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accession-icon GSE57720
Ingestion of Cryptococcus neoformans by macrophages damages multiple host cellular processes
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Human infection with Cryptococcus neoformans (Cn), a prevalent fungal pathogen, occurs by inhalation and deposition in the lung alveoli of infectious particles. The subsequent host pathogen interaction is multifactorial and can result either in eradication, latency or extra-pulmonary dissemination. Successful control of Cn infection is dependent on host macrophages as shown by numerous studies. However in vitro macrophages display little ability to kill Cn. Recently, we reported that ingestion of Cn by macrophages induces early cell cycle progression that is subsequently followed by mitotic arrest, an event that almost certainly reflects damage to the host cell. The goal of the present work was to understand macrophage pathways affected by Cn toxicity. Infection of J774.16 macrophage-like cell line macrophages by Cn in vitro was associated with changes in gene pattern expression. Concomitantly we observed depolarization of macrophage mitochondria and alterations in protein translation rate. Our results indicate that Cn infection impairs multiple host cellular functions. Therefore we conclude Cn intracellular residence in macrophages undermines the health of these critical phagocytic cells interfering with their ability to clear the fungal pathogen.

Publication Title

Macrophage mitochondrial and stress response to ingestion of Cryptococcus neoformans.

Sample Metadata Fields

Specimen part, Cell line, Time

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accession-icon GSE45725
Internal validation cohort of breast cancers for development of ClinicoMolecular Triad Classification
  • organism-icon Homo sapiens
  • sample-icon 340 Downloadable Samples
  • Technology Badge IconIllumina HumanRef-8 v3.0 expression beadchip

Description

In our early study (PMID: 21939527), we have created a ClinicoMolecular Triad Classification (CMTC) to improve prediction and prognostication of breast cancer by using a training cohort contained 161 breast cancer patients (2003 to 2008). Here, a supplemental internal validation cohort contained 340 breast cancer patients was collected (2008 to 2010) for development of the CMTC.

Publication Title

Validation of the prognostic gene portfolio, ClinicoMolecular Triad Classification, using an independent prospective breast cancer cohort and external patient populations.

Sample Metadata Fields

Age, Disease stage

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accession-icon GSE42135
Expression data from preimplantation mouse embryos
  • organism-icon Mus musculus
  • sample-icon 42 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Landmark events occur in a coordinated manner during preimplantation development of the mammalian embryo, yet the regulatory network that orchestrates these events remains largely unknown.

Publication Title

An Oct4-Sall4-Nanog network controls developmental progression in the pre-implantation mouse embryo.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE16987
A new gene expression signature, the ClinicoMolecular Triad Classification, may improve prediction and prognostication of breast cancer at the time of diagnosis
  • organism-icon Homo sapiens
  • sample-icon 161 Downloadable Samples
  • Technology Badge IconIllumina humanRef-8 v2.0 expression beadchip

Description

When making treatment decisions, oncologists often stratify breast cancers into a low-risk group (ER+, low grade); an intermediate-risk group (ER+, high grade); and a high-risk group that includes Her2+ and triple-negative (ER-/PR-/Her2-) tumors. None of the currently available gene signatures correlates to this clinical classification. We aimed to develop a test that is practical for the oncologists, that offers both molecular characterization of BCs, and improved prediction of prognosis and treatment response. We investigated the molecular basis of such clinical practice by grouping Her2+ and triple-negative breast cancers together during clustering analyses on the genome-wide gene expression profiles of our training cohort, mostly derived from fine needle aspiration biopsies (FNABs) of 149 consecutive evaluable Breast cancers. The analyses consistently divided these tumors into a three-cluster pattern, similar to clinical risk-stratification groups, that was reproducible in published microarray databases (n=2487) annotated with clinical outcomes. The clinicopathologic parameters of each of these three molecular groups were also similar to clinical classification. The low-risk group had good outcomes and benefited from endocrine therapy. Both intermediate- and high-risk groups had poor outcomes and were resistant to endocrine therapy. The latter demonstrated the highest rate of complete pathological response to neoadjuvant chemotherapy; the highest activities in MYC, E2F1, Ras, -Catenin and IFN- pathways; and poor prognosis predicted by 14 independent prognostic signatures. Based on a multivariate analysis, this new gene signature, termed ClinicoMolecular Triad Classification, predicted recurrence and treatment response better than all pathologic parameters and other prognostic signatures.

Publication Title

A new gene expression signature, the ClinicoMolecular Triad Classification, may improve prediction and prognostication of breast cancer at the time of diagnosis.

Sample Metadata Fields

Specimen part

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accession-icon GSE16984
Comparability and concordance of replicated microarray data.
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge IconIllumina humanRef-8 v2.0 expression beadchip

Description

To measures the comparability and concordance of Illumina microarray, a series of 30 samples of Universal Human Reference RNA (UHRR) were set as controls for every single chip of total 30 Human-Ref V2 BeadChips. The average bead number of the 30 arrays was 42.38.1 for any bead type over the 22,184 probes. A high average correlation coefficient (r) value was obtained as 0.99080077 relative to each other of the expression intensity values from the 30 duplicate UHRR samples.

Publication Title

A new gene expression signature, the ClinicoMolecular Triad Classification, may improve prediction and prognostication of breast cancer at the time of diagnosis.

Sample Metadata Fields

Disease

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accession-icon GSE81723
Transdifferentiation Of Human Dermal Fibroblasts Towards The Cardiac Cell Lineage
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Transdifferentiation has been recently described as a novel method for converting human fibroblasts into induced cardiomyocyte-like cells. Such an approach can produce differentiated cells to study physiology or pathophysiology, examine drug interactions or toxicities, and engineer tissues. Here we describe the transdifferentiation of human dermal fibroblasts towards the cardiac cell lineage via the induced expression of transcription factors (TFs) GATA4, TBX5, MEF2C, MYOCD, NKX2-5, and delivery of microRNAs miR-1 and miR-133a. Cells undergoing transdifferentiation expressed ACTN2 and TNNT2 and partially organized their cytoskeleton in a cross-striated manner. The conversion process was associated with significant upregulation of a cohort of cardiac-specific genes, activation of pathways associated with muscle contraction and physiology, and downregulation of fibroblastic markers. We used a genetically encoded calcium indicator and readily detected active calcium transients although no spontaneous contractions were observed in transdifferentiated cells. Finally, we determined that inhibition of Janus kinase 1, inhibition of glycogen synthase kinase 3, or addition of NRG1 significantly enhanced the efficiency of transdifferentiation. Overall, we describe a method for achieving transdifferentiation of human dermal fibroblasts into induced cardiomyocyte-like cells via transcription factor overexpression, microRNA delivery, and molecular pathway manipulation.

Publication Title

Core Transcription Factors, MicroRNAs, and Small Molecules Drive Transdifferentiation of Human Fibroblasts Towards The Cardiac Cell Lineage.

Sample Metadata Fields

Specimen part, Treatment, Time

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accession-icon GSE23386
Clinical relevance of DNA microarray analyses using archival formalin-fixed paraffin-embedded breast cancer specimens
  • organism-icon Homo sapiens
  • sample-icon 25 Downloadable Samples
  • Technology Badge IconIllumina HumanRef-8 v3.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Clinical relevance of DNA microarray analyses using archival formalin-fixed paraffin-embedded breast cancer specimens.

Sample Metadata Fields

Age, Specimen part, Disease stage

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accession-icon GSE2275
A Bioinformatic Analysis of Arginine-Sensitive Regulation of rat Hepatic Gene Expression
  • organism-icon Rattus norvegicus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Goals of the Study:

Publication Title

Short-term arginine deprivation results in large-scale modulation of hepatic gene expression in both normal and tumor cells: microarray bioinformatic analysis.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE44401
Transcription factors MYOCD, SRF, Mesp1 and SMARCD3 significantly enhance the cardio-inducing effect of GATA4, TBX5, and MEF2C during direct cellular reprogramming
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Transient over-expression of defined combinations of master regulator genes can effectively induce cellular reprogramming: the acquisition of an alternative predicted phenotype from a differentiated cell lineage. This can be of particular importance in cardiac regenerative medicine wherein the heart lacks the capacity to heal itself, but simultaneously contains a large pool of fibroblasts. In this study we determined the cardio-inducing capacity of ten transcription factors to actuate cellular reprogramming of mouse embryonic fibroblasts into cardiomyocyte-like cells. Over-expression of transcription factors MYOCD and SRF alone or in conjunction with Mesp1 and SMARCD3 significantly enhanced the basal but necessary cardio-inducing effect of the previously reported GATA4, TBX5, and MEF2C. In particular, combinations of five or seven transcription factors significantly enhanced the activation of cardiac reporter vectors, and induced an upregulation of cardiac-specific genes. Global gene expression analysis also demonstrated a significantly greater cardio-inducing effect when the transcription factors MYOCD and SRF were used. Detection of cross-striated cells was highly dependent on the cell culture conditions and was enhanced by the addition of valproic acid and JAK inhibitor. Although we detected Ca2+ transient oscillations in the reprogrammed cells, we did not detect significant changes in resting membrane potential or spontaneously contracting cells. This study further elucidates the cardio-inducing effect of the transcriptional networks involved in cardiac cellular reprogramming, contributing to the ongoing rational design of a robust protocol required for cardiac regenerative therapies.

Publication Title

Transcription factors MYOCD, SRF, Mesp1 and SMARCD3 enhance the cardio-inducing effect of GATA4, TBX5, and MEF2C during direct cellular reprogramming.

Sample Metadata Fields

Specimen part

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accession-icon GSE73469
Transdifferentiation of Human Endothelial Progenitors into Smooth Muscle Cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Derivation of induced smooth muscle cells (iSMC) through direct transdifferentiation of a convenient and expandable primary cell source would open a wide range of prospects for their use in tissue engineering, drug testing, and disease modeling. Hypothesizing that MYOCD as a master regulator of smooth muscle gene expression would facilitate the generation of iSMC, we studied the conversion of human endothelial progenitor cells (EPC) into iSMC through the induced expression of by over-expression of MYOCD. A significant cytoskeletal rearrangement of the EPC resembling that of mesenchymal cells occurred within 3 days post initiation of MYOCD expression. This transition was associated with a downregulation of endothelial cell surface markers (CD31, CD105) as determined by flow cytometry. By day 7, iSMC derivation was evident with a significant upregulation of smooth muscle markers ACTA2, MYH11, TAGLN, and downregulation of CD31 and CDH5 as determined by gene expression analysis. Immunofluorescence revealed expression of MYH11 and ACTA2 and absence of endothelial markers VWF and CD31. By two weeks, microarray gene expression analysis demonstrated a significant similarity between iSMC and umbilical artery SMC (UASMC). The iSMC continued to develop toward the SMC lineage after four weeks of MYOCD induced expression. Microarray gene expression analysis showed an upregulation of molecular pathways associated with smooth muscle contraction and cytoskeletal reorganization in iSMC. Calcium transients were detected in iSMC when stimulated with phenylephrine but not in EPC. Contractility of iSMC was also higher than that of EPC as determined by traction force microscopy. Tissue-engineered blood vessels constructed using iSMC showed functionality with respect to flow- and drug- mediated vasodilation and vasoconstriction.

Publication Title

Transdifferentiation of human endothelial progenitors into smooth muscle cells.

Sample Metadata Fields

Time

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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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