Identification of ADGRE5 as discriminating MYC target between Burkitt lymphoma and diffuse large B-cell lymphoma.

Background: MYC is a heterogeneously expressed transcription factor that plays a multifunctional role in many biological processes such as cell proliferation and differentiation. It is also associated with many types of cancer including the malignant lymphomas. There are two types of aggressive B-cell lymphoma, namely Burkitt lymphoma (BL) and a subgroup of diffuse large cell lymphoma (DLBCL), which both carry MYC translocations and overexpress MYC but both differ significantly in their clinical outcome.

Cooperative STAT/NF-κB signaling regulates lymphoma metabolic reprogramming and aberrant GOT2 expression.

Knowledge of stromal factors that have a role in the transcriptional regulation of metabolic pathways aside from c-Myc is fundamental to improvements in lymphoma therapy. Using a MYC-inducible human B-cell line, we observed the cooperative activation of STAT3 and NF-κB by IL10 and CpG stimulation. We show that IL10 + CpG-mediated cell proliferation of MYC cells depends on glutaminolysis.

External calibration with Drosophila whole-cell spike-ins delivers absolute mRNA fold changes from human RNA-Seq and qPCR data.

Gene expression measurements are typically performed on a fixed-weight aliquot of RNA, which assumes that the total number of transcripts per cell stays nearly constant across all conditions. In cases where this assumption does not hold (e.g.

Comprehensive Metaboproteomics of Burkitt's and Diffuse Large B-Cell Lymphoma Cell Lines and Primary Tumor Tissues Reveals Distinct Differences in Pyruvate Content and Metabolism.

Burkitt's lymphoma (BL) and diffuse large B-cell lymphoma (DLBCL) are pathologically and clinically distinct subtypes of aggressive non-Hodgkin B-cell lymphoma. To learn more about their biology, we employed metabolomic and proteomic methods to study both established cell lines as well as cryopreserved and formalin-fixed paraffin-embedded (FFPE) tissue sections of BL and DLBCL. Strikingly, NMR analyses revealed DLBCL cell lines to produce and secrete significantly (p = 1.

Synergy of interleukin 10 and toll-like receptor 9 signalling in B cell proliferation: Implications for lymphoma pathogenesis.

A network of autocrine and paracrine signals defines B cell homeostasis and is thought to be involved in transformation processes. Investigating interactions of these microenvironmental factors and their relation to proto-oncogenes as c-Myc (MYC) is fundamental to understand the biology of B cell lymphoma. Therefore, B cells with conditional MYC expression were stimulated with CD40L, insulin-like growth factor 1, α-IgM, Interleukin-10 (IL10) and CpG alone or in combination.

Natural variation of root exudates in Arabidopsis thaliana-linking metabolomic and genomic data.

Many metabolomics studies focus on aboveground parts of the plant, while metabolism within roots and the chemical composition of the rhizosphere, as influenced by exudation, are not deeply investigated. In this study, we analysed exudate metabolic patterns of Arabidopsis thaliana and their variation in genetically diverse accessions. For this project, we used the 19 parental accessions of the Arabidopsis MAGIC collection.

A statistical approach to virtual cellular experiments: improved causal discovery using accumulation IDA (aIDA).

Motivation: We address the following question: Does inhibition of the expression of a gene X in a cellular assay affect the expression of another gene Y? Rather than inhibiting gene X experimentally, we aim at answering this question computationally using as the only input observational gene expression data. Recently, a new statistical algorithm called Intervention calculus when the Directed acyclic graph is Absent (IDA), has been proposed for this problem. For several biological systems, IDA has been shown to outcompete regression-based methods with respect to the number of true positives versus the number of false positives for the top 5000 predicted effects.

Data Normalization of (1)H NMR Metabolite Fingerprinting Data Sets in the Presence of Unbalanced Metabolite Regulation.

Data normalization is an essential step in NMR-based metabolomics. Conducted properly, it improves data quality and removes unwanted biases. The choice of the appropriate normalization method is critical and depends on the inherent properties of the data set in question.

BiNChE: a web tool and library for chemical enrichment analysis based on the ChEBI ontology.

Background: Ontology-based enrichment analysis aids in the interpretation and understanding of large-scale biological data. Ontologies are hierarchies of biologically relevant groupings. Using ontology annotations, which link ontology classes to biological entities, enrichment analysis methods assess whether there is a significant over or under representation of entities for ontology classes.