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accession-icon GSE11812
Gene expression profile of cancer cell lines of different origin
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Gene expression profile of cancer cell lines of breast, lung, pancreatic, gasctric, ovarian, hepatocellular, prostate carcinomas and melanomas.

Publication Title

Gene expression profiling of 30 cancer cell lines predicts resistance towards 11 anticancer drugs at clinically achieved concentrations.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP125118
Aged Hematopoietic Stem Cells Drive Aging-Associated Immune Remodeling
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Phenotypic and functional changes seen in the aged adaptive immune system are primarily driven by aging of hematopoietic stem cells (HSCs), pharmacological rejuvenated aged HSCs were able to reconstituted a youthful immune system Overall design: We employed RNA-seq to assess similarities/differences between naive CD4+ T cells and CD19+ B cells isolated from RAG1-/- recipients transplanted with either young, old or old rejuvenated (CASIN treated) HSCs

Publication Title

Aged murine hematopoietic stem cells drive aging-associated immune remodeling.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon GSE11001
Genome-wide expression profiling from formalin-fixed paraffin-embedded breast cancer core biopsies
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The routine workflow for invasive cancer diagnostics is based on biopsy processing by formalin fixation and subsequent paraffin embedding. Formalin-fixed paraffin-embedded (FFPE) tissue samples are easy to handle, stable and particularly suitable for morphologic evaluation, immunohistochemistry and in situ hybridization. However, it has become a paradigm that these samples cannot be used for genome-wide expression analysis with microarrays. To oppose this view, we present a pilot microarray study using FFPE core needle biopsies from breast cancers as RNA source. We found that microarray probes interrogating sequences near the poly-A-tail of the transcribed genes were well suitable to measure RNA levels in FFPE core needle biopsies. For the ER and the HER2 gene, we observed strong correlations between RNA levels measured in these probe sets and protein expression determined by immunohistochemistry (p = 0.000003 and p = 0.0022). Further, we have identified a signature of 364 genes that correlated with ER protein status and a signature of 528 genes that correlated with HER2 protein status. Many of these genes (ER: 60%) could be confirmed by analysis of an independent publicly available data set. Finally, a hierarchical clustering of the biopsies with respect to three recently reported gene expression grade signatures resulted in widely stable low and high expression grade clusters that correlated with the pathological tumor grade. These findings support the notion that clinically relevant information can be gained from microarray based gene expression profiling of FFPE cancer biopsies. This opens new opportunities for the integration of gene expression analysis into the workflow of invasive cancer diagnostics as well as translational research in the setting of clinical studies.

Publication Title

Genome-wide gene expression profiling of formalin-fixed paraffin-embedded breast cancer core biopsies using microarrays.

Sample Metadata Fields

Disease stage

View Samples
accession-icon GSE17187
Gene expression analysis of 3 node positive vs 3 node negative intestinal type gastric cancers by gene array technology.
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Gastric cancer is one of the most common causes of cancer-related deaths worldwide. The lymph node status represents the strongest prognostic factor. Due to its extremely poor prognosis, the identification of novel therapeutic targets is urgently needed. Therefore, we aimed to assess differentially expressed genes in nodal negative versus nodal positive intestinal type gastric carcinoma by GeneChip array technique. The transcriptional profile of 6 gastric cancers with and without lymphatic dissemination was analyzed. A total of 115 transcripts were found to be up- and 219 to be down-regulated in node positive compared with node negative gastric cancers. Next we searched for differentially expressed GPCRs. We identified 52 GPCRs and GPCR-related genes, which were up- or down-regulated with a fold change factor greater 1.5.

Publication Title

Vascular CXCR4 expression - a novel antiangiogenic target in gastric cancer?

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE14764
A Prognostic Gene Expression Index in Ovarian Cancer
  • organism-icon Homo sapiens
  • sample-icon 80 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Ovarian carcinoma has the highest mortality rate among gynecological malignancies. In this project, we investigated the hypothesis that molecular markers are able to predict outcome of ovarian cancer independently of classical clinical predictors, and that these molecular markers can be validated using independent data sets. We applied a semi-supervised method for prediction of patient survival. Microarrays from a cohort of 80 ovarian carcinomas (TOC cohort) were used for the development of a predictive model, which was then evaluated in an entirely independent cohort of 118 carcinomas (Duke cohort). A 300 gene ovarian prognostic index (OPI) was generated and validated in a leave-one-out approach in the TOC cohort (Kaplan-Meier analysis, p=0.0087). In a second validation step the prognostic power of the OPI was confirmed in an independent data set (Duke cohort, p=0.0063). In multivariate analysis, the OPI was independent of the postoperative residual tumour, the main clinico-pathological prognostic parameter with an adjusted hazard ratio of 6.4 (TOC cohort, CI 1.8 23.5, p=0.0049) and 1.9 (Duke cohort, CI 1.2 3.0, p=0.0068). We constructed a combined score of molecular data (OPI) and clinical parameters (residual tumour), which was able to define patient groups with highly significant differences in survival. The integrated analysis of gene expression data as well as residual tumour can be used for optimised assessment of prognosis. As traditional treatment options are limited, this analysis may be able to optimise clinical management and to identify those patients that would be candidates for new therapeutic strategies.

Publication Title

A prognostic gene expression index in ovarian cancer - validation across different independent data sets.

Sample Metadata Fields

Specimen part, Disease stage

View Samples
accession-icon GSE8868
Comparison of splenic and small intestine lamina propria macrophages
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The intestinal immune system must elicit robust immunity against harmful pathogens but restrain immune responses directed against commensal microbes and dietary antigens. The mechanisms that maintain this dichotomy are poorly understood. Here we describe a population of CD11b+F4/80+CD11c macrophages in the lamina propria (LP) that express several anti-inflammatory molecules including interleukin 10 (IL-10), but little or no pro-inflammatory cytokines, even upon stimulation with Toll-like receptor (TLR) ligands. These macrophages induced, in a manner dependent on IL-10, retinoic acid and exogenous transforming growth factor-, differentiation of FoxP3+ regulatory T cells. In contrast, LP CD11b+ dendritic cells elicited IL-17 production. This IL-17 production was suppressed by LP macrophages, indicating that a dynamic interplay between these subsets may influence the balance between immune activation and tolerance.

Publication Title

Lamina propria macrophages and dendritic cells differentially induce regulatory and interleukin 17-producing T cell responses.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE65095
FinHER trial : Patients with human epidermal growth factor receptor 2 (HER2)positive breast cancer
  • organism-icon Homo sapiens
  • sample-icon 203 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

The FinHER trial is a multicentre phase 3 randomised adjuvant breast cancer trial that enrolled 1010 patients. The women were randomly assigned to receive three cycles of docetaxel or vinorelbine, followed by three cycles of fluorouracil, epirubicin, and cyclophosphamide.

Publication Title

Integrative proteomic and gene expression analysis identify potential biomarkers for adjuvant trastuzumab resistance: analysis from the Fin-her phase III randomized trial.

Sample Metadata Fields

Age, Disease stage

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accession-icon GSE9686
Human colon expression in healthy, CD, treated CD, and UC
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Activation of inflammatory pathways in human IBD

Publication Title

Activation of an IL-6:STAT3-dependent transcriptome in pediatric-onset inflammatory bowel disease.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP109190
Sex differences in peripheral not central immune responses to pain-inducing injury
  • organism-icon Mus musculus
  • sample-icon 25 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

Women suffer chronic pain more frequently than men. It is not clear whether this is due to differences in higher level cognitive processes or basic nociceptive responses. This study used a mouse model to dissociate these factors and found no differences in peripheral afferent neurons or in the spinal cord immune response to neuropathic injury. However, it did identify potential sexual dimorphisms in peripheral adaptive immune responses. Overall design: RNA-seq of naïve FACS-purified DRG neurons and MACS-purified DRG neurons after partial sciatic nerve ligation (day 8): comparison of male versus female samples

Publication Title

Sex differences in peripheral not central immune responses to pain-inducing injury.

Sample Metadata Fields

Sex, Specimen part, Cell line, Subject

View Samples
accession-icon GSE61140
Expression data from mouse arthritis tarsal joints
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Pathological bone changes differ considerably between inflammatory arthritic diseases, and most studies have focused on bone erosion. Collagen Induced Arthritis (CIA) is a model for Rheumatoid Arthritis, which, in addition to bone erosion, demonstrates bone formation at the time for clinical manifestations. The objective of this study was to use the CIA model to study bone remodelling by performing a gene expression profiling time-course study on the CIA model.

Publication Title

Kinetics of gene expression and bone remodelling in the clinical phase of collagen-induced arthritis.

Sample Metadata Fields

Specimen part

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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