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accession-icon GSE12368
Analysis of adrenocortical tumors identify IGF2 and Ki-67 as useful in differentiating carcinomas from adenomas
  • organism-icon Homo sapiens
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Purpose: The management of adrenocortical tumors (ACTs) is complex, compounded by the difficulty in discriminating benign from malignant tumors using conventional histology. The Weiss score is the current most widely used system for ACT diagnosis but it has limitations, particularly with ACTs with a score of 3. The am of this study was to identify molecular markers whose expression can discriminate adrenocortical carcinomas (ACCs) from adrenocortical adenomas (ACAs) by microarray gene expression profiling and to determine their clinical applicability by using immunohistochemistry (IHC). Experimental design: Microarray gene expression profiling was used to identify 7 molecular markers which were significantly differentially expressed between ACCs and ACAs. These results were confirmed with quantitative PCR for all 7 genes and IHC for 3 protein. Results: Microarray gene expression profiling was able to accurately categorize ACTs into ACCs and ACAs. All 7 genes were strong discriminators of ACCs from ACAs on qPCR. IHC with IGF2, MAD2L1, CCNB1 and Ki-67, but not ACADVL or ALOX15B, had high diagnostic accuracy in differentiating ACCs from ACAs. The best results however were obtained with a combination of IGF2 and Ki-67 with 96% sensitivity and 100% specificity in diagnosing ACCs. Conclusion: Microarray gene expression profiling accurately differentiates ACCs from ACAs. The combination of IGF2 and Ki-67 IHC is also highly accurate in distinguishing between the 2 groups and is particularly helpful in ACTs with Weiss score of 3.

Publication Title

Microarray gene expression and immunohistochemistry analyses of adrenocortical tumors identify IGF2 and Ki-67 as useful in differentiating carcinomas from adenomas.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE10317
A case of primary hyperparathyroidism and undetectable serum PTH due to a truncating PTH gene mutation
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

A investigation of the gene expression of one parathyroid tumour compared to its adjacent normal tissue

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE64826
Expression data from H295R_GR cells following treatment with dexamethasone or RU486
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The human glucocorticoid receptor (GR) is overexpressed at the molecular and protein level in malignant human adrenocortical cancers. A stable cell line model of GR overexpression was established using the H295R human adrenocortical cancer cell line.

Publication Title

No associated publication

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE37210
The application of nonsense-mediated mRNA decay inhibition to the identification of breast cancer susceptibility genes
  • organism-icon Homo sapiens
  • sample-icon 141 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip

Description

Identification of novel, highly penetrant, breast cancer susceptibility genes will require the application of additional strategies beyond that of traditional linkage and candidate gene approaches. Approximately one-third of inherited genetic diseases, including breast cancer susceptibility, are caused by frameshift or nonsense mutations that truncate the protein product [1]. Transcripts harbouring premature termination codons are selectively and rapidly degraded by the nonsense-mediated mRNA decay (NMD) pathway. Blocking the NMD pathway in any given cell will stabilise these mutant transcripts, which can then be detected using gene expression microarrays. This technique, known as gene identification by nonsense-mediated mRNA decay inhibition (GINI), has proved successful in identifying sporadic nonsense mutations involved in many different cancer types. However, the approach has not yet been applied to identify germline mutations involved in breast cancer. We therefore attempted to use GINI on lymphoblastoid cell lines (LCLs) from multiple-case, non-BRCA1/2 breast cancer families in order to identify additional high-risk breast cancer susceptibility genes.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Cell line

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accession-icon GSE7127
63 Melanoma cell lines
  • organism-icon Homo sapiens
  • sample-icon 57 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

63 melanoma cell lines hybridized to Affymetrix Hu133_Plus 2 oligo arrays. The aim of this study was to identify potential downstream targets of key oncogenes and TSGs in melanoma (including p14ARF, p16INK4A, BRAF etc).

Publication Title

Confirmation of a BRAF mutation-associated gene expression signature in melanoma.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE86260
Cancer Associated Fibroblasts are defined by a core set of epigenome changes that contribute to the tumor phenotype
  • 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

Enduring epigenetic landmarks define the cancer microenvironment.

Sample Metadata Fields

Sex, Specimen part, Subject

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accession-icon GSE76337
Novel contribution of acetylated histone variant H2A.Z in activation of neo-enhancers in prostate cancer
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II, Affymetrix Human Gene 2.1 ST Array (hugene21st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE7152
Melanoma cell lines involved in the p14ARF genotype analysis
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

35 Melanoma cell lines hybridized to Affymetrix Hu133_Plus 2 microarrays were analysed for genes differentially expressed between cell lines carrying wild-type p14ARF and those with mutant 14ARF. All of these cell lines contained wild-type p53 (so that the effects of p14ARF mutations could be analysed without contamination from p53).

Publication Title

Gene expression profiling in melanoma identifies novel downstream effectors of p14ARF.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE81408
Gene expression in healthy and gene deficient human nave CD4+ T cells
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

Ascertain the effects of disease-causing gene mutations on the differentiation status of human nave CD4+ T cells in the setting of primary immunodeficiencies. Thus, do CD4+ T cells isolated according to a nave surface phenotype (ie CD4+CD45RA+CCR7+) from healthy donors exhibit a similar gene expression profile as phenotpyically-matched cells isolated from individuals with defined primary immunodeficiencies caused by specific monogenic mutations.

Publication Title

Unique and shared signaling pathways cooperate to regulate the differentiation of human CD4+ T cells into distinct effector subsets.

Sample Metadata Fields

Specimen part

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accession-icon GSE40565
ISL1 regulates PPARg activation and early adipogenesis via BMP4-dependent and -independent mechanisms
  • organism-icon Mus musculus
  • sample-icon 27 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

While adipogenesis is controlled by a cascade of transcription factors, the global gene expression profiles in the early phase of adipogenesis are not well defined. Using microarray analysis of gene expression in 3T3-L1 cells we have identified evidence for the activity of 2568 genes during the early phase of adipocyte differentiation. One of these, ISL1, was of interest since its expression was markedly upregulated at 1 h after initiation of differentiation with a subsequent rapid decline. Overexpression of ISL1 at early times during adipocyte differentiation, but not at later times, was found to profoundly inhibit differentiation. This was accompanied by moderate down-regulation of PPARg levels, substantial down-regulation of PPARg downstream genes and down-regulation of BMP4 levels in preadipocytes. Readdition of BMP4 overcame the inhibitory effect of ISL1 on PPARg but not aP2 expression, a downstream gene of PPARg; and BMP4 also partially rescued ISL1 inhibition of adipogenesis, an effect which is additive with rosiglitazone. These results suggest that ISL1 is intimately involved in early regulation of adipogenesis, modulating PPARg expression and activity via BMP4-dependent and -independent mechanisms. Our time course gene expression survey sets the stage for further studies to explore other early and immediate regulators.

Publication Title

ISL1 regulates peroxisome proliferator-activated receptor γ activation and early adipogenesis via bone morphogenetic protein 4-dependent and -independent mechanisms.

Sample Metadata Fields

Cell line, Treatment, Time

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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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