Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study

BACKGROUND: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expression. Because of the complexity and the high dimensionality of microarray gene expression profiles, the dimensional reduction of raw expression data and the feature selections necessary for, for example, classification of disease samples remains a challenge. To solve the problem we propose a two-level analysis. First self-organizing map (SOM) is used. SOM is a vector quantization method that simplifies and reduces the dimensionality of original measurements and visualizes individual tumor sample in a SOM component plane. Next, hierarchical clustering and K-means clustering is used to identify patterns of gene expression useful for classification of samples. RESULTS: We tested the two-level analysis on public data from diffuse large B-cell lymphomas. The analysis easily distinguished major gene expression patterns without the need for supervision: a germinal center-related, a proliferation, an inflammatory and a plasma cell differentiation-related gene expression pattern. The first three patterns matched the patterns described in the original publication using supervised clustering analysis, whereas the fourth one was novel. CONCLUSIONS: Our study shows that by using SOM as an intermediate step to analyze genome-wide gene expression data, the gene expression patterns can more easily be revealed. The "expression display" by the SOM component plane summarises the complicated data in a way that allows the clinician to evaluate the classification options rather than giving a fixed diagnosis

BayesPI-BAR2: A New Python Package for Predicting Functional Non-coding Mutations in Cancer Patient Cohorts

Most of somatic mutations in cancer occur outside of gene coding regions. These mutations may disrupt the gene regulation by affecting protein-DNA interaction. A study of these disruptions is important in understanding tumorigenesis. However, current computational tools process DNA sequence variants individually, when predicting the effect on protein-DNA binding. Thus, it is a daunting task to identify functional regulatory disturbances among thousands of mutations in a patient. Previously, we have reported and validated a pipeline for identifying functional non-coding somatic mutations in cancer patient cohorts, by integrating diverse information such as gene expression, spatial distribution of the mutations, and a biophysical model for estimating protein binding affinity. Here, we present a new user-friendly Python package BayesPI-BAR2 based on the proposed pipeline for integrative whole-genome sequence analysis. This may be the first prediction package that considers information from both multiple mutations and multiple patients. It is evaluated in follicular lymphoma and skin cancer patients, by focusing on sequence variants in gene promoter regions. BayesPI-BAR2 is a useful tool for predicting functional non-coding mutations in whole genome sequencing data: it allows identification of novel transcription factors (TFs) whose binding is altered by non-coding mutations in cancer. BayesPI-BAR2 program can analyze multiple datasets of genome-wide mutations at once and generate concise, easily interpretable reports for potentially affected gene regulatory sites. The package is freely available at http://folk.uio.no/junbaiw/BayesPI-BAR2/

Application of new probabilistic graphical models in the genetic regulatory networks studies

This paper introduces two new probabilistic graphical models for reconstruction of genetic regulatory networks using DNA microarray data. One is an Independence Graph (IG) model with either a forward or a backward search algorithm and the other one is a Gaussian Network (GN) model with a novel greedy search method. The performances of both models were evaluated on four MAPK pathways in yeast and three simulated data sets. Generally, an IG model provides a sparse graph but a GN model produces a dense graph where more information about gene-gene interactions is preserved. Additionally, we found two key limitations in the prediction of genetic regulatory networks using DNA microarray data, the first is the sufficiency of sample size and the second is the complexity of network structures may not be captured without additional data at the protein level. Those limitations are present in all prediction methods which used only DNA microarray data.Comment: 38 pages, 3 figure

Deltex-1 mutations predict poor survival in diffuse large B-cell lymphoma

Non peer reviewe

Distinct gene expression profiles in different B-cell compartments in human peripheral lymphoid organs

BACKGROUND: There are three major B-cell compartments in peripheral lymphoid organs: the germinal center (GC), the mantle zone (MNZ) and the marginal zone (MGZ). Unique sets of B-cells reside in these compartments, and they have specific functional roles in humoral immune response. MNZ B cells are naïve cells in a quiescent state and may participate in GC reactions upon proper stimulation. The adult splenic MGZ contains mostly memory B cells and is also known to provide a rapid response to particulate antigens. The GC B-cells proliferate rapidly and undergo selection and affinity maturation. The B-cell maturational process is accompanied by changes in the expression of cell-surface and intracellular proteins and requires signals from the specialized microenvironments. RESULTS: We performed laser microdissection of the three compartments for gene expression profiling by cDNA microarray. The transcriptional program of the GC was dominated by upregulation of genes associated with proliferation and DNA repair or recombination. The MNZ and MGZ showed increased expression of genes promoting cellular quiescence. The three compartments also revealed distinct repertoires of apoptosis-associated genes, chemokines and chemokine receptors. The MNZ and GC showed upregulation of CCL20 and CCL18 respectively. The MGZ was characterized by high expression of many chemokines genes e.g. CXCL12, CCL3, CCL14 and IFN-associated genes, consistent with its role in rapid response to infections. A stromal signature was identified including genes associated with macrophages or with synthesis of extracellular matrix and genes that influenced lymphocyte migration and survival. Differentially expressed genes that did not belong to the above categories include the well characterized BCL6 and CD10 and many others whose function is not known. CONCLUSIONS: Transcriptional profiling of B-cell compartments has identified groups of genes involved in critical molecular and cellular events that affect proliferation, survival migration, and differentiation of the cells. The gene expression study of normal B-cell compartments may additionally contribute to our understanding of the molecular abnormalities of the corresponding lymphoid tumors

MicroRNAs regulate key cell survival pathways and mediate chemosensitivity during progression of diffuse large B- cell lymphoma

Despite better therapeutic options and improved survival of diffuse large B-cell lymphoma (DLBCL), 30-40% of the patients experience relapse or have primary refractory disease with a dismal prognosis. To identify biological correlates for treatment resistance, we profiled microRNAs (miRNAs) of matched primary and relapsed DLBCL by next-generation sequencing. Altogether 492 miRNAs were expressed in the DLBCL samples. Thirteen miRNAs showed significant differential expression between primary and relapse specimen pairs. Integration of the differentially expressed miRNAs with matched mRNA expression profiles identified highly anti-correlated, putative targets, which were significantly enriched in cancer-associated pathways, including phosphatidylinositol (PI)), mitogen-activated protein kinase (MAPK), and B-cell receptor (BCR) signaling. Expression data suggested activation of these pathways during disease progression, and functional analyses validated that miR-370-3p, miR-381-3p, and miR-409-3p downregulate genes on the PI, MAPK, and BCR signaling pathways, and enhance chemosensitivity of DLBCL cells in vitro. High expression of selected target genes, that is, PIP5K1 and IMPA1, was found to be associated with poor survival in two independent cohorts of chemoimmunotherapy-treated patients (n = 92 and n = 233). Taken together, our results demonstrate that differentially expressed miRNAs contribute to disease progression by regulating key cell survival pathways and by mediating chemosensitivity, thus representing potential novel therapeutic targets.Peer reviewe

Pulsed chemical vapor deposition of conformal GeSe for application as an OTS selector

The ovonic threshold switch (OTS) selector based on the voltage snapback of amorphous chalcogenides has received tremendous attention as it provides several desirable characteristics such as bidirectional switching, a controllable threshold voltage, high drive currents, and low leakage currents. GeSe is a well-known OTS selector that fulfills all the requirements imposed by future high-density storage class memories. Here, we report on pulsed chemical vapor deposition (CVD) of amorphous GeSe by using GeCl2 center dot C4H8O2 as a Ge source and two different Se sources namely bis-trimethylsilylselenide ((CH3)(3)Si)(2)Se (TMS)(2)Se and bis-triethylsilylselenide ((C2H5)(3)Si)(2)Se (TES)(2)Se. We utilized total reflection X-ray fluorescence (TXRF) to study the kinetics of precursor adsorption on the Si substrate. GeCl2 center dot C4H8O2 precursor adsorption on a 300 mm Si substrate showed under-dosing due to limited precursor supply. On the other hand, the Se precursor adsorption is limited by low reaction efficiency as we learned from a better within-wafer uniformity. Se precursors need Cl sites (from Ge precursor) for precursor ligand exchange reactions. Adsorption of (TMS)(2)Se is found to be much faster than (TES)(2)Se on a precoated GeClx layer. Atomic layer deposition (ALD) tests with GeCl2 center dot C4H8O2 and (TMS)(2)Se revealed that the growth per cycle (GPC) decreases with the introduction of purge steps in the ALD cycle, whereas a higher GPC is obtained in pulsed-CVD mode without purges. Based on this basic understanding of the process, we developed a pulsed CVD growth recipe (GPC = 0.3 angstrom per cycle) of GeSe using GeCl2 center dot C4H8O2 and (TMS)(2)Se at a reactor temperature of 70 degrees C. The 20 nm GeSe layer is amorphous and stoichiometric with traces of chlorine and carbon impurities. The film has a roughness of similar to 0.3 nm and it starts to crystallize at a temperature of similar to 370 degrees C. GeSe grown on 3D test structures showed excellent film conformality

Prognostic influence of macrophages in patients with diffuse large B-cell lymphoma : a correlative study from a Nordic phase II trial

Peer reviewe

CubeSpec, A Mission Overview

CubeSpec is an in-orbit demonstration CubeSat mission in the ESA technology programme, developed and funded in Belgium. The goal of the mission is to demonstrate high-spectral-resolution astronomical spectroscopy from a 6-unit CubeSat. The prime science demonstration case for the in-orbit demonstration mission is to unravel the interior of massive stars using asteroseismology by high-cadance monitoring of the variations in spectral line profiles during a few months. The technological challenges are numerous. The 10x20cm aperture telescope and echelle spectrometer have been designed to fit in a 10x10x20cm volume. Under low-Earth orbit thermal variations, maintaining the fast telescope focus and spectrometer alignment is achieved via an athermal design. Straylight rejection and thermal shielding from the Sun and Earth infrared flux is achieved via deploying Earth and Sunshades. The narrow spectrometer slit requires arcsecond-level pointing stability using a performant 3-axis wheel stabilised attitude control system with star tracker augmented with a fine beam steering mechanism controlled in closed loop with a guiding sensor. The high cadence, long-term monitoring requirement of the mission poses specific requirements on the orbit and operational scenarios to enable the required sky visibility. CubeSpec is starting the implementation phase, with a planned launch early 2024