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. The centenarian DNA had a lower DNA methylation content and a reduced correlation in the methylation status of neighboring cytosine-phosphate-guanine (CpGs) throughout the genome in comparison with the more homogeneously methylated newborn DNA. The more hypomethylated CpGs observed in the centenarian DNA compared with the neonate covered all genomic compartments, such as promoters, exonic, intronic, and intergenic regions. For regulatory regions, the most hypomethylated sequences in the centenarian DNA were present mainly at CpG-poor promoters and in tissue-specific genes, whereas a greater level of DNA methylation was observed in CpG island promoters. We extended the study to a larger cohort of newborn and nonagenarian samples using a 450,000 CpG-site DNA methylation microarray that reinforced the observation of more hypomethylated DNA sequences in the advanced age group. WGBS and 450,000 analyses of middle-age individuals demonstrated DNA methylomes in the crossroad between the newborn and the nonagenarian/centenarian groups. Our study constitutes a unique DNA methylation analysis of the extreme points of human life at a single-nucleotide resolution level.epigenomics | longevity D uring human aging, progressive impairment of organ and tissue functionality leads to an increasing probability of death. The molecular culprits behind this decline in physiological activities remain largely unknown. Studies of transcriptional and genomic associations in distinct tissues have identified several gene families and cellular pathways that might contribute to aging and alter lifespan. These families include the Sirtuins, DNA repair enzymes, insulin-signaling pathway/forkhead transcription factors, apolipoproteins, telomere biology, and oxidative damage/ mitochondrial metabolism (1, 2). Aging-associated mechanisms apparently involve many networks within a given cell. Considering that epigenetic regulation has emerged as a critical driver of cell fate and survival that targets many pathways (3, 4), that epigenetic drift can occur even in genetically identical humans (5, 6), and that DNA methylation patterns are disrupted in a wide range of common human diseases (7-11), we wondered whether individuals at the most extreme points of their lifespan had different DNA methylomes. To address this issue, we used whole-genome bisulfite sequencing (WGBS) (12-16) and a 450,000 CpG DNA methylation microarray to examine the DNA methylation profiles of newborn and nonagenarian/centenarian samples.Results and Discussion WGBS of Newborn and Centenarian DNA. The initial data were generated from the cord blood of a newborn (male Caucasian; NB) and from a centenarian (103-y-old male Caucasian; Y103) using DNA extracted from CD4 + T cells processed through an Illumina G...
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. Next, the analysis of three independent cohorts (totalizing 286 tumours) showed that approximately 65% of the HER2-positive cases have GSDMB gene amplification and protein over-expression. Moreover, GSDMB expression was also linked to poor therapeutic responses in terms of lower relapse free survival and pathologic complete response as well as positive lymph node status and the development of distant metastasis under neoadjuvant and adjuvant treatment settings, respectively. Importantly, GSDMB expression promotes survival to trastuzumab in different HER2-positive breast carcinoma cells, and is associated with trastuzumab resistance phenotype in vivo in Patient Derived Xenografts. In summary, our data identifies the ERBB2 co-amplified and co-expressed gene GSDMB as a critical determinant of poor prognosis and therapeutic response in HER2-positive breast cancer.
Genetic analysis identifies the HMMR gene as a modifier of the breast cancer risk associated with BRCA1 gene mutation, while cell biological analysis of the protein product suggests a function in regulating development of the mammary gland.
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. Diagnostic validation studies were performed using expression profiling data and potential protein biomarkers from prospective clinical studies of 13 diseases. A candidate drug was examined by a treatment study of a mouse model of arthritis, using phenotypic, immunohistochemical, and cellular analyses as read-outs. Results We performed the first systematic analysis of pathways, potential biomarkers, and drug targets in scRNA-seq data from a complex disease, starting with inflamed joints and lymph nodes from a mouse model of arthritis. We found the involvement of hundreds of pathways, biomarkers, and drug targets that differed greatly between cell types. Analyses of scRNA-seq and GWAS data from human rheumatoid arthritis (RA) supported a similar dispersion of pathogenic mechanisms in different cell types. Thus, systems-level approaches to prioritize biomarkers and drugs are needed. Here, we present a prioritization strategy that is based on constructing network models of disease-associated cell types and interactions using scRNA-seq data from our mouse model of arthritis, as well as human RA, which we term multicellular disease models (MCDMs). We find that the network centrality of MCDM cell types correlates with the enrichment of genes harboring genetic variants associated with RA and thus could potentially be used to prioritize cell types and genes for diagnostics and therapeutics. We validated this hypothesis in a large-scale study of patients with 13 different autoimmune, allergic, infectious, malignant, endocrine, metabolic, and cardiovascular diseases, as well as a therapeutic study of the mouse arthritis model. Conclusions Overall, our results support that our strategy has the potential to help prioritize diagnostic and therapeutic targets in human disease. Electronic supplementary material The online version of this article (10.1186/s13073-019-0657-3) contains supplementary material, which is available to authorized users.
Early regulators of disease may increase understanding disease mechanisms, and serve as markers for pre-symptomatic 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 This analytical strategy to identify early regulators of disease by combining gene regulatory networks with GWAS may be generally applicable for functional and clinical studies of early disease development.
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.Results: BioServices is a comprehensive Python framework that provides programmatic access to major bioinformatics Web Services (e.g. KEGG, UniProt, BioModels, ChEMBLdb). Wrapping additional Web Services based either on Representational State Transfer or Simple Object Access Protocol/Web Services Description Language technologies is eased by the usage of object-oriented programming.Availability and implementation: BioServices releases and documentation are available at http://pypi.python.org/pypi/bioservices under a GPL-v3 license.Contact: cokelaer@ebi.ac.uk or bioservices@googlegroups.comSupplementary information: Supplementary data are available at Bioinformatics online.
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 hormonedependent function. Here, to explore the role of RANK signaling once tumors have developed, we use the mouse mammary tumor virus-Polyoma Middle T (MMTV-PyMT), which mimics RANK and RANKL expression patterns seen in human breast adenocarcinomas. Complementary genetic and pharmacologic approaches demonstrate that therapeutic inhibition of RANK signaling drastically reduces the cancer stem cell pool, decreases tumor and metastasis initiation, and enhances sensitivity to chemotherapy. Mechanistically, genome-wide expression analyses show that anti-RANKL therapy promotes lactogenic differentiation of tumor cells. Moreover, RANK signaling in tumor cells negatively regulates the expression of Ap2 transcription factors, and enhances the Wnt agonist Rspo1 and the Sca1-population, enriched in tumor-initiating cells. In addition, we found that expression of TFAP2B and the RANK inhibitor, OPG, in human breast cancer correlate and are associated with relapse-free tumors. These results support the use of RANKL inhibitors to reduce recurrence and metastasis in breast cancer patients based on its ability to induce tumor cell differentiation. Cancer Res; 76(19); 5857-69. Ó2016 AACR.
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