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accession-icon GSE29370
Gene expression profile of malignant mesothelioma
  • organism-icon Homo sapiens
  • sample-icon 22 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Malignant mesothelioma (MM) is an asbestos-related malignancy and largely unresponsive to conventional chemotherapy or radiotherapy. Novel, more effective therapeutic strategies are needed for this fatal disease. We performed microarray analysis of MM using Affymetrix Human U133 Plus 2.0 array. Aberrant expression of the genes participating in semaphorin signaling were detected in malignant mesothelioma cells. All MM cells downregulated the expression of more than one gene for SEMA3B, 3F, and 3G when compared with Met5a, a normal pleura-derived cell line. In 12 of 14 epithelioid MM cells, the expression level of SEMA3A was lower than that in Met5a. An augmented expression of VEGFA was detected in half of the MM cells. The expression ratio of VEGFA/SEMA3A was significantly higher in the epithelioid MMs than in Met5a and the non-epithelioid MMs. Next, gene expression profiling for the polycomb and trithorax group genes revealed that expression of BAP1, the catalytic subunit of the polycomb repressive deubiquitinase complex, and many trithorax group genes was downregulated in MMs compared with the expression of the same genes in Met5a cells. Perturbation of the polycombtrithorax balance plays a significant role in the pathogenesis of malignant mesothelioma.

Publication Title

Frequent deletion of 3p21.1 region carrying semaphorin 3G and aberrant expression of the genes participating in semaphorin signaling in the epithelioid type of malignant mesothelioma cells.

Sample Metadata Fields

Sex, Age, Specimen part, Cell line

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accession-icon GSE55857
Comprehensive Analysis of Recurrence-Associated Small Non-Coding RNAs in Esophageal Cancer
  • organism-icon Homo sapiens
  • sample-icon 255 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Integrated genomic analysis of recurrence-associated small non-coding RNAs in oesophageal cancer.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Time

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accession-icon GSE76275
Comprehensive genomic analysis identify novel subtypes and targets of triple-negative breast cancer
  • organism-icon Homo sapiens
  • sample-icon 258 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

Comprehensive genomic analysis identifies novel subtypes and targets of triple-negative breast cancer.

Sample Metadata Fields

Sex, Age, Specimen part, Disease stage, Race

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accession-icon GSE75285
mRNA, miRNA and SNP profiles of 50 HB tumors
  • organism-icon Homo sapiens
  • sample-icon 55 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

Genomic analysis of hepatoblastoma identifies distinct molecular and prognostic subgroups.

Sample Metadata Fields

Sex, Age, Specimen part, Race

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accession-icon GSE76124
Comprehensive genomic analysis identify novel subtypes and targets of triple-negative breast cancer (198 TNBC tumors)
  • organism-icon Homo sapiens
  • sample-icon 194 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Recent meta-analyses suggest triple-negative breast cancer (TNBC) is a heterogenous disease. In this study we sought to define these TNBC subtypes and identify subtype-specific markers and targets.

Publication Title

Comprehensive genomic analysis identifies novel subtypes and targets of triple-negative breast cancer.

Sample Metadata Fields

Sex, Age, Specimen part, Disease stage, Race

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accession-icon GSE66258
Comprehensive Analysis of Recurrence-Associated Small Non-Coding RNAs in Esophageal Cancer [clinical study, Illumina]
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Targeted cancer therapy for squamous cell carcinoma (SCC) has made little progress largely due to a lack of knowledge of the driving genomic alterations. Small non-coding RNAs (sncRNAs) as a potential biomarker and therapeutic target to SCC remain a challenge. We analyzed sncRNAs microarray in 108 fresh frozen specimens of esophageal squamous cell carcinoma (ESCC) as discovery set and assessed associations between sncRNAs and recurrence-free survival. SncRNA signature identified was externally validated in two independent cohorts. We investigated the functional consequences of sncRNA identified and its integrative analysis of complex cancer genomics. We identified 3 recurrence-associated sncRNAs (miR-223, miR-1269a and nc886) from discovery set and proved risk prediction model externally in high and low volume centers. We uncovered through in vitro experiment that nc886 was down-regulated by hypermethylation of its promoter region and influences splicing of pre-mRNAs with minor introns by regulating expression of minor spliceosomal small nuclear RNAs (snRNAs) such as RNU4atac. Integrative analysis from lung SCC data in The Cancer Genome Atlas revealed that patients with lower expression of nc886 had more genetic alterations of TP53, DNA damage response and cell cycle genes. nc886 inhibits minor splicing to suppress expression of certain oncogenes such as PARP1 and E2F family containing minor introns. We present risk prediction model with sncRNAs for ESCC. Among them, nc886 may contribute to complete minor splicing via regulation of minor spliceosomal snRNAs supporting the notion that aberrant alteration in minor splicing might be a key driver of ESCC.

Publication Title

Integrated genomic analysis of recurrence-associated small non-coding RNAs in oesophageal cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE24185
Gene transcription signature of obesity in breast cancer
  • organism-icon Homo sapiens
  • sample-icon 102 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Obesity is thought to contribute to worse disease outcome in breast cancer as a result of increased levels of adipocyte-secreted endocrine factors, insulin, and insulin-like growth factors (IGFs) that accelerate tumor cell proliferation and impair treatment response. We examined the effects of patient obesity on primary breast tumor gene expression, by profiling transcription of a set of tumors for which the patients body mass index (BMI) was ascertained. Sample profiles were stratified according to patients obesity phenotype defined as normal (BMI <25), overweight (BMI 25-29.9), or obese (BMI>30). Widespread alterations in gene expression were evident in breast tumors from obese patients as compared to tumors from other patients, allowing us to define an obesity-associated cancer transcriptional signature of 662 genes.

Publication Title

A gene transcription signature of obesity in breast cancer.

Sample Metadata Fields

Age, Disease, Disease stage, Race

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accession-icon GSE27279
Delineation of Two Clinically and Molecularly Distinct Subgroups of Posterior Fossa Ependymoma
  • organism-icon Homo sapiens
  • sample-icon 101 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Gene expression (mRNA) profiling of human ependymomas

Publication Title

Delineation of two clinically and molecularly distinct subgroups of posterior fossa ependymoma.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE104932
Sequential gene regulatory events leading to glucocorticoid-evoked apoptosis of CEM human leukemic cells
  • organism-icon Homo sapiens
  • sample-icon 12 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

No associated publication

Sample Metadata Fields

Specimen part, Treatment, Time

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accession-icon GSE20427
Characterization of hepatic gene expression during liver regeneration in response to partial hepatectomy
  • organism-icon Mus musculus
  • sample-icon 79 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2), Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Elevated interferon gamma signaling contributes to impaired regeneration in the aged liver.

Sample Metadata Fields

Sex, Treatment

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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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