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accession-icon GSE28979
Gene expression profiles of serous ovarian cancer in human and mouse
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip, Illumina HumanWG-6 v3.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

High-grade serous ovarian cancer arises from fallopian tube in a mouse model.

Sample Metadata Fields

Specimen part, Disease, Disease stage

View Samples
accession-icon GSE14256
Human fibroblast stimulation with PDGF-BB or b-FGF
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

We analyzed gene expression in human fibroblasts stimulated by platelet-derived growth factor-BB (PDGF-BB) or basic fibroblast growth factor (bFGF) for 1h and 24h. The results of two independent experiments were merged. SAM analysis identified 116 relevant probe sets. Hierarchical clustering of these probe sets showed divergent early gene regulation by PDGF and FGF but overlapping late response. We first analyzed genes commonly regulated by PDGF-BB and b-FGF more than 2 fold after 24h of stimulation and we found that these two growth factors repressed FOXO.

Publication Title

The transcription of FOXO genes is stimulated by FOXO3 and repressed by growth factors.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE28721
Gene expression analysis of human serious ovarian tumors and fimbria control
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

The cell of origin of serious ovarian cancer is unknown. To create a mouse model for this lethal cancer and identify early cancer biomarkers, we conditionally deleted both Dicer (essential for microRNA biosynthesis) and Pten (a negative regulator of the PI3K pathway) in the female reproductive tract. Beginning at ~3-5 months, these Dicer/Pten mutant mice develop high-grade serious carcinomas that initiate in the stroma of the fallopian tube through a mesenchymal-to-epithelial transition (MET), subsequently envelop the ovary, and then metastasize throughout the peritoneum, resulting in ascites and 100% lethality by 13 months. The fallopian tube cancers demonstrate upregulation of genes encoding known and novel secreted proteins that are potential biomarkers. This study uncovers a new paradigm for the initiation of high-grade serous ovarian cancer.

Publication Title

High-grade serous ovarian cancer arises from fallopian tube in a mouse model.

Sample Metadata Fields

Specimen part, Disease, Disease stage

View Samples
accession-icon GSE6461
SYT-SSX murine synovial sarcoma model
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The human SYT-SSX fusion protein was expressed in a developmentally dependent fashion in murine myoblasts. Tumors harvested from mice in adolescence were compared to normal mouse skeletal muscle samples.

Publication Title

A conditional mouse model of synovial sarcoma: insights into a myogenic origin.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE28720
Gene expression analysis of ovarian tumors from mice with knockout of DICER and PTEN
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip, Illumina HumanWG-6 v3.0 expression beadchip

Description

The cell of origin of serious ovarian cancer is unknown. To create a mouse model for this lethal cancer and identify early cancer biomarkers, we conditionally deleted both Dicer (essential for microRNA biosynthesis) and Pten (a negative regulator of the PI3K pathway) in the female reproductive tract. Beginning at ~3-5 months, these Dicer/Pten mutant mice develop high-grade serious carcinomas that initiate in the stroma of the fallopian tube through a mesenchymal-to-epithelial transition (MET), subsequently envelop the ovary, and then metastasize throughout the peritoneum, resulting in ascites and 100% lethality by 13 months. The fallopian tube cancers demonstrate upregulation of genes encoding known and novel secreted proteins that are potential biomarkers. This study uncovers a new paradigm for the initiation of high-grade serous ovarian cancer.

Publication Title

High-grade serous ovarian cancer arises from fallopian tube in a mouse model.

Sample Metadata Fields

Specimen part, Disease, Disease stage

View Samples
accession-icon GSE99561
Liver samples of DO mice
  • organism-icon Mus musculus, Unidentified
  • sample-icon 267 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, Affymetrix Mouse Gene 2.1 ST Array (mogene21st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Systems genetics identifies a co-regulated module of liver microRNAs associated with plasma LDL cholesterol in murine diet-induced dyslipidemia.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE99558
Microarray measuring gene expression in livers of DO mice
  • organism-icon Mus musculus, Unidentified
  • sample-icon 267 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.1 ST Array (mogene21st), Illumina HiSeq 2000

Description

Genetic variation, in addition to environmental influences like diet, can govern the expression levels of microRNAs (miRNAs). MiRNAs are commonly found to operate cooperatively in groups to regulate gene expression. To investigate this, we combined small RNA sequencing, clinical phenotypes, and microarray data measuring gene expression from an outbred mouse model, the Diversity Outbred population. In the DO population, each individual has a distinct genome that is a mosaic of 8 inbred founder strains. We used these data to identify co-regulated modules of miRNAs and genes that are influenced by genetics and diet, and identify relationships between the modules and phenotypes in over 200 DO mice.

Publication Title

Systems genetics identifies a co-regulated module of liver microRNAs associated with plasma LDL cholesterol in murine diet-induced dyslipidemia.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE38831
Deciphering genomic alterations in colorectal cancer through transcriptional subtype-based network analysis
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

High-throughput genomic studies have identified thousands of genetic alterations in colorectal cancer (CRC). Distinguishing driver from passenger mutations is critical for developing rational therapeutic strategies. Because only a few transcriptional subtypes exist in previously studied tumor types, we hypothesize that highly heterogeneous genomic alterations may converge to a limited number of distinct mechanisms that drive unique gene expression patterns in different transcriptional subtypes. In this study, we defined transcriptional subtypes for CRC and identified driver networks/pathways for each subtype, respectively. Applying consensus clustering to a patient cohort with 1173 samples identified three transcriptional subtypes, which were validated in an independent cohort with 485 samples. The three subtypes were characterized by different transcriptional programs related to normal adult colon, early colon embryonic development, and epithelial mesenchymal transition, respectively. They also showed statistically different clinical outcomes. For each subtype, we mapped somatic mutation and copy number variation data onto an integrated signaling network and identified subtype-specific driver networks using a random walk-based strategy. We found that genomic alterations in the Wnt signaling pathway were common among all three subtypes; however, unique combinations of pathway alterations including Wnt, VEGF, Notch and TGF-beta drove distinct molecular and clinical phenotypes in different CRC subtypes. Our results provide a coherent and integrated picture of human CRC that links genomic alterations to molecular and clinical consequences, and which provides insights for the development of personalized therapeutic strategies for different CRC subtypes.

Publication Title

Deciphering genomic alterations in colorectal cancer through transcriptional subtype-based network analysis.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE51382
Retroviral overexpression or siRNA mediated knockdown of FOXP1 in DLBCL cell lines and primary human B cells
  • organism-icon Homo sapiens
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

To provide insight into the role of and target genes of the transcription factor FOXP1 in mature human B cells and in B cell non-Hodkgin lymhomas, we performed gene expression microarray studies, upon ectopic overexpression or silencing of FOXP1 in these cells.

Publication Title

FOXP1 directly represses transcription of proapoptotic genes and cooperates with NF-κB to promote survival of human B cells.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE10315
Multipotent mesenchymal stromal cells: identification of pathways common to TGF3/BMP2-induced chondrogenesis
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Human mesenchymal stem cells (MSC) display a high potential for the development of novel treatment strategies for cartilage repair. However, the pathways involved in their differentiation to functional and non hypertrophic chondrocytes remain largely unknown, despite the work on embryologic development and the identification of key growth factors including members of the TGF, Hh, Wnt and FGF families. In this study, we asked if we could identify specific biological networks independently from the growth factor used (TGF-3 or BMP-2). To address this question, we used DNA microarrays and performed large-scale expression profiling of MSC at different time points during their chondral differentiation. By comparing these data with those obtained during their differentiation into osteoblasts and adipocytes, we identified 318 genes specific for chondrogenesis. We distributed the selected genes in 5 classes according to their kinetic of expression and used the Ingenuity software in order to identify new biological networks. We could reconstruct 3 phases for chondral differentiation, characterized by functional pathways. The first phase corresponds to cell attachment and apoptosis prevention with the up-regulation of 5 integrins, BCL6, NFIL3, RGS2 and down-regulation of CTGF and CYR61. The second phase is characterized by a proliferation/differentiation step with the continuous expression of MAF, PGF, HGMA1 or NOTCH3, CHI3L1, WNT5A, LEPR. Finally, the last step of differentiation/hypertrophy is characterized by expression of DKK1, APOD/E, SERPINF1 and TIMP4. These data propose new pathways to understand the complexity of MSC differentiation to chondrocytes and new potential targets for cell therapy applied to cartilage repair.

Publication Title

Gene expression profile of multipotent mesenchymal stromal cells: Identification of pathways common to TGFbeta3/BMP2-induced chondrogenesis.

Sample Metadata Fields

No sample metadata fields

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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Developed by the Childhood Cancer Data Lab

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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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