24 research outputs found
Gene expression analysis reveals a strong signature of an interferon induced pathway in childhood lymphoblastic leukemia as well as in breast and ovarian cancer
On the basis of epidemiological studies, infection was suggested to play a
role in the etiology of human cancer. While for some cancers such a role was
indeed demonstrated, there is no direct biological support for the role of
viral pathogens in the pathogenesis of childhood leukemia. Using a novel
bioinformatic tool, that alternates between clustering and standard statistical
methods of analysis, we performed a "double blind" search of published gene
expression data of subjects with different childhood ALL subtypes, looking for
unanticipated partitions of patients, induced by unexpected groups of genes
with correlated expression. We discovered a group of about thirty genes,
related to the interferon response pathway, whose expression levels divide the
ALL samples into two subgroups; high in 50, low in 285 patients. Leukemic
subclasses prevalent in early childhood (the age most susceptible to infection)
are over-represented in the high expression subgroup. Similar partitions,
induced by the same genes, were found also in breast and ovarian cancer but not
in lung cancer, prostate cancer and lymphoma. About 40% of breast cancer
samples expressed the "interferon- related" signature. It is of interested that
several studies demonstrated MMTV-like sequences in about 40% of breast cancer
samples. Our discovery of an unanticipated strong signature of an interferon
induced pathway provides molecular support for a role for either inflammation
or viral infection in the pathogenesis of childhood leukemia as well as breast
and ovarian cancer
The promoters of human cell cycle genes integrate signals from two tumor suppressive pathways during cellular transformation
Deciphering regulatory events that drive malignant transformation represents
a major challenge for systems biology. Here we analyzed genome-wide
transcription profiling of an in-vitro transformation process. We focused on a
cluster of genes whose expression levels increased as a function of p53 and
p16INK4A tumor suppressors inactivation. This cluster predominantly consists of
cell cycle genes and constitutes a signature of a diversity of cancers. By
linking expression profiles of the genes in the cluster with the dynamic
behavior of p53 and p16INK4A, we identified a promoter architecture that
integrates signals from the two tumor suppressive channels and that maps their
activity onto distinct levels of expression of the cell cycle genes, which in
turn, correspond to different cellular proliferation rates. Taking components
of the mitotic spindle as an example, we experimentally verified our
predictions that p53-mediated transcriptional repression of several of these
novel targets is dependent on the activities of p21, NFY and E2F. Our study
demonstrates how a well-controlled transformation process allows linking
between gene expression, promoter architecture and activity of upstream
signaling molecules.Comment: To appear in Molecular Systems Biolog
Wide-Scale Analysis of Human Functional Transcription Factor Binding Reveals a Strong Bias towards the Transcription Start Site
We introduce a novel method to screen the promoters of a set of genes with
shared biological function, against a precompiled library of motifs, and find
those motifs which are statistically over-represented in the gene set. The gene
sets were obtained from the functional Gene Ontology (GO) classification; for
each set and motif we optimized the sequence similarity score threshold,
independently for every location window (measured with respect to the TSS),
taking into account the location dependent nucleotide heterogeneity along the
promoters of the target genes. We performed a high throughput analysis,
searching the promoters (from 200bp downstream to 1000bp upstream the TSS), of
more than 8000 human and 23,000 mouse genes, for 134 functional Gene Ontology
classes and for 412 known DNA motifs. When combined with binding site and
location conservation between human and mouse, the method identifies with high
probability functional binding sites that regulate groups of biologically
related genes. We found many location-sensitive functional binding events and
showed that they clustered close to the TSS. Our method and findings were put
to several experimental tests. By allowing a "flexible" threshold and combining
our functional class and location specific search method with conservation
between human and mouse, we are able to identify reliably functional TF binding
sites. This is an essential step towards constructing regulatory networks and
elucidating the design principles that govern transcriptional regulation of
expression. The promoter region proximal to the TSS appears to be of central
importance for regulation of transcription in human and mouse, just as it is in
bacteria and yeast.Comment: 31 pages, including Supplementary Information and figure
GEView (Gene Expression View) Tool for Intuitive and High Accessible Visualization of Expression Data for Non-Programmer Biologists
Gene Expression Meta-Analysis of Cerebellum Samples Supports the FKBP5 Gene-Environment Interaction Model for Schizophrenia
Background: One of the most studied molecular models of gene-environment interactions is that of FKBP5, which has been shown to interact with childhood adversity to increase the risk of psychiatric disorders, and has been implicated in schizophrenia. While the model predicts up-regulation of FKBP5, previous brain samples gene expression studies yielded inconsistent results. Methods: We performed a systematic gene expression meta-analysis of FKBP5 and NR3C1, a glucocorticoid receptor inhibited by FKBP5, in cerebellum samples of patients with schizophrenia. The gene expression databases GEO, SMRI and those of NIMH were searched, and out of six screened datasets, three were eligible for the meta-analysis (overall 69 with schizophrenia and 78 controls). Results: We detected up-regulation of FKBP5 and down-regulation of NR3C1 in schizophrenia, and a negative correlation between their expression patterns. Correlation analysis suggested that the detected differential expression did not result from potential confounding factors. Conclusions: Our results give significant support to the FKBP5 gene-environment interaction model for schizophrenia, which provides a molecular mechanism by which childhood adversity is involved in the development of the disorder. To explore FKBP5ās potential as a therapeutic target, a mapping of its differential expression patterns in different brain regions of schizophrenia patients is needed
GEView (Gene Expression View) Tool for Intuitive and High Accessible Visualization of Expression Data for Non-Programmer Biologists
This article describes how the last decade has been characterized by the production of huge amounts of different types of biological data. Following that, a flood of bioinformatics tools have been published. However, many of these tools are commercial, or require computational skills. In addition, not all tools provide intuitive and highly accessible visualization of the results. The authors have developed GEView (Gene Expression View), which is a free, user-friendly tool harboring several existing algorithms and statistical methods for the analysis of high-throughput gene, microRNA or protein expression data. It can be used to perform basic analysis such as quality control, outlier detection, batch correction and differential expression analysis, through a single intuitive graphical user interface. GEView is unique in its simplicity and highly accessible visualization it provides. Together with its basic and intuitive functionality it allows Bio-Medical scientists with no computational skills to independently analyze and visualize high-throughput data produced in their own labs
An accessible database for mouse and human whole transcriptome qPCR primers
ABSTRACT Motivation: Real time quantitative polymerase chain reaction (qPCR) is an important tool in quantitative studies of DNA and RNA molecules; especially in transcriptome studies, where different primer combinations allow identification of specific transcripts such as splice variants or precursor messenger RNA. Several softwares that implement various rules for optimal primer design are available. Nevertheless, as designing qPCR primers needs to be done manually, the repeated task is tedious, time consuming and prone to errors. Results: We used a set of rules to automatically design all possible exon-exon and intron-exon junctions in the human and mouse transcriptomes. The resulting database is included as a track in the UCSC genome browser, making it widely accessible and easy to use