion of Tbc1d4/As160 abrogates cardiac glucose uptake and increases myocardial damage after ischemia/reperfusion.

Background: Type 2 Diabetes mellitus (T2DM) is a major risk factor for cardiovascular disease and associated with poor outcome after myocardial infarction (MI). In T2DM, cardiac metabolic flexibility, i.e.

Reversible colorimetric sensing of volatile analytes by wicking in close proximity to a photonic film.

Isolation of volatile analytes from environmental or biological fluids is a rate-determining step that can delay the response time for continuous sensing. In this paper, we demonstrate a colorimetric sensing system that enables the rapid detection of gas-phase analytes released from a flowing micro-volume fluid sample. The sensor platform is an analyte-responsive metal-insulator-metal (MIM) thin-film structure integrated with a large area quartz micropillar array.

[Ronald D. Laing's "Radical Trip". Reflection on the Relationship Between Psychiatry, Anti-Psychiatry, and Science in the 1960s].

Inspired by American research on the role of the family environment in the development of schizophrenia, the Scottish psychiatrist Ronald D. Laing, now known as the figurehead of British antipsychiatry, began his own research project with his colleague Aaron Esterson in the late 1950s. In the process, he became convinced that those diagnosed as "schizophrenic" were far more rational than bourgeois families alienated from themselves.

Pre-Training on In Vitro and Fine-Tuning on Patient-Derived Data Improves Deep Neural Networks for Anti-Cancer Drug-Sensitivity Prediction.

Large-scale databases that report the inhibitory capacities of many combinations of candidate drug compounds and cultivated cancer cell lines have driven the development of preclinical drug-sensitivity models based on machine learning. However, cultivated cell lines have devolved from human cancer cells over years or even decades under selective pressure in culture conditions. Moreover, models that have been trained on in vitro data cannot account for interactions with other types of cells.

Epirubicin Alters DNA Methylation Profiles Related to Cardiotoxicity.

Background: Epirubicin (EPI) is an important anticancer drug that is well-known for its cardiotoxic side effect. Studying epigenetic modification such as DNA methylation can help to understand the EPI-related toxic mechanisms in cardiac tissue. In this study, we analyzed the DNA methylation profile in a relevant human cell model and inspected the expression of differentially methylated genes at the transcriptome level to understand how changes in DNA methylation could affect gene expression in relation to EPI-induced cardiotoxicity.

Deregulation and epigenetic modification of BCL2-family genes cause resistance to venetoclax in hematologic malignancies.

The BCL2 inhibitor venetoclax has been approved to treat different hematological malignancies. Because there is no common genetic alteration causing resistance to venetoclax in chronic lymphocytic leukemia (CLL) and B-cell lymphoma, we asked if epigenetic events might be involved in venetoclax resistance. Therefore, we employed whole-exome sequencing, methylated DNA immunoprecipitation sequencing, and genome-wide clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 screening to investigate venetoclax resistance in aggressive lymphoma and high-risk CLL patients.

Matching anticancer compounds and tumor cell lines by neural networks with ranking loss.

Computational drug sensitivity models have the potential to improve therapeutic outcomes by identifying targeted drug components that are likely to achieve the highest efficacy for a cancer cell line at hand at a therapeutic dose. State of the art drug sensitivity models use regression techniques to predict the inhibitory concentration of a drug for a tumor cell line. This regression objective is not directly aligned with either of these principal goals of drug sensitivity models: We argue that drug sensitivity modeling should be seen as a ranking problem with an optimization criterion that quantifies a drug's inhibitory capacity for the cancer cell line at hand relative to its toxicity for healthy cells.

Screening Electrocardiograms Have Low Utility in Medical Clearance Before Pediatric Inpatient Psychiatric Admission.

Objectives: Children presenting to the emergency department (ED) requiring psychiatric admission often undergo screening electrocardiograms (ECG) as part of the medical clearance process. The diagnostic yield of screening ECGs for this purpose has not been reported. The purpose of this study was to determine the clinical utility of screening ECGs in children and adolescents requiring acute inpatient psychiatric admission.

Altered DNA Methylation Profiles in Mutated CLL Patients.

Mutations in splicing factor genes have a severe impact on the survival of cancer patients. Splicing factor 3b subunit 1 () is one of the most frequently mutated genes in chronic lymphocytic leukemia (CLL); patients carrying these mutations have a poor prognosis. Since the splicing machinery and the epigenome are closely interconnected, we investigated whether these alterations may affect the epigenomes of CLL patients.

Large-scale literature mining to assess the relation between anti-cancer drugs and cancer types.

Background: There is a huge body of scientific literature describing the relation between tumor types and anti-cancer drugs. The vast amount of scientific literature makes it impossible for researchers and physicians to extract all relevant information manually.

Methods: In order to cope with the large amount of literature we applied an automated text mining approach to assess the relations between 30 most frequent cancer types and 270 anti-cancer drugs.

PWD/Ph-Encoded Genetic Variants Modulate the Cellular Wnt/β-Catenin Response to Suppress -Triggered Intestinal Tumor Formation.

Genetic predisposition affects the penetrance of tumor-initiating mutations, such as APC mutations that stabilize β-catenin and cause intestinal tumors in mice and humans. However, the mechanisms involved in genetically predisposed penetrance are not well understood. Here, we analyzed tumor multiplicity and gene expression in tumor-prone mice on highly variant C57BL/6J (B6) and PWD/Ph (PWD) genetic backgrounds.

Network integration and modelling of dynamic drug responses at multi-omics levels.

Uncovering cellular responses from heterogeneous genomic data is crucial for molecular medicine in particular for drug safety. This can be realized by integrating the molecular activities in networks of interacting proteins. As proof-of-concept we challenge network modeling with time-resolved proteome, transcriptome and methylome measurements in iPSC-derived human 3D cardiac microtissues to elucidate adverse mechanisms of anthracycline cardiotoxicity measured with four different drugs (doxorubicin, epirubicin, idarubicin and daunorubicin).

DMSO induces drastic changes in human cellular processes and epigenetic landscape in vitro.

Though clinical trials for medical applications of dimethyl sulfoxide (DMSO) reported toxicity in the 1960s, later, the FDA classified DMSO in the safest solvent category. DMSO became widely used in many biomedical fields and biological effects were overlooked. Meanwhile, biomedical science has evolved towards sensitive high-throughput techniques and new research areas, including epigenomics and microRNAs.

Combined Targeted Resequencing of Cytosine DNA Methylation and Mutations of DNA Repair Genes with Potential Use for Poly(ADP-Ribose) Polymerase 1 Inhibitor Sensitivity Testing.

Current molecular tumor diagnostics encompass panel sequencing to detect mutations, copy number alterations, and rearrangements. However, tumor suppressor genes can also be inactivated by methylation within their promoter region. These epigenetic alterations are so far rarely assessed in the clinical setting.

Epigenomic profiling of non-small cell lung cancer xenografts uncover LRP12 DNA methylation as predictive biomarker for carboplatin resistance.

Background: Non-small cell lung cancer (NSCLC) is the most common cause of cancer-related deaths worldwide and is primarily treated with radiation, surgery, and platinum-based drugs like cisplatin and carboplatin. The major challenge in the treatment of NSCLC patients is intrinsic or acquired resistance to chemotherapy. Molecular markers predicting the outcome of the patients are urgently needed.

QSEA-modelling of genome-wide DNA methylation from sequencing enrichment experiments.

Genome-wide enrichment of methylated DNA followed by sequencing (MeDIP-seq) offers a reasonable compromise between experimental costs and genomic coverage. However, the computational analysis of these experiments is complex, and quantification of the enrichment signals in terms of absolute levels of methylation requires specific transformation. In this work, we present QSEA, Quantitative Sequence Enrichment Analysis, a comprehensive workflow for the modelling and subsequent quantification of MeDIP-seq data.

Analyzing and interpreting genome data at the network level with ConsensusPathDB.

ConsensusPathDB consists of a comprehensive collection of human (as well as mouse and yeast) molecular interaction data integrated from 32 different public repositories and a web interface featuring a set of computational methods and visualization tools to explore these data. This protocol describes the use of ConsensusPathDB (http://consensuspathdb.org) with respect to the functional and network-based characterization of biomolecules (genes, proteins and metabolites) that are submitted to the system either as a priority list or together with associated experimental data such as RNA-seq.