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accession-icon GSE23176
Oncogene activation induces metabolic transformation resulting in insulin independence in human breast cancer cells
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge IconIllumina humanRef-8 v2.0 expression beadchip, Illumina HumanRef-8 v3.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Oncogene activation induces metabolic transformation resulting in insulin-independence in human breast cancer cells.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Time

View Samples
accession-icon GSE22955
Genome-wide analysis of time-dependent gene expression in SUM-225 cells treated with the HER-2-specific inhibitor CP724,714 for 45 hours
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge IconIllumina humanRef-8 v2.0 expression beadchip, Illumina HumanRef-8 v3.0 expression beadchip

Description

Results of blocking the HER-2 oncogene kinase function in SUM-225 cells by treatment with CP724,714 and measuring gene expression as a function of time provides information as to what genes are regulated by HER-2 in this breast cancer cell line.

Publication Title

Oncogene activation induces metabolic transformation resulting in insulin-independence in human breast cancer cells.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Time

View Samples
accession-icon GSE26079
Genome-wide analysis gene expression in SUM-149 cells expressing AREG shRNA
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip

Description

Results of knocking-down AREG expression in SUM-149 cells by lenitviral infection of shRNA vectors and measuring gene expression provides information as to what genes are regulated by AERG in inflammatory breast cancer cells.

Publication Title

Knock-down of amphiregulin inhibits cellular invasion in inflammatory breast cancer.

Sample Metadata Fields

Disease, Disease stage, Cell line

View Samples
accession-icon GSE12708
ERR mediates Tamoxifen resistance in novel models of invasive lobular breast cancer
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

One-third of all ER+ breast tumors treated with endocrine therapy fail to respond, and the remainder are likely to relapse in the future. Almost all data on endocrine resistance has been obtained in models of invasive ductal carcinoma (IDC). However, invasive lobular carcinomas (ILC) comprise up to 15% of newly diagnosed invasive breast cancers diagnosed each year and, while the incidence of IDC has remained relatively constant during the last 20 years, the prevalence of ILC continues to increase among postmenopausal women. We report a new model of Tamoxifen (TAM)-resistant invasive lobular breast carcinoma cells that provides novel insights into the molecular mechanisms of endocrine resistance. SUM44 cells express ER and are sensitive to the growth inhibitory effects of antiestrogens. Selection for resistance to 4-hydroxytamoxifen led to the development of the SUM44/LCCTam cell line, which exhibits decreased expression of estrogen receptor alpha (ER) and increased expression of the estrogen-related receptor gamma (ERR). Knockdown of ERR in SUM44/LCCTam cells by siRNA restores TAM sensitivity, and overexpression of ERR blocks the growth-inhibitory effects of TAM in SUM44 and MDA-MB-134 VI lobular breast cancer cells. ERR-driven transcription is also increased in SUM44/LCCTam, and inhibition of activator protein 1 (AP1) can restore or enhance TAM sensitivity. These data support a role for ERR/AP1 signaling in the development of TAM resistance, and suggest that expression of ERR may be a marker of poor Tamoxifen response.

Publication Title

ERRgamma mediates tamoxifen resistance in novel models of invasive lobular breast cancer.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE48984
Glutamine sensitivity analysis identifies the xCT antiporter as a common triple negative breast tumor therapeutic target.
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

A small number of tumor-derived cell lines have formed the mainstay of cancer therapeutic development, yielding drugs with impact typically measured as months to disease progression. To develop more effective breast cancer therapeutics, and more readily understand their potential clinical impact, we constructed a functional metabolic portrait of 46 independently-derived breast tumorigenic cell lines, contrasted with purified normal breast epithelial subsets, freshly isolated pleural effusion breast tumor samples and culture-adapted, non-tumorigenic mammary epithelial cell derivatives. We report our analysis of glutamine uptake, dependence, and identification of a significant subset of triple negative samples that are glutamine auxotrophs. This NCBI GEO submission comprises a small datasest generated to compare the expression profiles of the above nontumorigenic, purified normal and purified pleural effusion samples with 10 established breast cancer-derived cell lines. This dataset was subsequently merged with a previously published expression dataset derived from 45 independent breast cancer derived cell lines (Neve, et al 2006), and analyses contrasting various subsets of the merged dataset were published.

Publication Title

Glutamine sensitivity analysis identifies the xCT antiporter as a common triple-negative breast tumor therapeutic target.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE69017
caArray_gray-00215: A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes
  • organism-icon Homo sapiens
  • sample-icon 50 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Recent studies suggest that thousands of genes may contribute to breast cancer pathophysiologies when deregulated by genomic or epigenomic events. Here, we describe a model system to appraise the functional contributions of these genes to breast cancer subsets. In general, the recurrent genomic and transcriptional characteristics of 51 breast cancer cell lines mirror those of 145 primary breast tumors, although some significant differences are documented. The cell lines that comprise the system also exhibit the substantial genomic, transcriptional, and biological heterogeneity found in primary tumors. We show, using Trastuzumab (Herceptin) monotherapy as an example, that the system can be used to identify molecular features that predict or indicate response to targeted therapies or other physiological perturbations.

Publication Title

A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes.

Sample Metadata Fields

Cell line

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accession-icon SRP183468
Phospho-small RNA-seq reveals circulating, extracellular mRNA/lncRNAs as potential biomarkers in human plasma: Hematopoietic Stem Cell Transplant [HSCT]
  • organism-icon Homo sapiens
  • sample-icon 44 Downloadable Samples
  • Technology Badge Icon

Description

Extracellular RNAs (exRNAs) in blood and other biofluids have attracted great interest as potential biomarkers in liquid biopsy applications, as well as for their potential biological functions. Whereas it is well-established that extracellular microRNAs are present in human blood circulation, the degree to which messenger RNAs (mRNA) and long noncoding RNAs (lncRNA) are represented in plasma is less clear. Here we report that mRNA and lncRNA species are present as small fragments in plasma that are not detected by standard small RNA-seq methods, because they lack 5'-phosphorylation or carry 3'-phosphorylation. We developed a modified sequencing protocol (termed "phospho-sRNA-seq") that incorporates upfront RNA treatment with T4 polynucleotide kinase (which also has 3' phosphatase activity) and compared it to a standard small RNA-seq protocol, using as input both a pool of synthetic RNAs with diverse 5' and 3' end chemistries, as well exRNA isolated from human blood plasma. Using a custom, high-stringency pipeline for data analysis we identified mRNA and lncRNA transcriptome fingerprints in plasma, including multiple tissue-specific gene sets. In a longitudinal study of hematopoietic stem cell transplant (HSCT) patients, we found different sets corresponding to bone marrow- and liver- enriched genes, which tracked with bone marrow recovery or liver injury, providing proof-of-concept validation of this method as a biomarker approach. By accessing a previously unexplored realm of mRNA and lncRNA fragments in blood plasma, phospho-sRNA-seq opens up a new space for plasma transcriptome-based biomarker development in diverse clinical settings. Overall design: ExRNA-seq libraries were prepared from platelet-poor plasma obtained from serial blood draws collected from two individuals undergoing bone marrow transplantation. A total of 11 samples were collected from each individual, starting prior to chemotherapy/ratiation treatment (approximately 7 days pre-HSCT) the day of transplant, and then weekly up to approximately Day 63.

Publication Title

Phospho-RNA-seq: a modified small RNA-seq method that reveals circulating mRNA and lncRNA fragments as potential biomarkers in human plasma.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE54870
Transcription profiling by array of wild type and arr1,10,12 mutant Arabidopsis seedlings treated with the cytokinin benzyladenine
  • organism-icon Arabidopsis thaliana
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Effect of the cytokinin BA on wt and arr1,10,12 mutant seedlings

Publication Title

Type B response regulators of Arabidopsis play key roles in cytokinin signaling and plant development.

Sample Metadata Fields

Age, Specimen part

View Samples
accession-icon GSE21411
Systems biology of interstitial lung diseases
  • organism-icon Homo sapiens
  • sample-icon 29 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

Systems biology of interstitial lung diseases: integration of mRNA and microRNA expression changes.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE21369
Gene expression profiles of interstitial lung disease (ILD) patients
  • organism-icon Homo sapiens
  • sample-icon 29 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The mechanisms and molecular pathways underlying interstitial lung diseases (ILDs) are poorly understood. Systems biology approaches were used to identify perturbed networks in these disease states to gain a better understanding of the underlying mechanisms of disease. Through profiling genes and miRNAs, we found subsets of genes and miRNAs that distinguish different disease stages, ILDs from controls, and idiopathic pulmonary fibrosis (IPF) from non-specific interstitial pneumonitis (NSIP). Traditional pathway analysis revealed several disease-associated modules involving genes from the TGF-beta, Wnt, focal adhesion and smooth muscle actin pathways that may be involved in advancing fibrosis.

Publication Title

Systems biology of interstitial lung diseases: integration of mRNA and microRNA expression changes.

Sample Metadata Fields

Specimen part, Disease

View Samples

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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