This SuperSeries is composed of the SubSeries listed below.
Concurrent gene signatures for han chinese breast cancers.
Specimen part
View SamplesThe interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival. Distributions of signature genes were strongly associated with chromosomal location: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer.
Concurrent gene signatures for han chinese breast cancers.
Specimen part
View SamplesHuman survival from injury requires an appropriate inflammatory and immune response. We describe the circulating leukocyte transcriptome after severe trauma and show that the severe stress produce a global
A genomic storm in critically injured humans.
Sex, Age, Specimen part
View SamplesBlood was sampled from severe burns patients over time as well as healthy subjects. Genome-wide expression analyses were conducted using the Affymetrix U133 plus 2.0 GeneChip.
Genomic responses in mouse models poorly mimic human inflammatory diseases.
Sex, Age, Specimen part
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Deregulation of ribosomal protein expression and translation promotes breast cancer metastasis.
Specimen part, Cell line, Treatment, Subject
View SamplesPhysiological, anatomical, and clinical laboratory analytic scoring systems (APACHE, Injury Severity Score (ISS)) have been utilized, with limited success, to predict outcome following injury. We hypothesized that a peripheral blood leukocyte gene expression score could predict outcome, including multiple organ failure, following severe blunt trauma.
A genomic score prognostic of outcome in trauma patients.
Sex, Age
View SamplesWe report here the genes that are sequentially expressed in white blood cells from blood and spleen at 2 hours, 2 day,3 days, and 7 days after burn and sham injury or trauma-hemorrhage (T-H) and sham T-H. Includes WBC treated with LPS for 2 hours and 1 day.
Comparison of longitudinal leukocyte gene expression after burn injury or trauma-hemorrhage in mice.
Specimen part, Treatment, Time
View SamplesThis SuperSeries is composed of the SubSeries listed below.
STAT6 transcription factor is a facilitator of the nuclear receptor PPARγ-regulated gene expression in macrophages and dendritic cells.
Specimen part, Treatment, Subject, Time
View SamplesOligonucleotide and complementary DNA microarrays are being used to subclassify histologically similar tumours, monitor disease progress, and individualize treatment regimens. However, extracting new biological insight from high-throughput genomic studies of human diseases is a challenge, limited by difficulties in recognizing and evaluating relevant biological processes from huge quantities of experimental data. Here we present a structured network knowledge-base approach to analyse genome-wide transcriptional responses in the context of known functional interrelationships among proteins, small molecules and phenotypes. This approach was used to analyse changes in blood leukocyte gene expression patterns in human subjects receiving an inflammatory stimulus (bacterial endotoxin). We explore the known genome-wide interaction network to identify significant functional modules perturbed in response to this stimulus. Our analysis reveals that the human blood leukocyte response to acute systemic inflammation includes the transient dysregulation of leukocyte bioenergetics and modulation of translational machinery. These findings provide insight into the regulation of global leukocyte activities as they relate to innate immune system tolerance and increased susceptibility to infection in humans.
A network-based analysis of systemic inflammation in humans.
No sample metadata fields
View Samplesgene expression profiles of leukocytes from blood (WBCs) and spleen harvested at an early (two hours) time point after injury or sham injury in mice subjected to trauma-hemorrhage, burn injury or lipopolysaccharide (LPS)-infusion at three experimental sites
Commonality and differences in leukocyte gene expression patterns among three models of inflammation and injury.
No sample metadata fields
View Samples