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accession-icon GSE68465
caArray_jacob-00182: Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study
  • organism-icon Homo sapiens
  • sample-icon 222 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Here we report a large, training*testing, multi-site, blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) could be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early-stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas.

Publication Title

Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage, Race

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accession-icon SRP188673
A time course study by mRNA Sequencing to identify transcriptional changes in mice lung development
  • organism-icon Mus musculus
  • sample-icon 27 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Mammalian fetal lung development is a complex biological process.Despite considerable progress, a comprehensive understanding of the dynamic regulatory networks that govern postnatal alveolar lung development is still lacking. The purpose of this study as part of the LungMAP consortium (www.lungmap.net) is to understand the transcriptional changes in the process of mammalian lung development. Overall design: Method: We isolated alveolar septa from c57BL/6 mice by laser capture microdissection from 14 time points (E16.5, P0.5, P1, P1.5, P2.5, P4, P5, P7, P10, P13.5, P15, P19, P23, and P28) and performed RNA-Sequencing by Illumina Hi-Seq 2500 .

Publication Title

LungMAP: The Molecular Atlas of Lung Development Program.

Sample Metadata Fields

Sex, Specimen part, Cell line, Subject

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accession-icon SRP055528
Spatially heterogeneous choroid plexus transcriptomes encode positional identity and contribute to regional cerebrospinal fluid production
  • organism-icon Mus musculus
  • sample-icon 13 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

A sheet of choroid plexus epithelial cells extends into each cerebral ventricle and secretes signaling factors into the cerebrospinal fluid (CSF). To evaluate whether differences in the CSF proteome across ventricles arise, in part, from regional differences in choroid plexus gene expression, we defined the transcriptome of lateral ventricle (telencephalic) vs. fourth ventricle (hindbrain) choroid plexus. We find that positional identities of mouse, macaque, and human choroid plexi derive from gene expression domains that parallel their axial tissues of origin. We then show that molecular heterogeneity between telencephalic and hindbrain choroid plexi contributes to region-specific, age-dependent protein secretion in vitro. Transcriptome analysis of FACS-purified choroid plexus epithelial cells also predicts their cell type-specific secretome. Spatial domains with distinct protein expression profiles were observed within each choroid plexus. We propose that regional differences between choroid plexi contribute to dynamic signaling gradients across the mammalian cerebroventricular system. Overall design: Two-factor design with two levels per factor and n=2 biological replicates. Lateral (telencephalic) and fourth (hindbrain) choroid plexus samples are paired in that they are isolated from the same brains.

Publication Title

Spatially heterogeneous choroid plexus transcriptomes encode positional identity and contribute to regional CSF production.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE93291
A new molecular assay for the proliferation signature in mantle cell lymphoma applicable to formalin-fixed paraffin-embedded biopsies
  • organism-icon Homo sapiens
  • sample-icon 123 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Mantle cell lymphoma (MCL) is an aggressive B-cell neoplasm displaying heterogeneous outcomes after treatment. In 2003, the Lymphoma/Leukemia Molecular Profiling Project described a powerful biomarker, the "proliferation signature", using gene expression in fresh frozen material. Here we describe the training and validation of a new assay that measures the proliferation signature in RNA derived from routinely available formalin-fixed paraffin-embedded (FFPE) biopsies.

Publication Title

New Molecular Assay for the Proliferation Signature in Mantle Cell Lymphoma Applicable to Formalin-Fixed Paraffin-Embedded Biopsies.

Sample Metadata Fields

Disease, Disease stage, Subject

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accession-icon GSE62322
Gene expression signature in advanced colorectal cancer patients select drugs and response for the use of leucovorin, fluorouracil, and irinotecan
  • organism-icon Homo sapiens
  • sample-icon 112 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a), Affymetrix Human Genome U133B Array (hgu133b)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Gene expression signature in advanced colorectal cancer patients select drugs and response for the use of leucovorin, fluorouracil, and irinotecan.

Sample Metadata Fields

Sex, Age, Specimen part, Subject

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accession-icon GSE62321
Specific extracellular matrix remodeling signature of colon hepatic metastases [HG-U133B]
  • organism-icon Homo sapiens
  • sample-icon 56 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a), Affymetrix Human Genome U133B Array (hgu133b)

Description

To identify genes implicated in metastatic colonization of the liver in colorectal cancer, we collected pairs of primary tumors and hepatic metastases before chemotherapy in 13 patients. We compared mRNA expression in the pairs of patients to identify genes deregulated during metastatic evolution. We then validated the identified genes using data obtained by different groups. The 33-gene signature was able to classify 87% of hepatic metastases, 98% of primary tumors, 97% of normal colon mucosa, and 95% of normal liver tissues in six datasets obtained using five different microarray platforms. The identified genes are specific to colon cancer and hepatic metastases since other metastatic locations and hepatic metastases originating from breast cancer were not classified by the signature. Gene Ontology term analysis showed that 50% of the genes are implicated in extracellular matrix remodeling, and more precisely in cell adhesion, extracellular matrix organization and angiogenesis. Because of the high efficiency of the signature to classify colon hepatic metastases, the identified genes represent promising targets to develop new therapies that will specifically affect hepatic metastasis microenvironment.

Publication Title

Gene expression signature in advanced colorectal cancer patients select drugs and response for the use of leucovorin, fluorouracil, and irinotecan.

Sample Metadata Fields

Sex, Age, Specimen part, Subject

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accession-icon GSE62080
Gene expression signature in advanced colorectal cancer patients select drugs and response for the use of leucovorin, fluorouracil, and irinotecan
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

In patients with advanced colorectal cancer, leucovorin, fluorouracil, and irinotecan (FOLFIRI) is considered as one of the reference first-line treatments. However, only about half of treated patients respond to this regimen, and there is no clinically useful marker that predicts response. A major clinical challenge is to identify the subset of patients who could benefit from this chemotherapy. We aimed to identify a gene expression profile in primary colon cancer tissue that could predict chemotherapy response. Patients and Methods:- Tumor colon samples from 21 patients with advanced colorectal cancer were analyzed for gene expression profiling using Human Genome GeneChip arrays U133. At the end of the first-line treatment, the best observed response, according to WHO criteria, was used to define the responders and nonresponders. Discriminatory genes were first selected by the significance analysis of microarrays algorithm and the area under the receiver operating characteristic curve. A predictor classifier was then constructed using support vector machines. Finally, leave-one-out cross validation was used to estimate the performance and the accuracy of the output class prediction rule. Results:- We determined a set of 14 predictor genes of response to FOLFIRI. Nine of nine responders (100% specificity) and 11 of 12 nonresponders (92% sensitivity) were classified correctly, for an overall accuracy of 95%. Conclusion:- After validation in an independent cohort of patients, our gene signature could be used as a decision tool to assist oncologists in selecting colorectal cancer patients who could benefit from FOLFIRI chemotherapy, both in the adjuvant and the first-line metastatic setting.

Publication Title

Gene expression signature in advanced colorectal cancer patients select drugs and response for the use of leucovorin, fluorouracil, and irinotecan.

Sample Metadata Fields

Specimen part

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accession-icon GSE109941
Lungs from mice infected with S. pneumoniae and treated with Nemiralisib
  • organism-icon Mus musculus
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Bacterial infections cause exaserbations in COPD. Study conducted to asses the effect of Nemiralisib, a PI3Kdelta inhibitor, on S. pneumoniae infected mice

Publication Title

PI3Kδ hyper-activation promotes development of B cells that exacerbate Streptococcus pneumoniae infection in an antibody-independent manner.

Sample Metadata Fields

Specimen part, Time

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accession-icon SRP002056
High throughput sequencing of endogenous small RNAs from AGO pathway mutants
  • organism-icon Caenorhabditis elegans
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

High-throughput pyrosequencing of endogenous small RNAs from >95% male enriched populations of alg-3(tm1155);alg-4(ok1041);fog-2(q71) and fog-2(q71) worms as well as purified spermatids from fem-3(q20) adult worms. Gametogenesis is thermosensitive in numerous metazoa ranging from worms to man. In C. elegans a variety of germ-line nuage- (P-granule) -associated RNA-binding proteins including the Piwi-clade Argonaute, PRG-1, have been implicated in temperature-dependent fertility. Here, we describe the role of two AGO-class paralogs, alg-3 (T22B3.2) and alg-4 (ZK757.3) in promoting male fertility at elevated temperatures. A rescuing GFP::alg-3 transgene is localized in P-granules beginning at the late pachytene stage of male gametogenesis. alg-3/4 double mutants lack a subgroup of small RNAs, named 26G-RNAs, which target and appear to down-regulate numerous spermatogenesis-expressed mRNAs. These findings add to a growing number of AGO pathways required for temperature-dependent fertility in C. elegans and support a model in which AGOs and their small RNA co-factors function to promote robustness in gene-expression networks. Overall design: 3 samples examined. Small RNAs from alg-3(tm1155);alg-4(ok1041);fog-2(q71) males and fog-2(q71) males. Small RNAs from spermatids isolated from ferm-3(q20) worms.

Publication Title

Argonautes ALG-3 and ALG-4 are required for spermatogenesis-specific 26G-RNAs and thermotolerant sperm in Caenorhabditis elegans.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE58445
Gene expression signatures delineate biological and prognostic subgroups in peripheral T-cell lymphoma
  • organism-icon Homo sapiens
  • sample-icon 188 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Peripheral T-cell lymphoma (PTCL) encompasses a heterogeneous group of neoplasms with generally poor clinical outcome. Currently 50% of PTCL cases are not classifiable: PTCL-not otherwise specified (NOS). Gene-expression profiles on 372 PTCL cases were analyzed and robust molecular classifiers and oncogenic pathways that reflect the pathobiology of tumor cells and their microenvironment were identified for major PTCL-entities, including 114 angioimmunoblastic T-cell lymphoma (AITL), 31 anaplastic lymphoma kinase (ALK)-positive and 48 ALK-negative anaplastic large cell lymphoma, 14 adult T-cell leukemia/lymphoma and 44 extranodal NK/T-cell lymphoma that were further separated into NK-cell and gdT-cell lymphomas. Thirty-seven percent of morphologically diagnosed PTCL-NOS cases were reclassified into other specific subtypes by molecular signatures. Reexamination, immunohistochemistry, and IDH2 mutation analysis in reclassified cases supported the validity of the reclassification. Two major molecular subgroups can be identified in the remaining PTCL-NOS cases characterized by high expression of either GATA3 (33%; 40/121) or TBX21 (49%; 59/121). The GATA3 subgroup was significantly associated with poor overall survival (P=.01). High expression of cytotoxic genesignaturewithin the TBX21 subgroup also showed poor clinical outcome (P=.05). InAITL, high expression of several signatures associated with the tumor microenvironment was significantly associated with outcome. A combined prognostic score was predictive of survival in an independent cohort (P=.004).

Publication Title

Gene expression signatures delineate biological and prognostic subgroups in peripheral T-cell lymphoma.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage, Subject

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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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