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accession-icon GSE40712
Expression data from CD34+ hematopoietic cells transduced with control or anti-HCLS1 shRNA
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Knockdown of HCLS1 mRNA in CD34+ hematopoietic cells resulted in a severe diminished in vitro myeloid differentiation which was in line with downregulation of a set of genes, e.g., of Wnt or PI3K/Akt signaling cascades. We performed microarrays to evaluate specific genes and signaling systems regulated by HCLS1 in hematopoietic cells.

Publication Title

Interactions among HCLS1, HAX1 and LEF-1 proteins are essential for G-CSF-triggered granulopoiesis.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Treatment

View Samples
accession-icon GSE3467
The role of micro-RNA genes in papillary thyroid carcinoma
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We show that numerous miRNAs are transcriptionally up-regulated in papillary thyroid carcinoma (PTC) tumors compared with unaffected thyroid tissue. Among the predicted target genes of the three most upregulated miRNAs (miRs 221, 222 and 146b), only less than 15% showed significant downexpression in transcript level between tumor and unaffected tissue. The KIT gene which is known to be downregulated by miRNAs 221 and 222 displayed dramatic loss of transcript and protein in those tumors that had abundant mir-221, mir-222, and mir-146b transcript.

Publication Title

The role of microRNA genes in papillary thyroid carcinoma.

Sample Metadata Fields

Specimen part

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accession-icon GSE55998
Cellular and Molecular Immune Profiles in Renal Transplant Recipients after Conversion from Tacrolimus to Sirolimus
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Tacrolimus and Sirolimus are commonly used to maintain immunosuppression in kidney transplantation. However, their effects on immune cells and allograft molecular profiles have not been elucidated.

Publication Title

Cellular and molecular immune profiles in renal transplant recipients after conversion from tacrolimus to sirolimus.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE107509
Gene expression profiling of subclinical acute kidney rejection
  • organism-icon Homo sapiens
  • sample-icon 656 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Development and clinical validity of a novel blood-based molecular biomarker for subclinical acute rejection following kidney transplant.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE107503
Gene expression profiling of subclinical acute kidney rejection I
  • organism-icon Homo sapiens
  • sample-icon 529 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

Sub-clinical acute rejection (subAR) in kidney transplant recipients (KTR) leads to chronic rejection and graft loss. Non-invasive biomarkers are needed to detect subAR. 307 KTR were enrolled into a multi-center observational study. Precise clinical phenotypes (CP) were used to define subAR. Differential gene expression (DGE) data from peripheral blood samples paired with surveillance biopsies were used to train a Random Forests (RF) model to develop a gene expression profile (GEP) for subAR. A separate cohort of paired samples was used to validate the GEP. Clinical endpoints and gene pathway mapping were used to assess clinical validity and biologic relevance. DGE data from 530 samples (130 subAR) collected from 250 KTR yielded a RF model: AUC 0.85; 0.84 after internal validation with bootstrap resampling. We selected a predicted probability threshold favoring specificity and NPV (87% and 88%) over sensitivity and PPV (64% and 61%, respectively). We tested the locked model/threshold on a separate cohort of 138 KTR undergoing surveillance biopsies at our institution (rejection 42; no rejection 96): NPV 78%; PPV 51%; AUC 0.66. Both the CP and GEP of subAR within the first 12 months following transplantation were independently associated with worse graft outcomes at 24 months, including de novo donor-specific antibody (DSA). Serial GEP tracked with response to treatment of subAR. DGE data from both cohorts mapped to gene pathways indicative of allograft rejection.

Publication Title

Development and clinical validity of a novel blood-based molecular biomarker for subclinical acute rejection following kidney transplant.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE107506
Gene expression profiling of subclinical acute kidney rejection II
  • organism-icon Homo sapiens
  • sample-icon 127 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

Sub-clinical acute rejection (subAR) in kidney transplant recipients (KTR) leads to chronic rejection and graft loss. Non-invasive biomarkers are needed to detect subAR. 307 KTR were enrolled into a multi-center observational study. Precise clinical phenotypes (CP) were used to define subAR. Differential gene expression (DGE) data from peripheral blood samples paired with surveillance biopsies were used to train a Random Forests (RF) model to develop a gene expression profile (GEP) for subAR. A separate cohort of paired samples was used to validate the GEP. Clinical endpoints and gene pathway mapping were used to assess clinical validity and biologic relevance. DGE data from 530 samples (130 subAR) collected from 250 KTR yielded a RF model: AUC 0.85; 0.84 after internal validation with bootstrap resampling. We selected a predicted probability threshold favoring specificity and NPV (87% and 88%) over sensitivity and PPV (64% and 61%, respectively). We tested the locked model/threshold on a separate cohort of 138 KTR undergoing surveillance biopsies at our institution (rejection 42; no rejection 96): NPV 78%; PPV 51%; AUC 0.66. Both the CP and GEP of subAR within the first 12 months following transplantation were independently associated with worse graft outcomes at 24 months, including de novo donor-specific antibody (DSA). Serial GEP tracked with response to treatment of subAR. DGE data from both cohorts mapped to gene pathways indicative of allograft rejection.

Publication Title

Development and clinical validity of a novel blood-based molecular biomarker for subclinical acute rejection following kidney transplant.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP068723
RNA Seq analysis of e12.5 mouse pancreatic buds from control and Pdxcre; Gata4fl/fl;Gata6fl/fl; Tom mice
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

about 250 genes were significantly changed after Gata4 and Gata6 were specifically deleted in the pancreatic progenitor cells Overall design: 6 pancreatic buds were pooled for the control, and 12 pancreatic buds were pooled for the Pdxcre; Gata4fl/fl; Gata6fl/fl. Libraries were prepared from total RNA (RIN>8) with the TruSeq RNA prep kit (Illumina) and sequenced using the HiSeq2000 (Illumina) instrument. More than 20 million reads were mapped to the mouse genome (UCSC/mm9) using Tophat (version 2.0.4) with 4 mismatches and 10 maximum multiple hits. Significantly differentially expressed genes were calculated using DEseq

Publication Title

GATA4 and GATA6 regulate pancreatic endoderm identity through inhibition of hedgehog signaling.

Sample Metadata Fields

Specimen part, Disease, Subject

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accession-icon SRP078450
Transcriptional response to hepatitis C virus infection and interferon alpha treatment in the human liver
  • organism-icon Homo sapiens
  • sample-icon 43 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Hepatitis C virus (HCV) is widely used to investigate host-virus interactions and cellular responses to infection have been extensively studied in vitro. In human liver, interferon (IFN) stimulated gene expression can mask direct transcriptional responses to virus infection. To better characterize the direct effects of HCV infection in vivo, we analyze the transcriptomes of HCV-infected patients lacking an activated endogenous IFN system. We show that the expression changes observed in these patients predominantly reflect immune cell infiltrates rather than changes in cell-intrinsic metabolic pathways. We also investigate the transcriptomes of patients with endogenous IFN activation, which paradoxically cannot eradicate viral infection. We find that most IFN-stimulated genes (ISGs) are induced by both the endogenous IFN system and by recombinant IFN therapy, but with significantly higher induction levels in the latter. We conclude that the innate host immune response in chronic hepatitis C is too weak to clear the virus. Overall design: In this study, we aimed to disentangle the direct and indirect effects of HCV infection on cellular transcriptional profiles, by performing a detailed characterization of the gene expression changes associated with HCV infection, endogenous IFN system activation and pegIFNa treatment in the human liver. With this objective, we generated and analyzed high-throughput transcriptome sequencing profiles from liver biopsies derived from different categories of HCV-infected and non-infected patients, prior to and during treatment. First, to unveil HCV-induced cell-autonomous effects and to separate them from IFN-induced changes in the transcriptome, we selected liver biopsies from patients with chronic hepatitis C (CHC) without hepatic ISG induction, and compared them with un-infected control biopsies. Second, we examined the transcriptomic changes associated with the endogenous activation of the IFN system. Finally, we analyzed the gene expression changes resulting from pegIFNa/ribavirin treatment, by comparing transcriptome data from liver biopsies obtained before treatment and at different time points during the first week of therapy.

Publication Title

Transcriptional response to hepatitis C virus infection and interferon-alpha treatment in the human liver.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon GSE69815
Expression array of glucosamine-fed Drosophila heart/nephrocyte complexes
  • organism-icon Drosophila melanogaster
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Drosophila Genome 2.0 Array (drosophila2)

Description

Examined the expression effects of supplementing Drosophila food on heart and nephrocyte complexes

Publication Title

Diet-Induced Podocyte Dysfunction in Drosophila and Mammals.

Sample Metadata Fields

Sex, Specimen part, Treatment

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accession-icon SRP064433
RNA sequencing of e15.5 pancreas from Wild Type, Blinc1-/- and Blinc+/- mice.
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

We report the transcriptome changes that result of the genomic deletion of one or two alleles of an islet-specific long non-coding RNA (Blinc1) in isolated pancreas from e15.5 mouse embryos. Overall design: Pancreas from e15.5 embryos were dissected and total RNA extracted. Libraries were prepared from total RNA (RIN>8) with the TruSeq RNA prep kit (Illumina) and sequenced using the HiSeq2000 (Illumina) instrument. More than 20 million reads were mapped to the mouse genome (UCSC/mm9) using Tophat (version 2.0.4) with 4 mismatches and 10 maximum multiple hits. Significantly differentially expressed genes were calculated using DEseq.

Publication Title

βlinc1 encodes a long noncoding RNA that regulates islet β-cell formation and function.

Sample Metadata Fields

Specimen part, Subject

View Samples
...

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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