Purpose Biologic heterogeneity is a feature of diffuse large B-cell lymphoma (DLBCL), and the existence of a subgroup with poor prognosis and phenotypic proximity to Burkitt lymphoma is well known. Conventional cytogenetics identifies some patients with rearrangements of MYC and BCL2 and/or BCL6 (double-hit lymphomas) who are increasingly treated with more intensive chemotherapy, but a more biologically coherent and clinically useful definition of this group is required. Patients and Methods We defined a molecular high-grade (MHG) group by applying a gene expression–based classifier to 928 patients with DLBCL from a clinical trial that investigated the addition of bortezomib to standard rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) therapy. The prognostic significance of MHG was compared with existing biomarkers. We performed targeted sequencing of 70 genes in 400 patients and explored molecular pathology using gene expression signature databases. Findings were validated in an independent data set. Results The MHG group comprised 83 patients (9%), with 75 in the cell-of-origin germinal center B-cell-like group. MYC rearranged and double-hit groups were strongly over-represented in MHG but comprised only one half of the total. Gene expression analysis revealed a proliferative phenotype with a relationship to centroblasts. Progression-free survival rate at 36 months after R-CHOP in the MHG group was 37% (95% CI, 24% to 55%) compared with 72% (95% CI, 68% to 77%) for others, and an analysis of treatment effects suggested a possible positive effect of bortezomib. Double-hit lymphomas lacking the MHG signature showed no evidence of worse outcome than other germinal center B-cell-like cases. Conclusion MHG defines a biologically coherent high-grade B-cell lymphoma group with distinct molecular features and clinical outcomes that effectively doubles the size of the poor-prognosis, double-hit group. Patients with MHG may benefit from intensified chemotherapy or novel targeted therapies.

This article describes the implementation of a new docking approach. The method uses a Tabu search methodology to dock flexibly ligand molecules into rigid receptor structures. It uses an empirical objective function with a small number of physically based terms derived from fitting experimental binding affinities for crystallographic complexes. This means that docking energies produced by the searching algorithm provide direct estimates of the binding affinities of the ligands. The method has been tested on 50 ligand-receptor complexes for which the experimental binding affinity and binding geometry are known. All water molecules are removed from the structures and ligand molecules are minimized in vacuo before docking. The lowest energy geometry produced by the docking protocol is within 1.5 A root-mean square of the experimental binding mode for 86% of the complexes. The lowest energies produced by the docking are in fair agreement with the known free energies of binding for the ligands.

The mathematical structures known as Petri Nets have recently become the focus of much research effort in both the structural and quantitative analysis of all kinds of biological networks. This review provides a very brief summary of these interesting new research directions.

The value of genome-wide over targeted driver analyses for predicting clinical outcomes of cancer patients is debated. Here, we report the whole-genome sequencing of 485 chronic lymphocytic leukemia patients enrolled in clinical trials as part of the United Kingdom’s 100,000 Genomes Project. We identify an extended catalog of recurrent coding and noncoding genetic mutations that represents a source for future studies and provide the most complete high-resolution map of structural variants, copy number changes and global genome features including telomere length, mutational signatures and genomic complexity. We demonstrate the relationship of these features with clinical outcome and show that integration of 186 distinct recurrent genomic alterations defines five genomic subgroups that associate with response to therapy, refining conventional outcome prediction. While requiring independent validation, our findings highlight the potential of whole-genome sequencing to inform future risk stratification in chronic lymphocytic leukemia.

with bulky disease were not put at risk by this PET-based omission of radiotherapy, a planned interim analysis was performed. 1,4,14,28,42,56,91,126,175, 238). Pts. with bulk (> = 7.5 cm) that remained PET-positive after chemotherapy were assigned to RT (39.6 Gy), while PET-negative bulks were observed.Results : Conclusion: Radiotherapy can be spared in PET-negative bulks, resulting in a 42% reduction of patients who receive radiotherapy without compromising the outcome of these patients. Supported by Amgen, Roche, Spectrum.

Summary Gene coexpression analysis refers to the discovery of sets of genes which exhibit similar expression patterns across multiple transcriptomic data sets, such as microarray experiment data of public repositories. Arabidopsis Coexpression Tool (ACT), a gene coexpression analysis web tool for Arabidopsis thaliana , identifies genes which are correlated to a driver gene. Primary microarray data from ATH1 Affymetrix platform were processed with Single-Channel Array Normalization algorithm and combined to produce a coexpression tree which contains ∼21,000 A. thaliana genes. ACT was developed to present subclades of coexpressed genes, as well as to perform gene set enrichment analysis, being unique in revealing enriched transcription factors targeting coexpressed genes. ACT offers a simple and user-friendly interface producing working hypotheses which can be experimentally verified for the discovery of gene partnership, pathway membership, and transcriptional regulation. ACT analyses have been successful in identifying not only genes with coordinated ubiquitous expressions but also genes with tissue-specific expressions.

Recurrent mutational activation of the MAP kinase pathway in plasma cell myeloma implicates growth factor-like signaling responses in the biology of antibody secreting cells (ASCs). Physiological ASCs survive in niche microenvironments, but how niche signals are propagated and integrated is poorly understood. Here we dissect such a response in human ASCs using an in vitro model. Applying time course expression data and parsimonious gene correlation networking analysis (PGCNA), we map expression changes that occur during the maturation of proliferating plasmablast to quiescent plasma cell under survival conditions including the potential niche signal TGFB3. This analysis demonstrates a convergent pattern of differentiation, linking UPR/ER stress to secretory optimization, co-ordinated with cell cycle exit. TGFB3 supports ASC survival while having a limited effect on gene expression including up-regulation of CXCR4. This is associated with a significant shift in response to SDF1 in ASCs with amplified ERK1/2 activation, growth factor-like immediate early gene regulation and EGR1 protein expression. Similarly, ASCs responding to survival conditions initially induce partially overlapping sets of immediate early genes, without sustaining the response. Thus, in human ASCs growth factor-like gene regulation is transiently imposed by niche signals but is not sustained during subsequent survival and maturation.

Organismal proteostasis is maintained by intercellular signaling processes including cell nonautonomous stress responses such as transcellular chaperone signaling (TCS). When TCS is activated upon tissue-specific knockdown of hsp-90 in the Caenorhabditis elegans intestine, heat-inducible hsp-70 is induced in muscle cells at the permissive temperature resulting in increased heat stress resistance and lifespan extension. However, our understanding of the molecular mechanism and signaling factors mediating transcellular activation of hsp-70 expression from one tissue to another is still in its infancy. Here, we conducted a combinatorial approach using transcriptome RNA-Seq profiling and a forward genetic mutagenesis screen to elucidate how stress signaling from the intestine to the muscle is regulated. We find that the TCS-mediated “gut-to-muscle” induction of hsp-70 expression is suppressed by HSF-1 and instead relies on transcellular-X-cross-tissue (txt) genes. We identify a key role for the PDZ-domain guanylate cyclase txt-1 and the homeobox transcription factor ceh-58 as signaling hubs in the stress receiving muscle cells to initiate hsp-70 expression and facilitate TCS-mediated heat stress resistance and lifespan extension. Our results provide a new view on cell-nonautonomous regulation of “inter-tissue” stress responses in an organism that highlight a key role for the gut. Our data suggest that the HSF-1–mediated heat shock response is switched off upon TCS activation, in favor of an intercellular stress-signaling route to safeguard survival.