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accession-icon GSE10799
Gene expression profile of lung tumors
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We have investigated whether the early dissemination of tumor cells into bone marrow is associated with a specific molecular pattern in primary lung cancer

Publication Title

Genomic profiles associated with early micrometastasis in lung cancer: relevance of 4q deletion.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE31212
Mammary carcinomas in WAP-SV40 transgenic mice
  • organism-icon Mus musculus
  • sample-icon 34 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Low-grade and high-grade mammary carcinomas in WAP-T transgenic mice are independent entities distinguished by Met expression.

Sample Metadata Fields

Specimen part, Disease stage, Time

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accession-icon GSE29117
Mammary carcinomas in WAP-SV40 transgenic mice [gene expression]
  • organism-icon Mus musculus
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Transgenic expression in mice of two synergistically acting SV40 early region encoded proteins, large (LT) and small (sT) tumor antigens, in the mammary epithelium recapitulates loss of p53 and Rb function and deregulation of PP2A-controlled mitogenic pathways in human breast cancer. In primiparous mice, WAP-promoter driven expression of SV40 proteins induces well and poorly differentiated mammary adenocarcinomas. We performed a correlative aCGH and gene expression analysis of 25 monofocal tumors, representing four histopathological grades, to explore the molecular traits of SV40-induced mammary tumors and to emphasize the relevance of this tumor model for human breast tumorigenesis.

Publication Title

Low-grade and high-grade mammary carcinomas in WAP-T transgenic mice are independent entities distinguished by Met expression.

Sample Metadata Fields

Specimen part, Disease stage

View Samples
accession-icon GSE33038
Involuted normal mammary gland in WAP-SV40 transgenic mice [gene expression]
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Transgenic expression in mice of two synergistically acting SV40 early region encoded proteins, large (LT) and small (sT) tumor antigens, in the mammary epithelium recapitulates loss of p53 and Rb function and deregulation of PP2A-controlled mitogenic pathways in human breast cancer. In primiparous mice, WAP-promoter driven expression of SV40 proteins induces well and poorly differentiated mammary adenocarcinomas. We performed a correlative aCGH and gene expression analysis of 25 monofocal tumors, representing four histopathological grades, to explore the molecular traits of SV40-induced mammary tumors and to emphasize the relevance of this tumor model for human breast tumorigenesis.

Publication Title

Low-grade and high-grade mammary carcinomas in WAP-T transgenic mice are independent entities distinguished by Met expression.

Sample Metadata Fields

Specimen part, Time

View Samples
accession-icon GSE10327
mRNA expression data of 62 human medulloblastoma tumors
  • organism-icon Homo sapiens
  • sample-icon 58 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

To identify molecular subtypes of medulloblastoma we have profiled a series of 62 medulloblastoma tumors. Unsupervised hierarchical cluster analysis of these data identified 5 distinct molecular subtypes.

Publication Title

Integrated genomics identifies five medulloblastoma subtypes with distinct genetic profiles, pathway signatures and clinicopathological features.

Sample Metadata Fields

Sex

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accession-icon SRP057500
RNA-seq of tumor-educated platelets enables blood-based pan-cancer, multiclass and molecular pathway cancer diagnostics
  • organism-icon Homo sapiens
  • sample-icon 290 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

We report RNA-sequencing data of 283 blood platelet samples, including 228 tumor-educated platelet (TEP) samples collected from patients with six different malignant tumors (non-small cell lung cancer, colorectal cancer, pancreatic cancer, glioblastoma, breast cancer and hepatobiliary carcinomas). In addition, we report RNA-sequencing data of blood platelets isolated from 55 healthy individuals. This dataset highlights the ability of TEP RNA-based ''liquid biopsies'' in patients with several types with cancer, including the ability for pan-cancer, multiclass cancer and companion diagnostics. Overall design: Blood platelets were isolated from whole blood in purple-cap BD Vacutainers containing EDTA anti-coagulant by standard centrifugation. Total RNA was extracted from the platelet pellet, subjected to cDNA synthesis and SMARTer amplification, fragmented by Covaris shearing, and prepared for sequencing using the Truseq Nano DNA Sample Preparation Kit. Subsequently, pooled sample libraries were sequenced on the Illumina Hiseq 2500 platform. All steps were quality-controlled using Bioanalyzer 2100 with RNA 6000 Picochip, DNA 7500 and DNA High Sensitivity chips measurements. For further downstream analyses, reads were quality-controlled using Trimmomatic, mapped to the human reference genome using STAR, and intron-spanning reads were summarized using HTseq. The processed data includes 285 samples (columns) and 57736 ensemble gene ids (rows). The supplementary data file (TEP_data_matrix.txt) contains the intron-spanning read counts, after data summarization by HTseq.

Publication Title

RNA-Seq of Tumor-Educated Platelets Enables Blood-Based Pan-Cancer, Multiclass, and Molecular Pathway Cancer Diagnostics.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE37023
Comprehensive Genomic Meta-analysis Identifies Intra-Tumoral Stroma as a Predictor of Gastric Cancer Patient Survival
  • organism-icon Homo sapiens
  • sample-icon 213 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Background and Aims: Gastric adenocarcinoma (gastric cancer, GC) is a major cause of global cancer mortality. Identifying molecular programs contributing to GC patient survival may improve our understanding of GC pathogenesis, highlight new prognostic factors, and reveal novel therapeutic targets. We aimed to produce a comprehensive inventory of gene expression programs expressed in primary GCs, and to identify those expression programs significantly associated with patient survival.

Publication Title

Comprehensive genomic meta-analysis identifies intra-tumoural stroma as a predictor of survival in patients with gastric cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE35809
Gastric Cancer Subtyping (Australian Patient Cohort)
  • organism-icon Homo sapiens
  • sample-icon 70 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Genome-wide mRNA expression profiles of 70 primary gastric tumors from the Australian patient cohort. Like many cancers, gastric adenocarcinomas (gastric cancers) show considerable heterogeneity between patients. Thus, there is intense interest in using gene expression profiles to discover subtypes of gastric cancers with particular biological properties or therapeutic vulnerabilities.

Publication Title

Comprehensive genomic meta-analysis identifies intra-tumoural stroma as a predictor of survival in patients with gastric cancer.

Sample Metadata Fields

Specimen part

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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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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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