CPI203, a BET inhibitor, down-regulates a consistent set of DNA synthesis genes across a wide array of glioblastoma lines.

Introduction: Glioblastomas utilize malignant gene expression pathways to drive growth. Many of these gene pathways are not directly accessible with molecularly targeted pharmacological agents. Chromatin-modifying compounds can alter gene expression and target glioblastoma growth pathways.

Phosphodiesterase-4 Inhibitors Increase Pigment Cell Proliferation and Melanization in Cultured Melanocytes and within a 3-Dimensional Skin Equivalent Model.

Vitiligo is a common chronic autoimmune disease characterized by white macules and patches of the skin, having a negative impact on patients' life and without any definitive cure at present. Identification of new compounds to reverse depigmentation is therefore a pressing need for this disease. The pharmacologic compounds phosphodiesterase-4 inhibitors (PDE4is) are small molecules with immunomodulatory properties used for treatment of inflammatory dermatoses.

Smccnet 2.0: a comprehensive tool for multi-omics network inference with shiny visualization.

Sparse multiple canonical correlation network analysis (SmCCNet) is a machine learning technique for integrating omics data along with a variable of interest (e.g., phenotype of complex disease), and reconstructing multi-omics networks that are specific to this variable.

SmCCNet 2.0: A Comprehensive Tool for Multi-omics Network Inference with Shiny Visualization.

Summary: Sparse multiple canonical correlation network analysis (SmCCNet) is a machine learning technique for integrating omics data along with a variable of interest (e.g., phenotype of complex disease), and reconstructing multi-omics networks that are specific to this variable.

Integrated variant allele frequency analysis pipeline and R package: easyVAF.

Somatic sequence variants are associated with cancer diagnosis, prognostic stratification, and treatment response. Variant allele frequency (VAF), the percentage of sequence reads with a specific DNA variant over the read depth at that locus, has been used as a metric to quantify mutation rates in these applications. VAF has the potential for feature detection by reflecting changes in tumor clonal composition across treatments or time points.

Significant increase of high-risk chromosome 1q gain and 6q loss at recurrence in posterior fossa group A ependymoma: A multicenter study.

Background: Ependymoma (EPN) posterior fossa group A (PFA) has the highest rate of recurrence and the worst prognosis of all EPN molecular groups. At relapse, it is typically incurable even with re-resection and re-irradiation. The biology of recurrent PFA remains largely unknown; however, the increasing use of surgery at first recurrence has now provided access to clinical samples to facilitate a better understanding of this.

Phase II trial of fulvestrant plus enzalutamide in ER+/HER2- advanced breast cancer.

This clinical trial combined fulvestrant with the anti-androgen enzalutamide in women with metastatic ER+/HER2- breast cancer (BC). Eligible patients were women with ECOG 0-2, ER+/HER2- measurable or evaluable metastatic BC. Prior fulvestrant was allowed.

Deep learning on graphs for multi-omics classification of COPD.

Network approaches have successfully been used to help reveal complex mechanisms of diseases including Chronic Obstructive Pulmonary Disease (COPD). However despite recent advances, we remain limited in our ability to incorporate protein-protein interaction (PPI) network information with omics data for disease prediction. New deep learning methods including convolution Graph Neural Network (ConvGNN) has shown great potential for disease classification using transcriptomics data and known PPI networks from existing databases.

Single-Cell Analysis Reveals Distinct Immune and Smooth Muscle Cell Populations that Contribute to Chronic Thromboembolic Pulmonary Hypertension.

Chronic thromboembolic pulmonary hypertension (CTEPH) is a sequela of acute pulmonary embolism (PE) in which the PE remodels into a chronic scar in the pulmonary arteries. This results in vascular obstruction, pulmonary microvasculopathy, and pulmonary hypertension. Our current understanding of CTEPH pathobiology is primarily derived from cell-based studies limited by the use of specific cell markers or phenotypic modulation in cell culture.

Significant Subgraph Detection in Multi-omics Networks for Disease Pathway Identification.

Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death in the United States. COPD represents one of many areas of research where identifying complex pathways and networks of interacting biomarkers is an important avenue toward studying disease progression and potentially discovering cures. Recently, sparse multiple canonical correlation network analysis (SmCCNet) was developed to identify complex relationships between omics associated with a disease phenotype, such as lung function.

An Augmented High-Dimensional Graphical Lasso Method to Incorporate Prior Biological Knowledge for Global Network Learning.

Biological networks are often inferred through Gaussian graphical models (GGMs) using gene or protein expression data only. GGMs identify conditional dependence by estimating a precision matrix between genes or proteins. However, conventional GGM approaches often ignore prior knowledge about protein-protein interactions (PPI).

Identifying miRNA-mRNA Networks Associated With COPD Phenotypes.

Chronic obstructive pulmonary disease (COPD) is characterized by expiratory airflow limitation and symptoms such as shortness of breath. Although many studies have demonstrated dysregulated microRNA (miRNA) and gene (mRNA) expression in the pathogenesis of COPD, how miRNAs and mRNAs systematically interact and contribute to COPD development is still not clear. To gain a deeper understanding of the gene regulatory network underlying COPD pathogenesis, we used Sparse Multiple Canonical Correlation Network (SmCCNet) to integrate whole blood miRNA and RNA-sequencing data from 404 participants in the COPDGene study to identify novel miRNA-mRNA networks associated with COPD-related phenotypes including lung function and emphysema.

Multi-omics subtyping pipeline for chronic obstructive pulmonary disease.

Chronic Obstructive Pulmonary Disease (COPD) is the third leading cause of mortality in the United States; however, COPD has heterogeneous clinical phenotypes. This is the first large scale attempt which uses transcriptomics, proteomics, and metabolomics (multi-omics) to determine whether there are molecularly defined clusters with distinct clinical phenotypes that may underlie the clinical heterogeneity. Subjects included 3,278 subjects from the COPDGene cohort with at least one of the following profiles: whole blood transcriptomes (2,650 subjects); plasma proteomes (1,013 subjects); and plasma metabolomes (1,136 subjects).

Plasma Metabolomic Signatures of Chronic Obstructive Pulmonary Disease and the Impact of Genetic Variants on Phenotype-Driven Modules.

Small studies have recently suggested that there are specific plasma metabolic signatures in chronic obstructive pulmonary disease (COPD), but there have been no large comprehensive study of metabolomic signatures in COPD that also integrate genetic variants. Fresh frozen plasma from 957 non-Hispanic white subjects in COPDGene was used to quantify 995 metabolites with Metabolon's global metabolomics platform. Metabolite associations with five COPD phenotypes (chronic bronchitis, exacerbation frequency, percent emphysema, post-bronchodilator forced expiratory volume at one second [FEV]/forced vital capacity [FVC], and FEV percent predicted) were assessed.

Identifying Protein-metabolite Networks Associated with COPD Phenotypes.

Chronic obstructive pulmonary disease (COPD) is a disease in which airflow obstruction in the lung makes it difficult for patients to breathe. Although COPD occurs predominantly in smokers, there are still deficits in our understanding of the additional risk factors in smokers. To gain a deeper understanding of the COPD molecular signatures, we used Sparse Multiple Canonical Correlation Network (SmCCNet), a recently developed tool that uses sparse multiple canonical correlation analysis, to integrate proteomic and metabolomic data from the blood of 1008 participants of the COPDGene study to identify novel protein-metabolite networks associated with lung function and emphysema.

Bronchoalveolar Lavage Fluid from COPD Patients Reveals More Compounds Associated with Disease than Matched Plasma.

Smoking causes chronic obstructive pulmonary disease (COPD). Though recent studies identified a COPD metabolomic signature in blood, no large studies examine the metabolome in bronchoalveolar lavage (BAL) fluid, a more direct representation of lung cell metabolism. We performed untargeted liquid chromatography-mass spectrometry (LC-MS) on BAL and matched plasma from 115 subjects from the SPIROMICS cohort.

Unsupervised discovery of phenotype-specific multi-omics networks.

Motivation: Complex diseases often involve a wide spectrum of phenotypic traits. Better understanding of the biological mechanisms relevant to each trait promotes understanding of the etiology of the disease and the potential for targeted and effective treatment plans. There have been many efforts towards omics data integration and network reconstruction, but limited work has examined the incorporation of relevant (quantitative) phenotypic traits.

Interferon Beta Contributes to Astrocyte Activation in the Brain following Reovirus Infection.

Reovirus encephalitis in mice was used as a model system to investigate astrocyte activation (astrogliosis) following viral infection of the brain. Reovirus infection resulted in astrogliosis, as evidenced by increased expression of glial fibrillary acidic protein (GFAP), and the upregulation of genes that have been previously associated with astrocyte activation. Astrocyte activation occurred in regions of the brain that are targeted by reovirus but extended beyond areas of active infection.

Mitochondrial p53 Contributes to Reovirus-Induced Neuronal Apoptosis and Central Nervous System Injury in a Mouse Model of Viral Encephalitis.

Unlabelled: The tumor suppressor p53 plays a critical part in determining cell fate both as a regulator of the transcription of several proapoptotic genes and through its binding interactions with Bcl-2 family proteins at mitochondria. We now demonstrate that p53 protein levels are increased in infected brains during reovirus encephalitis. This increase occurs in the cytoplasm of reovirus-infected neurons and is associated with the activation of caspase 3.

IL-4 confers resistance to IL-27-mediated suppression on CD4+ T cells by impairing signal transducer and activator of transcription 1 signaling.

Background: TH2 cells play a critical role in the pathogenesis of allergic asthma. Established TH2 cells have been shown to resist reprogramming into TH1 cells. The inherent stability of TH2 cells poses a significant barrier to treating allergic diseases.

Antagonistic regulation by the transcription factors C/EBPα and MITF specifies basophil and mast cell fates.

It remains unclear whether basophils and mast cells are derived from a common progenitor. Furthermore, how basophil versus mast cell fate is specified has not been investigated. Here, we have identified a population of granulocyte-macrophage progenitors (GMPs) that were highly enriched in the capacity to differentiate into basophils and mast cells while retaining a limited capacity to differentiate into myeloid cells.

IFN-γ suppresses permissive chromatin remodeling in the regulatory region of the Il4 gene.

In order to develop the most effective T helper type-1 (Th1) immunity, naïve CD4(+) T cells must acquire the capacity to express IFN-γ while silencing T helper type-2 (Th2) cytokine-producing potential. An Il4 gene silencer has been described. However, it is not completely understood how the silencer works.