Global Impairment of Immediate-Early Genes Expression in Rett Syndrome Models and Patients Linked to Myelination Defects.

Rett syndrome (RTT) is a severe neurodevelopmental disease caused almost exclusively by mutations to the gene. This disease may be regarded as a synaptopathy, with impairments affecting synaptic plasticity, inhibitory and excitatory transmission and network excitability. The complete understanding of the mechanisms behind how the transcription factor MeCP2 so profoundly affects the mammalian brain are yet to be determined.

A High-Throughput Screening Platform Identifies Novel Combination Treatments for Malignant Peripheral Nerve Sheath Tumors.

Malignant peripheral nerve sheath tumors (MPNST) are soft-tissue sarcomas that are the leading cause of mortality in patients with Neurofibromatosis type 1 (NF1). Single chemotherapeutic agents have shown response rates ranging from 18% to 44% in clinical trials, so there is still a high medical need to identify chemotherapeutic combination treatments that improve clinical prognosis and outcome. We screened a collection of compounds from the NCATS Mechanism Interrogation PlatE (MIPE) library in three MPNST cell lines, using cell viability and apoptosis assays.

A validated single-cell-based strategy to identify diagnostic and therapeutic targets in complex diseases.

Background: Genomic medicine has paved the way for identifying biomarkers and therapeutically actionable targets for complex diseases, but is complicated by the involvement of thousands of variably expressed genes across multiple cell types. Single-cell RNA-sequencing study (scRNA-seq) allows the characterization of such complex changes in whole organs.

Methods: The study is based on applying network tools to organize and analyze scRNA-seq data from a mouse model of arthritis and human rheumatoid arthritis, in order to find diagnostic biomarkers and therapeutic targets.

Correction: Lymphangioleiomyomatosis Biomarkers Linked to Lung Metastatic Potential and Cell Stemness.

[This corrects the article DOI: 10.1371/journal.pone.

Tumor xenograft modeling identifies an association between TCF4 loss and breast cancer chemoresistance.

Understanding the mechanisms of cancer therapeutic resistance is fundamental to improving cancer care. There is clear benefit from chemotherapy in different breast cancer settings; however, knowledge of the mutations and genes that mediate resistance is incomplete. In this study, by modeling chemoresistance in patient-derived xenografts (PDXs), we show that adaptation to therapy is genetically complex and identify that loss of transcription factor 4 (TCF4; also known as ITF2) is associated with this process.

Radioresistance of mesenchymal glioblastoma initiating cells correlates with patient outcome and is associated with activation of inflammatory program.

Glioblastoma (GBM) still remains an incurable disease being radiotherapy (RT) the mainstay treatment. Glioblastoma intra-tumoral heterogeneity and Glioblastoma-Initiating Cells (GICs) challenge the design of effective therapies. We investigated GICs and non-GICs response to RT in a paired model and addressed molecular programs activated in GICs after RT.

Potential Involvement of Type I Interferon Signaling in Immunotherapy in Seasonal Allergic Rhinitis.

Specific immunotherapy (SIT) reverses the symptoms of seasonal allergic rhinitis (SAR) in most patients. Recent studies report type I interferons shifting the balance between type I T helper cell (Th1) and type II T helper cells (Th2) towards Th2 dominance by inhibiting the differentiation of naive T cells into Th1 cells. As SIT is thought to cause a shift towards Th1 dominance, we hypothesized that SIT would alter interferon type I signaling.

Cancer network activity associated with therapeutic response and synergism.

Background: Cancer patients often show no or only modest benefit from a given therapy. This major problem in oncology is generally attributed to the lack of specific predictive biomarkers, yet a global measure of cancer cell activity may support a comprehensive mechanistic understanding of therapy efficacy. We reasoned that network analysis of omic data could help to achieve this goal.

RANK Signaling Blockade Reduces Breast Cancer Recurrence by Inducing Tumor Cell Differentiation.

RANK expression is associated with poor prognosis in breast cancer even though its therapeutic potential remains unknown. RANKL and its receptor RANK are downstream effectors of the progesterone signaling pathway. However, RANK expression is enriched in hormone receptor negative adenocarcinomas, suggesting additional roles for RANK signaling beyond its hormone-dependent function.

Gasdermin B expression predicts poor clinical outcome in HER2-positive breast cancer.

Around, 30-40% of HER2-positive breast cancers do not show substantial clinical benefit from the targeted therapy and, thus, the mechanisms underlying resistance remain partially unknown. Interestingly, ERBB2 is frequently co-amplified and co-expressed with neighbour genes that may play a relevant role in this cancer subtype. Here, using an in silico analysis of data from 2,096 breast tumours, we reveal a significant correlation between Gasdermin B (GSDMB) gene (located 175 kilo bases distal from ERBB2) expression and the pathological and clinical parameters of poor prognosis in HER2-positive breast cancer.

Rankl Impairs Lactogenic Differentiation Through Inhibition of the Prolactin/Stat5 Pathway at Midgestation.

Prolactin and progesterone both orchestrate the proliferation and differentiation of the mammary gland during gestation. Differentiation of milk secreting alveoli depends on the presence of prolactin receptor, the downstream Jak2-Stat5 pathway and the transcription factor Elf5. A strict regulation of Rank signaling is essential for the differentiation of the mammary gland and in particular for alveolar commitment.

A validated gene regulatory network and GWAS identifies early regulators of T cell-associated diseases.

Early regulators of disease may increase understanding of disease mechanisms and serve as markers for presymptomatic diagnosis and treatment. However, early regulators are difficult to identify because patients generally present after they are symptomatic. We hypothesized that early regulators of T cell-associated diseases could be found by identifying upstream transcription factors (TFs) in T cell differentiation and by prioritizing hub TFs that were enriched for disease-associated polymorphisms.

Lymphangioleiomyomatosis Biomarkers Linked to Lung Metastatic Potential and Cell Stemness.

Lymphangioleiomyomatosis (LAM) is a rare lung-metastasizing neoplasm caused by the proliferation of smooth muscle-like cells that commonly carry loss-of-function mutations in either the tuberous sclerosis complex 1 or 2 (TSC1 or TSC2) genes. While allosteric inhibition of the mechanistic target of rapamycin (mTOR) has shown substantial clinical benefit, complementary therapies are required to improve response and/or to treat specific patients. However, there is a lack of LAM biomarkers that could potentially be used to monitor the disease and to develop other targeted therapies.

VAV3 mediates resistance to breast cancer endocrine therapy.

Introduction: Endocrine therapies targeting cell proliferation and survival mediated by estrogen receptor α (ERα) are among the most effective systemic treatments for ERα-positive breast cancer. However, most tumors initially responsive to these therapies acquire resistance through mechanisms that involve ERα transcriptional regulatory plasticity. Herein we identify VAV3 as a critical component in this process.

Integrated genomic and prospective clinical studies show the importance of modular pleiotropy for disease susceptibility, diagnosis and treatment.

Background: Translational research typically aims to identify and functionally validate individual, disease-specific genes. However, reaching this aim is complicated by the involvement of thousands of genes in common diseases, and that many of those genes are pleiotropic, that is, shared by several diseases.

Methods: We integrated genomic meta-analyses with prospective clinical studies to systematically investigate the pathogenic, diagnostic and therapeutic roles of pleiotropic genes.

Integrating gene expression and epidemiological data for the discovery of genetic interactions associated with cancer risk.

Dozens of common genetic variants associated with cancer risk have been identified through genome-wide association studies (GWASs). However, these variants only explain a modest fraction of the heritability of disease. The missing heritability has been attributed to several factors, among them the existence of genetic interactions (G × G).

BioServices: a common Python package to access biological Web Services programmatically.

Motivation: Web interfaces provide access to numerous biological databases. Many can be accessed to in a programmatic way thanks to Web Services. Building applications that combine several of them would benefit from a single framework.

Cancer develops, progresses and responds to therapies through restricted perturbation of the protein-protein interaction network.

The products of genes mutated or differentially expressed in cancer tend to occupy central positions within the network of protein-protein interactions, or the interactome network. Integration of different types of gene and protein relationships has considerably increased the understanding of the mechanisms of carcinogenesis, while also enhancing the applicability of expression signatures. In this scenario, however, it remains unknown how cancer develops, progresses and responds to therapies in a potentially controlled manner at the systems level.

Distinct DNA methylomes of newborns and centenarians.

Human aging cannot be fully understood in terms of the constrained genetic setting. Epigenetic drift is an alternative means of explaining age-associated alterations. To address this issue, we performed whole-genome bisulfite sequencing (WGBS) of newborn and centenarian genomes.

Tools for protein-protein interaction network analysis in cancer research.

As cancer is a complex disease, the representation of a malignant cell as a protein-protein interaction network (PPIN) and its subsequent analysis can provide insight into the behaviour of cancer cells and lead to the discovery of new biomarkers. The aim of this review is to help life-science researchers without previous computer programming skills to extract meaningful biological information from such networks, taking advantage of easy-to-use, public bioinformatics tools. It is structured in four parts: the first section describes the pipeline of consecutive steps from network construction to biological hypothesis generation.

Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome.

DNA methylation is the most studied epigenetic mark and CpG methylation is central to many biological processes and human diseases. Since cancer has highlighted the contribution to disease of aberrant DNA methylation patterns, such as the presence of promoter CpG island hypermethylation-associated silencing of tumor suppressor genes and global DNA hypomethylation defects, their importance will surely become apparent in other pathologies. However, advances in obtaining comprehensive DNA methylomes are hampered by the high cost and time-consuming aspects of the single nucleotide methods currently available for whole genome DNA methylation analyses.

Exploring the link between germline and somatic genetic alterations in breast carcinogenesis.

Recent genome-wide association studies (GWASs) have identified candidate genes contributing to cancer risk through low-penetrance mutations. Many of these genes were unexpected and, intriguingly, included well-known players in carcinogenesis at the somatic level. To assess the hypothesis of a germline-somatic link in carcinogenesis, we evaluated the distribution of somatic gene labels within the ordered results of a breast cancer risk GWAS.