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accession-icon GSE112681
Whole blood transcriptome analysis in amyotrophic lateral sclerosis: a biomarker study
  • organism-icon Homo sapiens
  • sample-icon 1117 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Whole blood transcriptome analysis in amyotrophic lateral sclerosis: A biomarker study.

Sample Metadata Fields

Sex, Disease

View Samples
accession-icon GSE112676
Whole blood transcriptome analysis in amyotrophic lateral sclerosis: a biomarker study [HT12_V3]
  • organism-icon Homo sapiens
  • sample-icon 741 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip

Description

Transcriptome-wide analysis of whole blood gene expression profiles of ALS patients, gender- and age-matched controls and patients diagnosed with diseases mimicking ALS at a tertiary referral center for motor neuron diseases.

Publication Title

Whole blood transcriptome analysis in amyotrophic lateral sclerosis: A biomarker study.

Sample Metadata Fields

Sex, Disease

View Samples
accession-icon GSE112680
Whole blood transcriptome analysis in amyotrophic lateral sclerosis: a biomarker study [HT12_V4]
  • organism-icon Homo sapiens
  • sample-icon 376 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip

Description

Transcriptome-wide analysis of whole blood gene expression profiles of ALS patients, gender- and age-matched controls and patients diagnosed with diseases mimicking ALS at a tertiary referral center for motor neuron diseases.

Publication Title

Whole blood transcriptome analysis in amyotrophic lateral sclerosis: A biomarker study.

Sample Metadata Fields

Sex, Disease

View Samples
accession-icon GSE65682
Genome-wide blood transcriptional profiling in critically ill patients - MARS consortium
  • organism-icon Homo sapiens
  • sample-icon 802 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

The host response in critically ill patients with sepsis, septic shock remains poorly defined. Considerable research has been conducted to accurately distinguish patients with sepsis from those with non-infectious causes of disease. Technological innovations have positioned systems biology at the forefront of biomarker discovery. Analysis of the whole-blood leukocyte transcriptome enables the assessment of thousands of molecular signals beyond simply measuring several proteins in plasma, which for use as biomarkers is important since combinations of biomarkers likely provide more diagnostic accuracy than the measurement of single ones or a few. Evidence suggests that genome-wide transcriptional profiling of blood leukocytes can assist in differentiating between infection and non-infectious causes of severe disease. Of importance, RNA biomarkers have the potential advantage that they can be measured reliably in rapid quantitative reverse transcriptase polymerase chain reaction (qRT-PCR)-based point of care tests.

Publication Title

A molecular biomarker to diagnose community-acquired pneumonia on intensive care unit admission.

Sample Metadata Fields

Sex, Age

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accession-icon GSE74224
Discrimination of SIRS from Sepsis in Critically Ill Adults
  • organism-icon Homo sapiens
  • sample-icon 105 Downloadable Samples
  • Technology Badge Icon 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

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accession-icon GSE73395
BAL cell gene expression is predictive of Mortality in Idiopathic Pulmonary Fibrosis and enriched for Genes of Airway Basal Cells (IV)
  • organism-icon Homo sapiens
  • sample-icon 57 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background: We got interested whether genes of airway basal cells are enriched in COPD.

Publication Title

BAL Cell Gene Expression Is Indicative of Outcome and Airway Basal Cell Involvement in Idiopathic Pulmonary Fibrosis.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE73394
BAL cell gene expression is predictive of Mortality in Idiopathic Pulmonary Fibrosis and enriched for Genes of Airway Basal Cells (III)
  • organism-icon Homo sapiens
  • sample-icon 46 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Background: We got interested whether genes of airway basal cells are enriched in sarcoidosis.

Publication Title

BAL Cell Gene Expression Is Indicative of Outcome and Airway Basal Cell Involvement in Idiopathic Pulmonary Fibrosis.

Sample Metadata Fields

Specimen part, Disease

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accession-icon GSE67953
Tumor-Associated Macrophages Promote Colorectal Tumor Development Through Remodeling of Its Extracellular Matrix
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Ly6Chi monocytes massively infiltrate the CRC-tumors by virtue of their CCR2 expression and further mature into Ly6CloF4/80hi CD64hiMHCII+ TAM upon tumor progression. We demonstrated that TAM-deficient tumors display impaired tumor-growth via alternation of the ECM morphology, structure and composition. Using advanced high-resolution optical imaging to visualize the tumoral-ECM macromolecule network together with transcriptomic and proteomic approaches we unraveled that TAM play critical role in the deposition, linearization and cross-linking of collagenous ECM. Remarkably, we show that cues embedded in ECM by TAM-mediated remodeling activity promote tumor cell proliferation in vitro and orthotopic tumor development in vivo.

Publication Title

Tumor macrophages are pivotal constructors of tumor collagenous matrix.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon SRP174051
TNF induces Glucocorticoid Resistance by reshaping the GR Nuclear Cofactor Profile: Investigation of TNF mediated effects on the GR mediated gene expression
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer

Description

Glucocorticoid resistance (GCR) is defined as an unresponsiveness to the anti-inflammatory properties of glucocorticoids (GCs) and their receptor, the glucocorticoid receptor (GR). It is a serious problem in the management of inflammatory diseases and occurs frequently. The strong pro-inflammatory cytokine TNF induces an acute form of GCR, not only in mice, but also in several cell lines, e.g. in the hepatoma cell line BWTG3, as evidenced by impaired Dexamethasone (Dex)-induced GR-dependent gene expression. We report that TNF has a significant and broad impact on the transcriptional performance of GR, but no impact on nuclear translocation, dimerization or DNA binding capacity of GR. Proteome-wide proximity-mapping (BioID), however, revealed that the GR interactome is strongly modulated by TNF. One GR cofactor that interacts significantly less with the receptor under GCR conditions is p300. NF?B activation and p300 knockdown both reduce transcriptional output of GR, whereas p300 overexpression and NF?B inhibition revert TNF-induced GCR, which is in support of a cofactor reshuffle model. This hypothesis is supported by FRET studies. This mechanism of GCR opens new avenues for therapeutic interventions in GCR diseases Overall design: Examination of GR induced gene expression in 4 conditions (1 control: NI and 3 treated: DEX, TNF, TNFDEX) starting from 3 biological replicates

Publication Title

TNF-α inhibits glucocorticoid receptor-induced gene expression by reshaping the GR nuclear cofactor profile.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject

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accession-icon GSE48836
Transcript profiling of ERF115 transgenic Arabidopsis thaliana
  • organism-icon Arabidopsis thaliana
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

This experiment was set up in order to identify the (direct) transcriptional targets of the Ethylene Response Factor 115 (ERF115) transcription factor. Because ERF115 expression occurs in quiescent center (QC) cells and strong effects on the QC cells were observed in ERF115 overexpression plants, root tips were harvested for transcript profiling in order to focus on root meristem and QC specific transcriptional targets.

Publication Title

ERF115 controls root quiescent center cell division and stem cell replenishment.

Sample Metadata Fields

Age, Specimen part

View Samples
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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Developed by the Childhood Cancer Data Lab

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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