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accession-icon GSE48391
Concurrent Gene Signatures for Han Chinese Breast Cancers
  • organism-icon Homo sapiens
  • sample-icon 81 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Concurrent gene signatures for han chinese breast cancers.

Sample Metadata Fields

Specimen part

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accession-icon GSE48390
Concurrent Gene Signatures for Han Chinese Breast Cancers [Affymetrix]
  • organism-icon Homo sapiens
  • sample-icon 81 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival. Distributions of signature genes were strongly associated with chromosomal location: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer.

Publication Title

Concurrent gene signatures for han chinese breast cancers.

Sample Metadata Fields

Specimen part

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accession-icon GSE73617
Modulation of reversibility by DNA Methyltransferases during hepatogenic differentiation in Mesenchymal Stromal Cells
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Mesenchymal stromal cells (MSCs) hold great promise in the field of liver regenerative medicine. However, the mechanisms and reversibility of hepatogenic differentiation in MSCs are poorly understood. Here, we demonstrate that hepatogenic differentiation of MSCs is a reversible process and is modulated by the transforming growth factor beta 1- DNA methyltransferases (TGF-1-Dnmts) axis. Dnmt1 and Dnmt3a differentially regulate hepatogenic differentiation and de-differentiation in response to the alternation of TGF-1 concentration. Knockdown of Dnmt1 accelerates the hepatogenic differentiation in MSCs-derived hepatocyte-like cells (dHeps) whereas Knockdown of Dnmt3a represses hepatogenic differentiation. Conclusions: Our finding first demonstrates that epigenetic regulation by Dnmts in response to stimulation from the surrounding microenvironment controls the reversibility of hepatogenic differentiation in MSCs. Manipulation of Dnmts provides a rapid and efficient differentiation protocol to generate functional dHeps from MSCs that may provide clinical potential for regenerative medicine.

Publication Title

DNA Methyltransferases Modulate Hepatogenic Lineage Plasticity of Mesenchymal Stromal Cells.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE43330
Fanconi anemia proteins interact with CtBP1 and modulate the expression of the Wnt antagonist Dickkopf-1
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Fanconi anemia (FA) is a genetic disorder characterized by congenital abnormalities, bone marrow failure and increased susceptibility to cancer. Of the fifteen FA proteins, Fanconi anemia group C (FANCC) is one of eight FA core complex components of the FA pathway. Unlike other FA core complex proteins, FANCC is mainly localized in the cytoplasm, where it is thought to function in apoptosis, redox regulation, cytokine signaling and other processes. Previously, we showed that regulation of FANCC involved proteolytic processing during apoptosis. To elucidate the biological significance of this proteolytic modification, we searched for molecular interacting partners of proteolytic FANCC fragments. Among the candidates obtained, the transcriptional corepressor protein C-terminal binding protein-1 (CtBP1) interacted directly with FANCC and other FA core complex proteins. Although not required for stability of the FA core complex or ubiquitin ligase activity, CtBP1 is essential for proliferation, cell survival and maintenance of chromosomal integrity. Expression profiling of CtBP1-depleted and FA-depleted cells revealed that several genes were commonly up- and down-regulated, including the Wnt antagonist Dickkopf-1 (DKK1). These findings suggest that FA and Wnt signaling via CtBP1 could share common effectors.

Publication Title

Fanconi anemia proteins interact with CtBP1 and modulate the expression of the Wnt antagonist Dickkopf-1.

Sample Metadata Fields

Cell line

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accession-icon GSE13139
LOX-1-dependent transcriptional regulation after oxidized LDL (OxLDL) treatment of human aortic endothelial cells.
  • organism-icon Homo sapiens
  • sample-icon 52 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

LOX-1 is the primary endothelial receptor for oxidized LDL in endothelial cells and plays a role in the development of atherosclerosis. Expression profiling was carried out on samples from HAECT cells over-expressing either LOX-1 or GFP control and treated with or without OxLDL over a time course of 2, 6, 12 and 24 Hours. The goal of the study was to identify genes expression changes activated by OxLDL binding to LOX-1 at several different time points.

Publication Title

LOX-1-dependent transcriptional regulation in response to oxidized LDL treatment of human aortic endothelial cells.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE9674
Expression data from Arabidopsis plants misexpressing AtMYB30 after Xanthomonas inoculation at early timepoints
  • organism-icon Arabidopsis thaliana
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Plant immune responses to pathogen attack involve various defense mechanisms and among them, the Hypersensitive Response (HR), a form of programmed cell death occurring at invasion sites. AtMYB30, a transcription factor acts as a positive regulator of a cell death pathway conditioning the HR.

Publication Title

A MYB transcription factor regulates very-long-chain fatty acid biosynthesis for activation of the hypersensitive cell death response in Arabidopsis.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE44104
COL11A1 promotes tumor progression and predicts poor clinical outcome in ovarian cancer.
  • organism-icon Homo sapiens
  • sample-icon 55 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Biomarkers that predict disease progression might assist the development of better therapeutic strategies for aggressive cancers, such as ovarian cancer. Here, we investigated the role of collagen type XI alpha 1 (COL11A1) in cell invasiveness and tumor formation and the prognostic impact of COL11A1 expression in ovarian cancer. Microarray analysis suggested that COL11A1 is a disease progression-associated gene that is linked to ovarian cancer recurrence and poor survival.

Publication Title

COL11A1 promotes tumor progression and predicts poor clinical outcome in ovarian cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE46892
Generating mouse model with predominant nave or innate memory phenotype CD4+ T cells
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Innate memory phenotype (IMP) CD4+ T cells are non-conventional T cells exhibiting features of innate immune cells, characterized as CD44high and CD62Llow in periphery. It is recently reported by our group that bone marrow chimeric mice lacking thymic MHCI expression develop predominantly IMP CD8+ T cells, while those lacking hematopoietic MHCI develop predominantly nave CD8+ T cells. Here we perform hirarchical clustering analysis and found that CD4+ T cells share similar property: chimeras lacking thymic MHCII gave rise to predominantly CD4+ T cells that resemble IMP CD4+ T cells observed in WT mice, and vice versa, chimeras lacking hematopoietic MHCII had a majority of nave-like CD4+ T cells resembling naveCD4+ T cells seen in WT mice.

Publication Title

Dendritic cell-MHC class II and Itk regulate functional development of regulatory innate memory CD4+ T cells in bone marrow transplantation.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE46272
PINT lincRNA connects the p53 pathway with epigenetic silencing by the Polycomb Repressive Complex 2
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Pint lincRNA connects the p53 pathway with epigenetic silencing by the Polycomb repressive complex 2.

Sample Metadata Fields

Specimen part, Disease, Cell line, Treatment, Subject

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accession-icon GSE46247
PINT lincRNA connects the p53 pathway with epigenetic silencing by the Polycomb Repressive Complex 2 (MEF cells)
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

It has been recently shown that the transcription factor p53 induces the expression of multiple lincRNAs. However, relatively little is known about the role that lincRNAs play in this pathway. Here we characterize a lincRNA named PINT (p53 Induced Noncoding Transcript). We show that PINT is a ubiquitously expressed lincRNA that is finely regulated by p53. In mouse cells, PINT promotes cell proliferation and survival by regulating the expression of genes of TGF-beta, MAPK and p53 pathways. PINT is a nuclear lincRNA that directly interacts with Polycomb Repressive Complex 2 (PRC2), being required for PRC2 targeting of specific genes for repression. Furthermore, PINT functional activity is dependent on PRC2 expression, representing a connection between the p53 pathway and epigenetic regulation by PRC2. We have also identified PINT human ortholog (hPINT), which presents suggestive analogies with the mouse lincRNA. hPINT is similarly regulated by p53, and its expression correlates significantly with the same cellular pathways as the mouse ortholog, including the p53 pathway. Interestingly, hPINT is significantly downregulated in colon cancer, representing a novel tumor suppressor candidate. Our results not only help our understanding of the role of p53 and lincRNAs in cancer, but also contribute to the open debate regarding the utility of mouse models for the study of lincRNAs.

Publication Title

Pint lincRNA connects the p53 pathway with epigenetic silencing by the Polycomb repressive complex 2.

Sample Metadata Fields

Specimen part, Treatment

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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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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