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accession-icon GSE102612
Protective effects of INSL6 on heart failure
  • organism-icon Mus musculus
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Background: The insulin/IGF/relaxin family represents a group of structurally related but functionally diverse proteins. The family member Relaxin-2 has been evaluated in clinical trials for its efficacy in the treatment of acute heart failure. In this study, we assessed the role of Insulin-like peptide 6 (Insl6), another member of this protein family, in murine heart failure models using genetic loss-of-function and protein delivery methods. Methods and Results: Insl6-deficient (Insl6-KO) and wild-type (C57BL/6N) mice were administered angiotensin II or isoproterenol via continuous infusion with an osmotic pump or via intraperitoneal injection once a day, respectively for 2 weeks. In both models, Insl6-KO mice exhibited greater cardiac systolic dysfunction and left ventricular dilatation hypertrophy. Cardiac dysfunction in the Insl6-KO mice was associated with more extensive cardiac fibrosis and greater expression of fibrosis-associated genes. The continuous infusion of chemically synthesized INSL6 significantly attenuated left ventricular systolic dysfunction and cardiac fibrosis induced by isoproterenol infusion. Gene expression profiling suggests Lxr/ Rxr signaling is activated in the isoproterenol-challenged hearts treated with INSL6 protein. Conclusions: Endogenous Insl6 protein inhibits cardiac systolic dysfunction and cardiac fibrosis in angiotensin II- and isoproterenol-induced cardiac stress models. The administration of recombinant Insl6 protein could have utility for the treatment of heart failure and cardiac fibrosis.

Publication Title

Relaxin Family Member Insulin-Like Peptide 6 Ameliorates Cardiac Fibrosis and Prevents Cardiac Remodeling in Murine Heart Failure Models.

Sample Metadata Fields

Sex, Specimen part, Treatment

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accession-icon GSE87371
Expression data from Diffuse Large B Cell Lymphoma (DLBCL) patients
  • organism-icon Homo sapiens
  • sample-icon 220 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Diffuse large B-cell lymphoma (DLBCL) is currently divided into three main molecular subtypes, defined by gene expression profiling (GEP): Germinal Center B-cell like (GCB), Activated B-Cell like (ABC), and Primary Mediastinal B-cell Lymphoma (PMBL).

Publication Title

Biological and Clinical Relevance of Associated Genomic Alterations in MYD88 L265P and non-L265P-Mutated Diffuse Large B-Cell Lymphoma: Analysis of 361 Cases.

Sample Metadata Fields

Sex, Age, Disease

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accession-icon GSE100846
Blood-brain barrier transport and neuroprotective potential of blackberry-digested polyphenols: an in vitro study
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Purpose: Epidemiological and intervention studies have attempted to link the health effects of a diet rich in fruits and vegetables with the consumption of polyphenols and their impact in neurodegenerative diseases. Studies have shown that polyphenols can cross the intestinal barrier and reach concentrations in the bloodstream able to exert effects in vivo. However, the effective uptake of polyphenols in the brain is still regarded with some reservations. Here we describe a combination of approaches to examine the putative transport of blackberry-digested polyphenols (BDP) across the blood-brain barrier (BBB) and ultimate evaluation of their beneficial effects.

Publication Title

Blood-brain barrier transport and neuroprotective potential of blackberry-digested polyphenols: an in vitro study.

Sample Metadata Fields

Sex, Specimen part, Cell line, Race

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accession-icon GSE73066
Transcriptional profiles of pilocytic astrocytoma
  • organism-icon Homo sapiens
  • sample-icon 35 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Pilocytic astrocytoma is the most common type of brain tumor in pediatric population, generally connected with favorable prognosis, although recurrences or dissemination sometimes are also observed. For tumors originating in supra- or infratentorial location different molecular background was suggested but plausible correlations between transcriptional profile and radiological features and/or clinical course are still undefined. The purpose of this study was to identify gene expression profiles related to the most frequent locations of this tumor, subtypes based on various radiological features and clinical pattern of the disease. According to the radiological features presented on MRI, all cases were divided into four subtypes: solid or mainly solid, cystic with an enhancing cyst wall, cystic with a non-enhancing cyst wall and solid with central necrosis. Bioinformatic analyses showed that gene expression profile of pilocytic astrocytoma highly depends on the tumor location. Most prominent differences were noted for IRX2, PAX3, CXCL14, LHX2, SIX6, CNTN1 and SIX1 genes expression which could distinguish pilocytic astrocytomas of different location even within supratentorial region. Analysis of the genes potentially associated between radiological features showed much weaker transcriptome differences. Single genes showed association with the tendency to progression. Here we showed that pilocytic astrocytomas of three different locations could be precisely differentiated on the basis of gene expression level but their transcriptional profiles did not strongly reflect the radiological appearance of the tumor or the course of the disease.

Publication Title

Transcriptional profiles of pilocytic astrocytoma are related to their three different locations, but not to radiological tumor features.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

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accession-icon GSE93261
Transcriptome analysis of Follicular Lymphomas from the PRIMABIO cohort
  • organism-icon Homo sapiens
  • sample-icon 124 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We investigated the biological features of FL and their relationship to patients outcome. Gene expression analysis was carried out on diagnosis biopsies from 148 follicular lymphoma patients enrolled in the PRIMA clinical trial. We developed a gene expression-based predictor of progression-free survival (PFS) in high-tumour burden FL patients and we analysed gene-expression signatures reflecting different aspects of tumour biology for their association with outcome. proposition SH: We investigated the biological features of FL and their relationship to patients outcome. Gene expression analysis was carried out on diagnosis biopsies from 148 follicular lymphoma patients enrolled in the PRIMA clinical trial. We developed a gene expression-based predictor of progression-free survival (PFS) in high-tumour burden FL patients and we analysed gene-expression signatures reflecting different aspects of tumour biology for their association with outcome.

Publication Title

A gene-expression profiling score for prediction of outcome in patients with follicular lymphoma: a retrospective training and validation analysis in three international cohorts.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE50567
BRCA1-related gene signature in breast cancer: the role of ER status and molecular type
  • organism-icon Homo sapiens
  • sample-icon 41 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We have analyzed, using DNA microarrays, putative differences in gene-expression level between hereditary BRCA1 mutation-linked and sporadic breast cancer. Our results show that a previously reported marked difference between BRCA1-mutation linked and sporadic breast cancer was probably due to uneven stratification of samples with different ER status and basal-like versus luminal-like subtype. We observed that apparent difference between BRCA1-linked and other types of breast cancer found in univariate analysis was diminished when data were corrected for ER status and molecular subtype in multivariate analyses. In fact, the difference in gene expression pattern of BRCA1-mutated and sporadic cancer is very discrete. These conclusions were supported by the results of Q-PCR validation. We also found that BRCA1 gene inactivation due to promoter hypermethylation had similar effect on general gene expression profile as mutation-induced protein truncation. This suggests that in the molecular studies of hereditary breast cancer, BRCA1 gene methylation should be recognized and considered together with gene mutation.

Publication Title

BRCA1-related gene signature in breast cancer: the role of ER status and molecular type.

Sample Metadata Fields

Age

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accession-icon GSE13909
Molecular signature of cell cycle exit induced in human T lymphoblasts by IL-2 withdrawal
  • organism-icon Homo sapiens
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Molecular mechanisms of cell cycle exit are poorly understood. A group of genes required for cell cycle exit and maintenance of cell quiescence in human fibroblasts following serum deprivation has been recently identified. Studies on lymphocytes following growth factor deprivation-induced cell cycle exit have predominantly focused on the initiation of apoptosis. A set of genes involved in lymphocyte quiescence have also been identified among genes highly expressed in resting lymphocytes and down-regulated after cell activation. In our study, proliferating IL-2-dependent human T cells were forced to exit cell cycle by growth factor withdrawal, and their gene expression profiles were examined.

Publication Title

Molecular signature of cell cycle exit induced in human T lymphoblasts by IL-2 withdrawal.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE63885
Gene expression profiling in ovarian cancer
  • organism-icon Homo sapiens
  • sample-icon 99 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The introduction of microarray techniques to cancer research brought great expectations for finding biomarkers that would improve patients treatment; however, the results of such studies are poorly reproducible and critical analyses of these methods are rare. In this study, we examined global gene expression in 97 ovarian cancer samples. Also, validation of results by quantitative RT-PCR was performed on 30 additional ovarian cancer samples. We carried out a number of systematic analyses in relation to several defined clinicopathological features. The main goal of our study was to delineate the molecular background of ovarian cancer chemoresistance and find biomarkers suitable for prediction of patients prognosis. We found that histological tumor type was the major source of variability in genes expression, except for serous and undifferentiated tumors that showed nearly identical profiles. Analysis of clinical endpoints [tumor response to chemotherapy, overall survival, disease-free survival (DFS)] brought results that were not confirmed by validation either on the same group or on the independent group of patients. CLASP1 was the only gene that was found to be important for DFS in the independent group, whereas in the preceding experiments it showed associations with other clinical endpoints and with BRCA1 gene mutation; thus, it may be worthy of further testing. Our results confirm that histological tumor type may be a strong confounding factor and we conclude that gene expression studies of ovarian carcinomas should be performed on histologically homogeneous groups. Among the reasons of poor reproducibility of statistical results may be the fact that despite relatively large patients group, in some analyses one has to compare small and unequal classes of samples. In addition, arbitrarily performed division of samples into classes compared may not always reflect their true biological diversity. And finally, we think that clinical endpoints of the tumor probably depend on subtle changes in many and, possibly, alternative molecular pathways, and such changes may be difficult to demonstrate.

Publication Title

Gene expression analysis in ovarian cancer - faults and hints from DNA microarray study.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE65005
Snai1 regulates cell lineage allocation and stem cell maintenance in the mouse intestinal epithelium
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

Conditional knockout of Snai1 in the mouse intestinal epithlium results in apoptotic loss of crypt base columnar cells and bias towards differentiation of secretory lineages. In vitro organoid cultures derived from Snail conditional knockout mice also undergo apoptosis when Snai1 is deleted.

Publication Title

Snai1 regulates cell lineage allocation and stem cell maintenance in the mouse intestinal epithelium.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE58689
Gene expression signature associated with BRAFV600E mutation in human papillary thyroid carcinoma based on transgenic mouse model
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 54 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st), Affymetrix Human Genome U133A Array (hgu133a)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

BRAFV600E-Associated Gene Expression Profile: Early Changes in the Transcriptome, Based on a Transgenic Mouse Model of Papillary Thyroid Carcinoma.

Sample Metadata Fields

Sex, Age

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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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