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accession-icon GSE11516
Circadian Rhythm of Gene Expression Patterns in Liver of Mouse
  • organism-icon Mus musculus
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconMouseWG-6 V2

Description

Genes encoding the circadian pacemaker in the hypothalamic suprachiasmatic nuclei (SCN) of mammals have recently been identified, but the molecubasis of circadian timing in peripheral tissue is not well understood. We used a bead-based microarray to identify mouse liver transcripts that show circadian cycles of abundance under constant conditions.

Publication Title

Comprehensive analysis of microRNA-mRNA co-expression in circadian rhythm.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE46862
Predicting multi-class responses to preoperative chemoradiotherapy in rectal patients
  • organism-icon Homo sapiens
  • sample-icon 69 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The treatment strategy of rectal cancer has substantially changed in recent decades. Historically postoperative chemoradiotherapy (CRT) was considered to be the first-line therapy for stage II and III rectal cancers. However, the preoperative CRT is now considered to be the optimal therapy regimen for locally advanced rectal ancer due to its improved local control, reduced toxicity, and increased rate of sphincter preservation. Our study established a clinically practical multi-class prediction model by adopting a novel strategy that applies two separate prediction models (MI and TO predictor) sequentially to a patient to predict the response. For promising clinical practice, we validated our model in a published dataset, which is completely independent dataset from ours. This study suggests a clinically plausible prediction model that correctly infers the preoperative CRT response of patients with high accuracy based on 163 gene signatures we identified.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Age

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accession-icon GSE43748
Transcriptional profiles of psychostimulant reinforcement in rats
  • organism-icon Rattus norvegicus
  • sample-icon 63 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Drug-induced alterations in transcriptional regulation play a central role in establishing the persistent neuroplasticities that occur during drug addiction. Additionally, changes in gene expression associated with drug administration provide valuable insight into the molecular basis of drug abuse. The molecular mechanisms that underlie susceptibility to psychostimulant addiction remain unknown. Identifying the common gene transcriptional responses to psychostimulants can provide a mechanistic insight to elucidate the molecular nature of drug dependence.

Publication Title

Neuronal development genes are key elements mediating the reinforcing effects of methamphetamine, amphetamine, and methylphenidate.

Sample Metadata Fields

Specimen part

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accession-icon GSE20549
Expression data from H1299 and H460 lung cancer cell lines
  • organism-icon Homo sapiens
  • sample-icon 41 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

To identify a set of genes related to radioresistance, we analyzed the time-series gene expression profiles of radioresistant H1299 and radiosensitive H460 lung cancer cells in response to 2 Gy of ionizing radiation (IR) by performing quadratic regression (QR) analysis. Out of the 21,331 genes, we selected 6,538 genes by QR analysis from the gene expression profile of H460 cells and 6,086 genes from that of H1299 cells. Most of the genes identified in the H460 cells were classified into continuously up- or down-regulated groups, while the major QR groups were transiently changed groups in the H1299 cell line. From gene ontology analysis of the major QR groups, the DNA damage response was commonly enriched in both cell lines. DNA repair-related genes such as ATM, ATR, TP53BP1, BRCA1, MRE11, NBN and RAD50 were particularly up-regulated in H1299 cells. Suppression of these DNA repair-related genes using siRNA made H1299 cells radiosensitive to ionizing radiation. The data suggest that differential responses to DNA damage confer radioresistance to cancer cells, and provide potential novel targets for sensitizing radiotherapy.

Publication Title

No associated publication

Sample Metadata Fields

Cell line

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accession-icon GSE30074
Expression data from 30 medulloblastomas
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Pediatric medulloblastoma is considered a highly heterogeneous disease, and a new strategy of risk stratification to optimize therapeutic outcomes is required. We aimed to investigate a new risk-stratification approach based on expression profiles of medulloblastoma cohorts. We analyzed gene expression profiles of 30 primary medulloblastomas and detected strong evidence that poor survival outcome was significantly associated with mRNA expression profiles of 17p loss. However, it was not supported in independent cohorts from previously published data (n=100). We speculated that this controversy might come from complex conditions of two important prognostic determinants, loss of tumor suppressors (chromosome 17p) and high expression of oncogenes, c-myc (MYC) or N-myc (MYCN). Simultaneous consideration of these two factors led to a new subgrouping of patients, exhibiting obviously different survival expectancies between the subgroups. Patients with up-regulated WNT signalings were always pre-defined as an independent subgroup, which ultimately removed confounding effect arising from contradictory outcome, favorable prognosis of WNT medulloblastomas despite their high MYC/MYCN expression level. We also found that age is a significant prognostic marker after adjusting for 17p and MYC/MYCN status. Diminished survival in age <3 years was more substantial in groups with high expression of MYC/MYCN or 17p loss, indicating survival outcome might be coordinately affected by these three factors. We suggest a more tailored and easily applicable subgrouping system based on expression profiles of chromosome 17p and MYC/MYCN, while separating WNT medulloblastoma as an independent subgroup, which could provide the basis for a novel risk-stratification strategy in pediatric medulloblastoma.

Publication Title

Prognostic classification of pediatric medulloblastoma based on chromosome 17p loss, expression of MYCC and MYCN, and Wnt pathway activation.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE79264
Global gene transcriptional profiles of RAW 264.7 cells following the infection with Brucella abortus wild and mutant strains
  • organism-icon Mus musculus
  • sample-icon 25 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

We focused on whether transposon mutagenesis in Brucella abortus could induce difference in the trascriptional responses of RAW 264.7 cell infection model compared to the wild strain infected RAW 264.7 cells.

Publication Title

No associated publication

Sample Metadata Fields

Cell line, Time

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accession-icon GSE24972
Gene expression profiling of spleen marginal zone B cells and spleen follicular B cells in IRF8 conditional KO mice
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Conditional IRF8 KO mice (mice with a conditional allele of Irf8 crossed with CD19-Cre mice) showed increased numbers of both Gene expression data spleen marginal zone (MZ) and Gene expression data spleen follicular (FO) B cells compared to control mice.

Publication Title

IFN regulatory factor 8 restricts the size of the marginal zone and follicular B cell pools.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE13640
Effect of miRNA biogenesis factors on mRNA levels
  • organism-icon Homo sapiens
  • sample-icon 23 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

Posttranscriptional crossregulation between Drosha and DGCR8.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE60670
High-resolution transcriptome analysis reveals neuropathic pain gene-expression signatures in spinal microglia after nerve injury
  • organism-icon Mus musculus
  • sample-icon 23 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Microglia activation contributes to the development of neuropathic pain.

Publication Title

High-resolution transcriptome analysis reveals neuropathic pain gene-expression signatures in spinal microglia after nerve injury.

Sample Metadata Fields

Specimen part

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accession-icon GSE17685
Gene expression profile in selenophosphate synthetase 1 (SPS1) knockdown Drosophila SL2 cell
  • organism-icon Drosophila melanogaster
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Drosophila Genome 2.0 Array (drosophila2)

Description

Selenophosphate, which is the active donor of selenium in selenocysteine (Sec) biosynthesis is synthesized from selenite and ATP by an enzyme designated as selenophosphate synthetase (SPS).There are two isoforms of SPS in higher eukaryotes,SPS1 and SPS2. Initially, both SPS1 and SPS2 were thought to be involved in selenophosphate synthesis. However, it was subsequently shown that only SPS2 catalyzes selenophosphate synthesis. Although SPS1 is an essential gene in Drosophila, its function has not been determined.

Publication Title

Elevation of glutamine level by selenophosphate synthetase 1 knockdown induces megamitochondrial formation in Drosophila cells.

Sample Metadata Fields

Cell line

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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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