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accession-icon GSE18912
Expression profiling of breast cancer cell lines MCF-7 and MCF-7R4
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Human breast cancer cell line MCF-7 is usually sensitive to chemotherapy drug BMS-554417, an insulin receptor (IR) and insulin-like growth factor receptor (IGFR) inhibitor. However, through step-wise increase in BMS-554417 doses in culture media, we were able able to screen and select a single MCF-7 clone that is BMS-554417 resistant. It is cross resistant to BMS-536924. This new line of MCF-7 cells was named as MCF-7R4. The transcriptome profiling of both MCF-7 and MCF-7R4 was performed using Affymetrix HG-U133 plus2.0 GeneChip arrays.

Publication Title

Drug efflux by breast cancer resistance protein is a mechanism of resistance to the benzimidazole insulin-like growth factor receptor/insulin receptor inhibitor, BMS-536924.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon SRP002326
Ultra-high throughput sequencing-based small RNA discovery and discrete statistical biomarker analysis in a collection of cervical tumors and matched controls
  • organism-icon Homo sapiens
  • sample-icon 38 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzer

Description

We prepared small RNA libraries from 29 tumor/normal pairs of human cervical tissue samples. Analysis of the resulting sequences (42 million in total) defined 64 new human microRNA (miRNA) genes. Both arms of the hairpin precursor were observed in twenty-three of the newly identified miRNA candidates. We tested several computational approaches for analysis of class differences between high throughput sequencing datasets, and describe a novel application of log linear model that has provided the most datasets, and describe a novel application of log linear model that has provided the most effective analysis for this data. This method resulted in the identification of 67 miRNAs that were differentially-expressed between the tumor and normal samples at a false discovery rate less than 0.001. Overall design: A total of 29 tumor/normal pairs of human cervical tissue samples were analyzed. Two samples (G699N_2 and G761T_2) were performed in duplicates. No Fastq files for GSM532871 to GSM532889, GSM532929, and GSM532930. Sequence files are provided as text files for these 22 Sample records in GSE20592_RAW.tar. 38 samples with quality scores are available from SRA as SRP002/SRP002326 (see Supplementary file below).

Publication Title

Ultra-high throughput sequencing-based small RNA discovery and discrete statistical biomarker analysis in a collection of cervical tumours and matched controls.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP023262
A shared transcriptional program in early breast neoplasias despite genetic and clinical distinctions
  • organism-icon Homo sapiens
  • sample-icon 80 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

The earliest recognizable stages of breast neoplasia are lesions that represent a heterogeneous collection of epithelial proliferations currently classified based on morphology. Their role in the development of breast cancer is not well understood but insight into the critical events at this early stage will improve efforts in breast cancer detection and prevention. These microscopic lesions are technically difficult to study so very little is known about their molecular alterations. To characterize the transcriptional changes of early breast neoplasia, we sequenced 3''- end enriched RNAseq libraries from formalin-fixed paraffin-embedded tissue of early neoplasia samples and matched normal breast and carcinoma samples from 25 patients. We find that gene expression patterns within early neoplasias are distinct from both normal and breast cancer patterns and identify a pattern of pro-oncogenic changes, including elevated transcription of ERBB2, FOXA1, and GATA3 at this early stage. We validate these findings on a second independent gene expression profile data set generated by whole transcriptome sequencing. Measurements of protein expression by immunohistochemistry on an independent set of early neoplasias confirms that ER pathway regulators FOXA1 and GATA3, as well as ER itself, are consistently upregulated at this early stage. The early neoplasia samples also demonstrate coordinated changes in long non-coding RNA expression and microenvironment stromal gene expression patterns. This study is the first examination of global gene expression in early breast neoplasia, and the genes identified here represent candidate participants in the earliest molecular events in the development of breast cancer. Overall design: 3SEQ was performed on 72 FFPE human breast samples from 25 patients: 24 normal, 25 early neoplasia, 9 carcinoma in situ, and 14 invasive cancer

Publication Title

A shared transcriptional program in early breast neoplasias despite genetic and clinical distinctions.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Subject

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accession-icon SRP159013
Gene exression in single T cells across division states.
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

Purpose: To compare diversity of primary human CD8+ T cells that have divided 0, 1, or 2 times on day 3 of ex vivo expansion from naïve resting state. Methods: Naïve T cells were enriched from human peripheral blood monoluclear cells (PBMCs), labeled with CFSE dye, and expanded for 3 days using rapid expansion protocol (Li, Y. & Kurlander, R.J. Journal of Translational Medicine, 2010). On day 3, 10,000 single live CFSE+ CD8+ T cells from each of divisions 0, 1, and 2 were sorted and immediately processed using 10X Genomics single-cell RNA-sequencing platform. Results: We found that undivided cells display the highest gene expression diversity. Using 1,000 most variably expressed genes, we created a force-directed layout, representing a phenotypic map of cellular differentiation across division states. To understand the basis of T-cell diversity, we defined and quantified regions of interest on this map based on diffusion pseudo-time (DPT), a metric of cell differentiation state. Finally, we examined gene expression in cells from each region and found that undivided cells acquire gene expression associated with effector cell function, while remaining cells go on to grow and differentiate. Conclusions: Our study provides insights into T-cell differentiation within an ex vivo expansion system for cancer immunotherapy applications. Overall design: A total of 4,060 cells (division 0: n = 552 cells, division 1: n = 1,777 cells, division23: n = 1,731 cells) were sequenced to an average of 52,040 post-normalization reads per cell capturing a median of 18,770 unique molecular identifier (UMI) counts per cell mapping to 3,544 unique genes per cell.

Publication Title

Proliferation tracing with single-cell mass cytometry optimizes generation of stem cell memory-like T cells.

Sample Metadata Fields

Subject

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accession-icon GSE19830
Expression data from pure/mixed brain, liver and lung to test feasability and sensitivity of statistical deconvolution
  • organism-icon Rattus norvegicus
  • sample-icon 42 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Tissues are often made up of multiple cell-types. Blood, for example, contains many different cell-types, each with its own functional attributes and molecular signature. In humans, because of its accessibility and immune functionality, blood cells have been used as a source for RNA-based biomarkers for many diseases. Yet, the proportions of any given cell-type in the blood can vary markedly, even between normal individuals. This results in a significant loss of sensitivity in gene expression studies of blood cells and great difficulty in identifying the cellular source of any perturbations. Ideally, one would like to perform differential expression analysis between patient groups for each of the cell-types within a tissue but this is impractical and prohibitively expensive.

Publication Title

Cell type-specific gene expression differences in complex tissues.

Sample Metadata Fields

Specimen part

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accession-icon GSE20300
Whole blood gene expression analysis of stable and acute rejection pediatric kidney transplant patients
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Full title: Expression data from whole blood gene expression analysis of stable and acute rejection pediatric kidney transplant patients

Publication Title

Cell type-specific gene expression differences in complex tissues.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE48839
Genome-wide transcript profiling for native porcine valvular interstitial cells and those cultured on TCPS and treated with TGF-1
  • organism-icon Sus scrofa
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Porcine Genome Array (porcine)

Description

Fibrotic diseases have significant health impact and have been associated with differentiation of the resident fibroblasts into myofibroblasts. In particular, stiffened extracellular matrix and TGF-1 in fibrotic lesions have been shown to promote pathogenic myofibroblast activation and progression of fibrosis in various tissues. To better understand the roles of mechanical and chemical cues on myofibroblast differentiation and how they may crosstalk, we cultured primary valvular interstitial cells (VICs) isolated from porcine aortic valves and studied how traditional TCPS culture, which presents a non-physiologically stiff environment, and TGF-1 affect native VIC phenotypes.

Publication Title

Hydrogels preserve native phenotypes of valvular fibroblasts through an elasticity-regulated PI3K/AKT pathway.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE65588
Expression data from B220+ Hspa9+/+ and Hspa9+/- CFU-PreB colonies isolated on Day 7 of culture
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

CFU-PreB colonies are reduced in number and size in Hspa9+/- mice compared to wildtype littermates. We compared the expression profiles of these colonies to gain insight into the mechanism driving this difference.

Publication Title

Reduced levels of Hspa9 attenuate Stat5 activation in mouse B cells.

Sample Metadata Fields

Specimen part

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accession-icon SRP066807
Impact of Prnp genetic ablation in the hippocampus transcriptome of congenic B6.129-PrnpZH1/ZH1 or coisogenic C57BL/6-PrnpZH3/ZH3 mice
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

To study the effect of Prnp genetic ablation on different aspects of RNA metabolism, we performed RNA sequencing of the hippocampus of wild-type C57BL/6J, congenic B6.129-PrnpZH1/ZH1 and coisogenic C57BL/6J-PrnpZH3/ZH3 mice. We analyzed differential gene expression, exon usage and RNA editing. Overall design: RNA sequencing on hippocampus of wild-type C57BL/6 mice, congenic B6.129-PrnpZH1/ZH1 and coisogenic C57BL/6-PrnpZH3/ZH3 mice (3 month-old males, n=4 per genotype).

Publication Title

Strictly co-isogenic C57BL/6J-Prnp-/- mice: A rigorous resource for prion science.

Sample Metadata Fields

Sex, Age, Specimen part, Cell line, Subject

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accession-icon GSE79074
Jurkat T cell gene expression with IKKe gene knockdown and PMA and ionomycin stimulation
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We used microarray to monitor the differentially expresed genes during Jurkat T cell activaiton.

Publication Title

IκB Kinase ε Is an NFATc1 Kinase that Inhibits T Cell Immune Response.

Sample Metadata Fields

Cell line

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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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