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accession-icon GSE113624
Gene expression profiles of tumor-induced pTregs and anergic tumor-specific CD4+ T cells
  • organism-icon Mus musculus
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.1 ST Array (mogene21st)

Description

Up to now the role of tumor-specific pTregs and anergic cells during tumor development is not fully understood. Here we used a genetically-induced tumor expressing a MHC-II restricted DBY model antigen to characterize the tumor-induced pTregs and anergic cells that arise early during tumor development.

Publication Title

Induction of anergic or regulatory tumor-specific CD4<sup>+</sup> T cells in the tumor-draining lymph node.

Sample Metadata Fields

Time

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accession-icon GSE113623
Gene expression profile of tumor antigen-specific CD4 T cells
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.1 ST Array (mogene21st)

Description

Up to know CD4 T cell antitumor responses have been mostly studied in transplanted tumor models. However, although they are valuable tools, they are not suitable to study the long term interactions between tumors and the immune system

Publication Title

Induction of anergic or regulatory tumor-specific CD4<sup>+</sup> T cells in the tumor-draining lymph node.

Sample Metadata Fields

Time

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accession-icon GSE113625
Gene expression profile of chronically activated CD4+ T cells from cancer patients
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.1 ST Array (hugene21st)

Description

CD4+ T cells as mediators of antitumor responses are beginning to be appreciated. Our team demonstrated that chronically activated CD4+ T cells (chCD4+ T cells) were expanded in the blood of cancer patients and their expansion is correlated with tumor regression.

Publication Title

Induction of anergic or regulatory tumor-specific CD4<sup>+</sup> T cells in the tumor-draining lymph node.

Sample Metadata Fields

Disease

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accession-icon GSE30818
Transcript profiling of crown rootless1 mutant stem base reveals new elements associated with crown root development in rice
  • organism-icon Oryza sativa
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

Expression data from rice crownrootless1 mutant and corresponding WT stem bases

Publication Title

Transcript profiling of crown rootless1 mutant stem base reveals new elements associated with crown root development in rice.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE62693
miR-125b controls mitochondrial metabolism and dynamics by targeting BIK and MTP18
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Abnormal mitochondria metabolism and innate immune responses participate in the pathogenesis of many inflammatory disorders. The molecular events regulating mitochondrial activity to control survival and cell death in monocytes/macrophages are poorly understood. Here we show that miR-125b attenuates the activity of the mitochondrial respiratory chain through BIK silencing, and promotes the elongation of mitochondrial network through MTP18 targeting, without impacting autophagy, in the human monocytes. Proinflammatory activation is associated with a concomitant increase in miR-125b expression, decrease in BIK and MTP-18 expression, reduced oxidative phosphorylation, and enhanced mitochondrial fusion. Furthermore, expression of M1-associated transcripts as well as mitochondrial dynamics and energy metabolism are induced upon ectopic expression of miR-125b. In turn, by repressing miR-125b, mitochondrial dynamics was preserved, LPS-induced repression of BIK expression and of mitochondrial respiration were prevented, and M1 polarization of macrophages was inhibited. Altogether, our data reveal a novel role for miR-125b in controlling mitochondrial metabolism and dynamics by targeting BIK and MTP18, respectively, two novel cellular target proteins involved in maintaining the mitochondrial integrity in human monocytes. These findings not only suggest a novel function for miR-125b in regulating metabolic adaptation of monocytes to inflammation but also unravel new molecular mechanisms for its pro-apoptotic role and identify potential targets for interfering with inflammatory activation of monocytes.

Publication Title

miR-125b controls monocyte adaptation to inflammation through mitochondrial metabolism and dynamics.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE36876
affy_cotton_2011_12 - Comparative transcriptional profiling of cotton fibers in Gossypium hirsutum and Gossypium barbadense using EST pyrosequencing and microarray hybridization
  • organism-icon Gossypium barbadense, Gossypium hirsutum
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Cotton Genome Array (cotton)

Description

affy_cotton_2011_12 - affy_cotton_2011_12 - In this study we characterized the fiber transcriptomes of the two species, Gossypium hirsutum and Gossypium barbadense that were parental genotypes of a RIL mapping population used previously for phenotypic QTL and expression QTL mapping., We used 454 deep pyrosequencing to characterize cDNAs from developing fibers at two key developmental time-points; 10 and 22 days post anthesis. A unigene set was assembled and annotated, and differential digital gene expression was assessed from the different time-point and genotype representations of the reads within assembled contigs. As a complementary approach, we conducted microarray-based hybridization profiling using the cotton Affymetrix gene chip and labeled cDNAs from fibers at 11 dpa and for the same two genotypes and compared differentially expressed genes identified by the two platforms. The 454 unigenes were also mined for the presence of microsatellite repeats and SNPs that will be useful markers for mapping and marker-assisted selection in cotton improvement.-Total RNA was extracted from 11 dpa-old fibers from the two genotypes, Guazuncho 2 (Gossypium hirsutum) and VH8-4602 (G. barbadense), and included two replicates of each. RNA was checked for quality and quantity using an Agilent Bioanalyser 2100 (Agilent Technologies, Santa Clara, CA, USA, http://www.home.agilent.com) following the manufacturers recommendations. The RNA was sent to the Australian Genome Research Facility Ltd. (http://www.agrf.org.au, Melbourne, Victoria, Australia) for labeling and hybridization to the Affymetrix Genechip Cotton Genome Array (21,854 genes) (Affymetrix, http://www.affymetrix.com/). -

Publication Title

Deep sequencing reveals differences in the transcriptional landscapes of fibers from two cultivated species of cotton.

Sample Metadata Fields

Age, Specimen part

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accession-icon E-MTAB-991
Transcription profiling by array of human colon cancer xenografted in immunodeficient mice and rats to investigate clinical heterogeneity
  • organism-icon Homo sapiens
  • sample-icon 115 Downloadable Samples
  • Technology Badge Icon Affymetrix HT Human Genome U133A Array (hthgu133a)

Description

Patient-derived xenograft models are considered to represent the heterogeneity of human cancers and might be more relevant preclinical models to evaluate effective therapeutic agents. Our consortium joins efforts to extensively develop and characterize a new collection of patient-derived colorectal cancer models. From 86 unsupervised surgical colon sample collection, 54 tumors were successfully xenografted in immunodeficient mice and rats, representing 35 primary tumors, 5 peritoneal carcinosis and 14 metastases. Our histological and molecular characterization of patient tumors, first passage on mice and later passages includes the sequence of key genes involved in CRC (ie APC, KRAS, TP53), CGH array and transcriptomic analysis. This comprehensive characterization demonstrates that our collection recapitulates the clinical situation regarding the histopathological and molecular diversity of colorectal cancers. Moreover, patient tumors and corresponding models are clustering together which gives the opportunity to look for relevant signatures and comparison studies between clinical and preclinical data. Hence, we performed pharmacological monotherapy studies with standard of care for colon cancer (5-FU, oxaliplatin, irinotecan, cetuximab). Through this extensive in vivo analysis, we have compared the molecular profile with the drug sensitivity of each tumor models, and run an equivalent of a cetuximab phase II clinical trial in a preclinical setting. Our results confirm the key role of KRAS mutation in the cetuximab resistance and demonstrate that such collection could bring benefit to evaluate novel targeted therapeutic strategies and potentially help the stratification strategy for cancer patients according to molecular marker. This set correspond to 82 CGH profiles, with 7 samples from patient tumor and 75 samples from mouse xenograft at different passages P0 to P9. All hybridizations are performed with Human CGH 244K Agilent arrays (amadid 014693) in dual color with Human DNA Promega (sex matched) as reference. ID for biosources without an -Px suffix correspond to tumor patients. ID with a suffix correspond to xenograft with 0 for the first passage.

Publication Title

Characterization of a large panel of patient-derived tumor xenografts representing the clinical heterogeneity of human colorectal cancer.

Sample Metadata Fields

Specimen part, Disease, Disease stage, 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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