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accession-icon GSE108461
Targeting EphA4 abrogates intrinsic resistance to chemotherapy in well-differentiated tumors
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

Purpose Alkylating reagent chemotherapy for human cancers is not curative, and relapse occurs due to the continued presence of tumor cells, referred to as minimal residual disease (MRD). Methods The survival of MRD cells after chemotherapy, a phenomenon referred to as intrinsic resistance, depends on reactive oxygen species (ROS). Well-differentiated regions of the tumor are intrinsically resistant to chemotherapy. Results Here, we report that ROS produced by cisplatin exposure induce the tyrosine phosphorylation of the receptor tyrosine kinase erythropoietin-producing human hepatocellular receptor A4 (EphA4). EphA4 protein is highly expressed in the well-differentiated tumor-derived cervical cancer cell line Caski, but not in poorly differentiated tumor-derived cervical cancer cell lines such as HeLa or SiHa. Pharmacological inhibition of EphA4 increased cisplatin-induced cell death in Caski cells. Moreover, we observed increased expression levels of the senescence marker cyclin-dependent kinase inhibitor 2A (p16) and IL-8 in the absence of EphA4 kinase function after stimulation of Caski cells with hydrogen peroxide or cisplatin exposure. Conclusion Our data demonstrate that EphA4 expression levels determine the threshold of alkylating reagent chemotherapy. Therefore, ROS-induced tyrosine phosphorylation of EphA4 confers intrinsic resistance to alkylating reagent chemotherapy in a well-differentiated tumor, and may represent a unifying Achilles heel for chemotherapy resistance of well-differentiated tumors.

Publication Title

No associated publication

Sample Metadata Fields

Treatment

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accession-icon GSE38309
Expression data from A549 cells after treatment with flagellin and transforming growth factor beta 1
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We have examined the changes in gene expression aftert reatment of A549 cells, a cultured alveolar epithelial cells, with flagellin and transforming growth factor beta 1.

Publication Title

Induction of epithelial-mesenchymal transition by flagellin in cultured lung epithelial cells.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE73072
Host gene expression signatures of H1N1, H3N2, HRV, RSV virus infection in adults
  • organism-icon Homo sapiens
  • sample-icon 2886 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Consider the problem of designing a panel of complex biomarkers to predict a patient's health or disease state when one can pair his or her current test sample, called a target sample, with the patient's previously acquired healthy sample, called a reference sample. As contrasted to a population averaged reference, this reference sample is individualized. Automated predictor algorithms that compare and contrast the paired samples to each other could result in a new generation of test panels that compare to a person's healthy reference to enhance predictive accuracy. This study develops such an individualized predictor and illustrates the added value of including the healthy reference for design of predictive gene expression panels. The objective is to predict each subject's state of infection, e.g., neither exposed nor infected, exposed but not infected, pre-acute phase of infection, acute phase of infection, post-acute phase of infection. Using gene microarray data collected in a large-scale serially sampled respiratory virus challenge study, we quantify the diagnostic advantage of pairing a person's baseline reference with his or her target sample.

Publication Title

An individualized predictor of health and disease using paired reference and target samples.

Sample Metadata Fields

Specimen part, Subject, Time

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accession-icon GSE138914
Gene expression data from lymphoblastoid cell lines from African American participants in the GENOA study
  • organism-icon Homo sapiens
  • sample-icon 711 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

African-American individuals of the GENOA cohort

Publication Title

Genetic Architecture of Gene Expression in European and African Americans: An eQTL Mapping Study in GENOA.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE18927
University of Washington Human Reference Epigenome Mapping Project
  • organism-icon Homo sapiens
  • sample-icon 97 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

The NIH Roadmap Epigenomics Mapping Consortium aims to produce a public resource of epigenomic maps for stem cells and primary ex vivo tissues selected to represent the normal counterparts of tissues and organ systems frequently involved in human disease.

Publication Title

The NIH Roadmap Epigenomics Mapping Consortium.

Sample Metadata Fields

Sex, Specimen part, Disease, Subject

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accession-icon GSE30211
Gene expression changes during Type 1 diabetes pathogenesis
  • organism-icon Homo sapiens
  • sample-icon 724 Downloadable Samples
  • Technology Badge IconIllumina human-6 v2.0 expression beadchip, Affymetrix Human Genome U219 Array (hgu219)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Innate immune activity is detected prior to seroconversion in children with HLA-conferred type 1 diabetes susceptibility.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE45642
Circadian patterns of gene expression in the human brain and disruption in major depressive disorder [control set]
  • organism-icon Homo sapiens
  • sample-icon 667 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

A cardinal symptom of Major Depressive Disorder (MDD) is the disruption of circadian patterns. Yet, to date, there is no direct evidence of circadian clock dysregulation in the brains of MDD patients. Circadian rhythmicity of gene expression has been observed in animals and peripheral human tissues, but its presence and variability in the human brain was difficult to characterize. Here we applied time-of-death analysis to gene expression data from high-quality postmortem brains, examining 24-hour cyclic patterns in six cortical and limbic regions of 55 subjects with no history of psychiatric or neurological illnesses ('Controls') and 34 MDD patients. Our dataset covered ~12,000 transcripts in the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (AnCg), hippocampus (HC), amygdala (AMY), nucleus accumbens (NAcc) and cerebellum (CB). Several hundred transcripts in each region showed 24-hour cyclic patterns in Controls, and >100 transcripts exhibited consistent rhythmicity and phase-synchrony across regions. Among the top ranked rhythmic genes were the canonical clock genes BMAL1(ARNTL), PER1-2-3, NR1D1(REV-ERB), DBP, BHLHE40(DEC1), and BHLHE41(DEC2). The phasing of known circadian genes was consistent with data derived from other diurnal mammals. Cyclic patterns were much weaker in MDD brains, due to shifted peak timing and potentially disrupted phase relationships between individual circadian genes. This is the first transcriptome-wide analysis of cyclic patterns in the human brain and demonstrates a rhythmic rise and fall of gene expression in regions outside of the suprachiasmatic nucleus in control subjects. The description of its breakdown in MDD suggest novel molecular targets for treatment of mood disorders.

Publication Title

Circadian patterns of gene expression in the human brain and disruption in major depressive disorder.

Sample Metadata Fields

Subject

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accession-icon GSE71620
The effects of aging on circadian patterns of gene expression in the human prefrontal cortex
  • organism-icon Homo sapiens
  • sample-icon 419 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

With aging, significant changes in circadian rhythms occur, including a shift in phase toward a morning chronotype and a loss of rhythmicity in circulating hormones. However, the effects of aging on molecular rhythms in the human brain have remained elusive. Here we employed a previously-described time-of-death analyses to identify transcripts throughout the genome that have a significant circadian rhythm in expression in the human prefrontal cortex (Brodmanns areas (BA) 11 and 47). Expression levels were determined by microarray analysis in 146 individuals. Rhythmicity in expression was found in ~10% of detected transcripts (p<0.05). Using a meta-analysis across the two brain areas, we identified a core set of 235 genes (q<0.05) with significant circadian rhythms of expression. These 235 genes showed 92% concordance in the phase of expression between the two areas. In addition to the canonical core circadian genes, a number of other genes were found to exhibit rhythmic expression in the brain. Notably, we identified more than one thousand genes (1186 in BA11; 1591 in BA47) that exhibited age-dependent rhythmicity or alterations in rhythmicity patterns with aging. Interestingly, a set of transcripts gained rhythmicity in older individuals, which may represent a compensatory mechanism due to a loss of canonical clock function. Thus, we confirm that rhythmic gene expression can be reliably measured in human brain and identified for the first time significant changes in molecular rhythms with aging that may contribute to altered cognition, sleep and mood in later life.

Publication Title

Effects of aging on circadian patterns of gene expression in the human prefrontal cortex.

Sample Metadata Fields

Sex, Age, Specimen part, Race

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accession-icon GSE36059
Molecular diagnosis of T cell-mediated rejection in human kidney transplant biopsies; Molecular diagnosis of antibody-mediated rejection in human kidney transplants
  • organism-icon Homo sapiens
  • sample-icon 391 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Histologic diagnosis of T cell-mediated rejection in kidney transplant biopsies has limited reproducibility because it is based on non-specific lesions using arbitrary rules that are subject to differing interpretations. We used microarray results from 403 indication biopsies previously given histologic diagnoses to develop a molecular classifier that assigned a molecular T cell-mediated rejection score to each biopsy. Independent assessment of the biopsies by multiple pathologists confirmed considerable disagreement on the presence of TCMR features: 79-88% accuracy and 35-69% sensitivity. The agreement of the molecular T cell-mediated rejection score with the histology diagnosis was similar to agreement among individual pathologists: accuracy 89%, sensitivity 51%. However, the score also predicted the consensus among pathologists, being highest when all agreed. Many discrepancies between the scores and the histologic diagnoses were in situations where histology is unreliable e.g. scarred biopsies. The score correlated with histologic lesions and gene sets associated with T cell-mediated rejection. The transcripts most often selected by the classifier were expressed in effector T cells, dendritic cells, or macrophages or inducible by interferon-gamma. Thus the T cell-mediated rejection score offers an objective assessment of kidney transplant biopsies, predicting the consensus opinion among multiple pathologists, and offering insights into underlying disease mechanisms.

Publication Title

Molecular diagnosis of T cell-mediated rejection in human kidney transplant biopsies.

Sample Metadata Fields

Disease

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accession-icon GSE12417
Prognostic gene signature for normal karyotype AML
  • organism-icon Homo sapiens
  • sample-icon 404 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Patients with cytogenetically normal acute myeloid leukemia (CN-AML) show heterogeneous treatment outcomes. We used gene expression profiling to develop a gene signature that predicts overall survival (OS) in CN-AML. Based on data from 163 patients treated in the German AMLCG 1999 trial and analyzed on oligonucleotide microarrays, we used supervised principal component analysis to identify 86 probe sets (representing 66 different genes) which correlated with OS, and defined a prognostic score based on this signature. When applied to an independent cohort of 79 CN-AML patients, this continuous score remained a significant predictor for OS (hazard ratio [HR], 1.85; P=0.002), EFS (HR, 1.73; P=0.001), and RFS (HR, 1.76; P=0.025). It kept its prognostic value in multivariate analyses adjusting for age, FLT3 ITD and NPM1 status. In a validation cohort of 64 CN-AML patients treated on CALGB study 9621, the score also predicted OS (HR, 4.11; P<0.001), EFS (HR, 2.90; P<0.001), and RFS (HR, 3.14, P<0.001) and retained its significance in a multivariate model for OS. In summary, we present a novel gene expression signature that offers additional prognostic information for patients with CN-AML.

Publication Title

An 86-probe-set gene-expression signature predicts survival in cytogenetically normal acute myeloid leukemia.

Sample Metadata Fields

No sample metadata fields

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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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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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