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GSE74224
Homo sapiens
105 Downloadable Samples
Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)
Description
Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood could be discovered that would: 1) determine which patients with systemic inflammation had sepsis; 2) be robust across independent patient cohorts; 3) be insensitive to disease severity; and 4) provide diagnostic utility. The overall goal of this study was to identify and validate such a molecular classifier. Methods and Findings: We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyte Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood possible) gave an AUC of 0.89 (95% CI: 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyte Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyte Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyte Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyte Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation.
Publication Title
A Molecular Host Response Assay to Discriminate Between Sepsis and Infection-Negative Systemic Inflammation in Critically Ill Patients: Discovery and Validation in Independent Cohorts.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 50 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
Oxidative stress is a common phenomenon and is linked to a wide range of diseases and pathological processes. Tissue-specific variation in redox signaling and cellular responses to oxidative stress may be associated with vulnerability to toxic agents and carcinogenic exposures. In order to provide a basis for tissue-specific difference, we examined the tissue-specific transcriptional features of 101 oxidative stress-associated genes in 10 different tissues and organs of healthy mice under physiological conditions.
Publication Title
Tissue-Specific Profiling of Oxidative Stress-Associated Transcriptome in a Healthy Mouse Model.
Sample Metadata Fields
Sex
View Samples- Homo sapiens
- 678 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
BACKGROUND: In patients with suspicious pulmonary lesions, bronchoscopy is frequently non-diagnostic. This often results in additional invasive testing, including surgical biopsy, although many patients have benign disease. We sought to validate an airway gene-expression classifier for lung cancer in patients undergoing diagnostic bronchoscopy. METHODS: Two multicenter prospective studies (AEGIS 1 and 2) enrolled 1357 current or former smokers undergoing bronchoscopy for suspected lung cancer. Bronchial epithelial cells were collected from normal appearing mucosa in the mainstem bronchus during bronchoscopy. Patients without a definitive diagnosis from bronchoscopy were followed for 12 months. A gene-expression classifier was used to assess the risk of lung cancer, and its performance was evaluated. RESULTS: A total of 298 patients from AEGIS 1 and 341 from AEGIS 2 met criteria for analysis. Bronchoscopy was non-diagnostic for cancer in 272 of 639 patients (43%; 95%CI, 39-46%). The gene expression classifier correctly identified 431 of 487 patients with cancer (89% sensitivity; 95%CI, 85-91%), and 72 of 152 patients without cancer (47% specificity; 95%CI, 40-55%). The combination of the classifier and bronchoscopy had a sensitivity of 97% (95%CI, 95-98%), which was independent of size, location, stage, and histological subtype of lung cancer. In patients with an intermediate pre-test risk (10-60%) of lung cancer, the NPV of the classifier was 91% (95%CI 75-98%). CONCLUSIONS: In patients with an intermediate risk of lung cancer and a non-diagnostic bronchoscopy, a gene-expression classification of low-risk warrants consideration of a more conservative diagnostic approach that could reduce unnecessary invasive testing in patients with benign disease.
Publication Title
A Bronchial Genomic Classifier for the Diagnostic Evaluation of Lung Cancer.
Sample Metadata Fields
Sex, Specimen part
View Samples- Homo sapiens
- 594 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Gene expression profiling reveals epithelial mesenchymal transition (EMT) genes can selectively differentiate eribulin sensitive breast cancer cells.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Homo sapiens
- 150 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
Description
The systematic characterization of somatic mutations in cancer genomes is essential for understanding the disease and for developing targeted therapeutics. Here we report the identification of 2,576 somatic mutations across approximately 1,800 megabases of DNA representing 1,507 coding genes from 441 tumours comprising breast, lung, ovarian and prostate cancer types and subtypes. Additionally, 373 tumors were assayed for copy number alterations via Agilent 244A CGH arrays and 153 breast, lung, and colon samples were assayed for mRNA abundance with Affymetrix HuEx1 Exon Arrays.
Publication Title
Diverse somatic mutation patterns and pathway alterations in human cancers.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 294 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Gastric cancer, a leading cause of cancer related deaths, is a heterogeneous disease, with little consensus on molecular subclasses and their clinical relevance. We describe four molecular subtypes linked with distinct patterns of molecular alterations, disease progression and prognosis viz. a) Microsatellite Instable: hypermutated intestinal subtype tumors occurring in antrum, best overall prognosis, lower frequency of recurrence (22%), with liver metastasis in 23% of recurred cases b) Mesenchymal-like: diffuse tumors with worst prognosis, a tendency to occur at an earlier age and highest recurrence (63%) with peritoneal seeding in 64% of recurred cases, low frequency of molecular alterations c) TP53-inactive with TP53 loss, presence of focal amplifications and chromosomal instability d) TP53-active marked by EBV infection and PIK3CA mutations. The key molecular mechanisms and associated survival patterns are validated in multiple independent cohorts, to provide a consistent and unified framework for further preclinical and clinical research.
Publication Title
Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 294 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
No associated publication
Sample Metadata Fields
Specimen part, Subject
View Samples- Rattus norvegicus
- 294 Downloadable Samples
- Affymetrix Rat Genome 230 2.0 Array (rat2302)
Description
This study is designed to compare and contrast the temporal and spatial changes in bone formation rates and transcriptional profiles in cortical and cancellous bone cell populations enriched by laser capture microdissection (LCM) in ovariectomized rats administered Scl-Ab by subcutaneous injection for up to 26 consecutive weeks, followed by a recovery period of up to 18 weeks.
Publication Title
Time-dependent cellular and transcriptional changes in the osteoblast lineage associated with sclerostin antibody treatment in ovariectomized rats.
Sample Metadata Fields
Sex, Specimen part, Time
View Samples- Homo sapiens
- 238 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Eribulin mesylate is a synthetic macrocyclic ketone analog of the marine sponge natural product halichondrin B. Eribulin is a mechanistically unique inhibitor of microtubule dynamics, leading to inhibition of microtubule growth in the absence of effects on microtubule shortening at microtubule plus ends, and formation of nonproductive tubulin aggregates. In this study, we investigated whether selective signal pathways were associated with eribulin activity compared to paclitaxel, which stabilizes microtubules, based on gene expression profiling of cell line panels of breast, endometrial, and ovarian cancer in vitro.
Publication Title
Gene expression profiling reveals epithelial mesenchymal transition (EMT) genes can selectively differentiate eribulin sensitive breast cancer cells.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Homo sapiens
- 224 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Immune cell-specific expression is one indication of the importance of a gene's role in the immune response.
Publication Title
Immune response in silico (IRIS): immune-specific genes identified from a compendium of microarray expression data.
Sample Metadata Fields
Specimen part
View Samples