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accession-icon GSE82203
Identification of DHT induced cell cycle dependent trascriptome and AR binding events
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Cell cycle-coupled expansion of AR activity promotes cancer progression.

Sample Metadata Fields

Cell line

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accession-icon GSE82201
Identification of DHT induced cell cycle dependent trascriptome in prostate cancer cells
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Evaluation of the genome wide impact of cell cycle position on DHT stimulated gene expression programs. Results show differential cell cycle regulated gene expression in different cell cycle phases.

Publication Title

Cell cycle-coupled expansion of AR activity promotes cancer progression.

Sample Metadata Fields

Cell line

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accession-icon SRP057758
RNA-seq in two ER+ breast cancer cell lines with and without progestins
  • organism-icon Homo sapiens
  • sample-icon 192 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Exploring effect of progesterone/progestin treatment on gene expression Overall design: Two cell lines, three conditions (Full Media with E2, E2+ Progesterone, Full Media + R5020 Progestin)

Publication Title

Progesterone receptor modulates ERα action in breast cancer.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE30407
The ets transcription factor ELF5 suppresses the estrogen sensitive phenotype and contributes to antiestrogen resistance in luminal breast cancer.
  • organism-icon Homo sapiens
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

ELF5 suppresses estrogen sensitivity and underpins the acquisition of antiestrogen resistance in luminal breast cancer.

Sample Metadata Fields

Cell line, Treatment, Time

View Samples
accession-icon GSE14328
Three non-invasive protein biomarkers for solid-organ transplant rejection found through integrative genomics
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We integrated three transplant rejection microarray studies examining gene expression in samples from pediatric renal, adult renal, and adult heart transplants. We performed one study ourselves and retrieved two others from the NCBI Gene Expression Omnibus (GEO)(GSE4470 and GSE1563). We identified 45 genes that were upregulated in common in acute rejection. Half were involved in one immune-related pathway. Among ten proteins we tested by serum ELISA, three successfully distinguished acute rejection from stable transplants. These were CXCL9, PECAM1, and CD44, with areas under the receiver operating characteristic curves of 0.844, 0.802, and 0.738, respectively. Immunohistochemistry showed that the PECAM1 protein was increased in acute rejection in renal, liver and heart transplants versus normal tissues. Our results show that integrating publicly-available gene expression data sets is a fast, powerful, and cost-effective way to identify serum-detectable diagnostic biomarkers.

Publication Title

Integrative urinary peptidomics in renal transplantation identifies biomarkers for acute rejection.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE37552
A Systems Biology Approach Reveals Common Metastatic Pathways in Osteosarcoma
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background

Publication Title

A systems biology approach reveals common metastatic pathways in osteosarcoma.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE41856
Cell growth in aggregates determines gene expression, proliferation, survival and chemoresistance of Follicular Lymphoma
  • organism-icon Homo sapiens
  • sample-icon 14 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

Cell growth in aggregates determines gene expression, proliferation, survival, chemoresistance, and sensitivity to immune effectors in follicular lymphoma.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE41855
Expression data from quiescent cells and cycling cells isolated from Multicellular aggregates of lymphoma cells (MALC)
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Follicular Lymphomas are blood tumors growing as spheres in patients. Before this study, there was no experimental model mimicking the 3D organization of these in vivo tumors. We develop such a model, called MALC, and observed a progressive enrichment in quiescent cells in these with time of culture; these cells were sorted, as their cycling counterparts, and their transcriptomes were compared. We used microarrays to detail the differential global gene expression profile between quiescent and cycling cells isolated from MALC.

Publication Title

Cell growth in aggregates determines gene expression, proliferation, survival, chemoresistance, and sensitivity to immune effectors in follicular lymphoma.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE41851
Expression data from follicular lymphoma cells cultured either in suspension either as Multicellular aggregates of lymphoma cells (MALC)
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Follicular Lymphomas are blood tumors growing as spheres in patients. Before this study, there was no experimental model mimicking the 3D organization of these in vivo tumors. We develop such a model, called MALC, and performed a pan-genomic comparative analysis between MALC and classical suspension cultures. We used microarrays to detail the global gene expression profile induced by aggregated growth of lymphoma cells.

Publication Title

Cell growth in aggregates determines gene expression, proliferation, survival, chemoresistance, and sensitivity to immune effectors in follicular lymphoma.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE26980
Expression data from melanoma cells grown under neural crest cell culture conditions (spheroid cells) versus under classical adherent conditions (adherent cells) - 2 different specimens of melanoma tumors
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Summary: Melanoma spheroids grown under neural crest cell conditions are highly plastic migratory/invasive tumor cells endowed with immunomodulator function

Publication Title

Melanoma spheroids grown under neural crest cell conditions are highly plastic migratory/invasive tumor cells endowed with immunomodulator function.

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)

fund-icon Fund the CCDL

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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