Leveraging gene expression subgroups to classify DLBCL patients and select for clinical benefit from a novel agent

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, commonly described by cell-of-origin (COO) molecular subtypes. We sought to identify novel patient subgroups through an unsupervised analysis of a large public dataset of gene expression profiles from newly diagnosed de novo DLBCL patients, yielding 2 biologically distinct subgroups characterized by differences in the tumor microenvironment. Pathway analysis and immune deconvolution algorithms identified higher B-cell content and a strong proliferative signal in subgroup A and enriched T-cell, macrophage, and immune/inflammatory signals in subgroup B, reflecting similar biology to published DLBCL stratification research. A gene expression classifier, featuring 26 gene expression scores, was derived from the public dataset to discriminate subgroup A (classifier-negative, immune-low) and subgroup B (classifier-positive, immune-high) patients. Subsequent application to an independent series of diagnostic biopsies replicated the subgroups, with immune cell composition confirmed via immunohistochemistry. Avadomide, a CRL4CRBN E3 ubiquitin ligase modulator, demonstrated clinical activity in relapsed/refractory DLBCL patients, independent of COO subtypes. Given the immunomodulatory activity of avadomide and the need for a patient-selection strategy, we applied the gene expression classifier to pretreatment biopsies from relapsed/refractory DLBCL patients receiving avadomide (NCT01421524). Classifier-positive patients exhibited an enrichment in response rate and progression-free survival of 44% and 6.2 months vs 19% and 1.6 months for classifier-negative patients (hazard ratio, 0.49; 95% confidence interval, 0.280-0.86; P = .0096). The classifier was not prognostic for rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone or salvage immunochemotherapy. The classifier described here discriminates DLBCL tumors based on tumor and nontumor composition and has potential utility to enrich for clinical response to immunomodulatory agents, including avadomide

Calibration of the Transport Parameters of a Local Problem of Water Quality in Igap\'o I Lake

The calibration of a model refers to the process by which one can estimate some parameters by comparisons with observed data. Due to the dynamical nature of the environment, variations between predicted and observed values occur. Thus, the environmental parameters may vary due to random temperature changes, time of discharge flow, time of the day, and other conditions. Such variations can be minimized by identifying and optimizing some parameters of the transport model, like the values of diffusion coefficients in x and y directions and the kinetic parameter that describes the process of removing pollutants. This paper presents results concerning the calibration of transport parameters for two-dimensional problems of water quality (fecal coliform control) at Igap\'o I Lake, located in Londrina, Paran\'a, Brazil. Thus, the convection-diffusion-reaction equation, which describes mathematically the process studied in this work, is resolved by a semidiscrete finite element method (SUPG) which combines finite differences in time and finite elements in space.Comment: 8 Pages, 3 figures, 2 tables, XVIII International Conference on Water Resources CMWR 2010 - J. Carrera (Ed) - CIMNE, Barcelona 201

Internal representations of smell in the Drosophila brain

Recent advances in sensory neuroscience using Drosophila olfaction as a model system have revealed brain maps representing the external world. Once we understand how the brain's built-in capability generates the internal olfactory maps, we can then elaborate how the brain computes and makes decision to elicit complex behaviors. Here, we review current progress in mapping Drosophila olfactory circuits and discuss their relationships with innate olfactory behaviors