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accession-icon SRP187599
mRNA sequencing of single-cell and 20-cell pools of CD103+CD8+ and CD103-CD8+ T lymphocytes sorted from human ovarian cancer
  • organism-icon Homo sapiens
  • sample-icon 118 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Cytotoxic T cells confer a prognostic benefit in many tumors, including ovarian cancer. We and others have previously identified a subset of CD8+ T cells, namely CD103+CD8+ T cells, that seems to have a better prognostic effect. The aim of this study is to identify how these CD103+ T cells differ from CD103-CD8+ T cells on mRNA level in human samples of ovarian cancer. Overall design: mRNA profiles of 10 pools of 20 cells CD103+CD8+, 10 pools of 20 cells CD103-CD8+, 20 single-cells CD103+CD8+, 20 single-cells CD103-CD8+ were generated from TILs of 3 ovarian cancers (high-grade serous ovarian cancer) by SMARTseq2

Publication Title

A Transcriptionally Distinct CXCL13<sup>+</sup>CD103<sup>+</sup>CD8<sup>+</sup> T-cell Population Is Associated with B-cell Recruitment and Neoantigen Load in Human Cancer.

Sample Metadata Fields

Subject

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accession-icon GSE94801
Macrophages confer survival signals via CCR1-dependent translational MCL-1 induction in chronic lymphocytic leukemia.
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Protective interactions with bystander cells in micro-environmental niches such as lymph nodes (LNs) contribute to survival and therapy resistance of chronic lymphocytic leukemia (CLL) cells. This is caused by a shift in expression of BCL-2 family members. Pro-survival proteins BCL-XL, BFL-1, and MCL-1 are upregulated by LN-residing T cells through CD40L interaction, presumably via NF-B signaling. Macrophages also reside in the LN, and are assumed to provide important supportive functions for CLL cells. However, if and how macrophages are able to induce survival is incompletely known. We first established that macrophages induced survival due to an exclusive upregulation of MCL-1. Next, we investigated the mechanism underlying MCL-1 induction by macrophages in comparison with CD40L. Genome-wide expression profiling of in vitro macrophage- and CD40L-stimulated CLL cells indicated activation of the PI3K-AKT-mTOR pathway, which was confirmed in ex vivo CLL LN material. Inhibition of PI3K-AKT-mTOR signaling abrogated MCL-1 upregulation and survival by macrophages as well asCD40 stimulation. MCL-1 can be regulated at multiple levels, and we established that AKT leads to increased MCL-1 translation, but does not affect MCL-1 transcription or protein stabilization. Furthermore, among macrophage-secreted factors that could activate AKT, we found that induction of MCL-1 and survival critically depended on C-C Motif Chemokine Receptor-1 (CCR1). In conclusion, this study indicates that two distinct micro-environmental factors, CD40L and macrophages, signal via CCR1 to induce AKT activation resulting in translational stabilization of MCL-1, and hence can contribute to CLL cell survival.

Publication Title

Macrophages confer survival signals via CCR1-dependent translational MCL-1 induction in chronic lymphocytic leukemia.

Sample Metadata Fields

Specimen part, Disease stage

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accession-icon GSE9232
Control of glycolytic enzyme fluxes in Saccharomyces cerevisiae
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome S98 Array (ygs98)

Description

Metabolic fluxes may be regulated "hierarchically," e.g., by changes of gene expression that adjust enzyme capacities (V(max)) and/or "metabolically" by interactions of enzymes with substrates, products, or allosteric effectors. In the present study, a method is developed to dissect the hierarchical regulation into contributions by transcription, translation, protein degradation, and posttranslational modification. The method was applied to the regulation of fluxes through individual glycolytic enzymes when the yeast Saccharomyces cerevisiae was confronted with the absence of oxygen and the presence of benzoic acid depleting its ATP. Metabolic regulation largely contributed to the approximately 10-fold change in flux through the glycolytic enzymes. This contribution varied from 50 to 80%, depending on the glycolytic step and the cultivation condition tested. Within the 50-20% hierarchical regulation of fluxes, transcription played a minor role, whereas regulation of protein synthesis or degradation was the most important. These also contributed to 75-100% of the regulation of protein levels.

Publication Title

The fluxes through glycolytic enzymes in Saccharomyces cerevisiae are predominantly regulated at posttranscriptional levels.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE13567
US28-expressing and mock-transfected stable NIH-3T3 cell lines
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The human cytomegalovirus (HCMV) encodes the chemokine receptor US28 that exhibits constitutive activity. NIH-3T3 cells stably transfected with US28 present a pro-angiogenic and transformed phenotype both in vitro and in vivo.

Publication Title

The human cytomegalovirus-encoded chemokine receptor US28 promotes angiogenesis and tumor formation via cyclooxygenase-2.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE18497
Diagnosis-relapse in ALL
  • organism-icon Homo sapiens
  • sample-icon 81 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Almost a quarter of pediatric patients with Acute Lymphoblastic Leukemia (ALL) suffer from relapses. The biological mechanisms underlying therapy response and development of relapses have remained unclear. In an attempt to better understand this phenomenon, we have analyzed 41 matched diagnosis relapse pairs of ALL patients using genomewide expression arrays (82 arrays) on purified leukemic cells. In roughly half of the patients very few differences between diagnosis and relapse samples were found (stable group), suggesting that mostly extra-leukemic factors (e.g., drug distribution, drug metabolism, compliance) contributed to the relapse. Therefore, we focused our further analysis on 20 samples with clear differences in gene expression (skewed group), reasoning that these would allow us to better study the biological mechanisms underlying relapsed ALL. After finding the differences between diagnosis and relapse pairs in this group, we identified four major gene clusters corresponding to several pathways associated with changes in cell cycle, DNA replication, recombination and repair, as well as B cell developmental genes. We also identified cancer genes commonly associated with colon carcinomas and ubiquitination to be upregulated in relapsed ALL. Thus, about half of relapses are due to selection or emergence of a clone with deregulated expression of a genes involved in pathways that regulate B cell signaling, development, cell cycle, cellular division and replication.

Publication Title

Genome-wide expression analysis of paired diagnosis-relapse samples in ALL indicates involvement of pathways related to DNA replication, cell cycle and DNA repair, independent of immune phenotype.

Sample Metadata Fields

Sex, Specimen part, Disease

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accession-icon SRP170629
RNA Sequencing Analysis of Intracranial Aneurysm Walls Reveals Involvement of Lysosomes and Immunoglobulins in Rupture
  • organism-icon Homo sapiens
  • sample-icon 60 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Background and Purpose—Analyzing genes involved in development and rupture of intracranial aneurysms can enhance knowledge about the pathogenesis of aneurysms, and identify new treatment strategies. We compared gene expression between ruptured and unruptured aneurysms and control intracranial arteries. Methods—We determined expression levels with RNA sequencing. Applying a multivariate negative binomial model, we identified genes that were differentially expressed between 44 aneurysms and 16 control arteries, and between 22 ruptured and 21 unruptured aneurysms. The differential expression of 8 relevant and highly significant genes was validated using digital polymerase chain reaction. Pathway analysis was used to identify enriched pathways. We also analyzed genes with an extreme pattern of differential expression: only expressed in 1 condition without any expression in the other. Results—We found 229 differentially expressed genes in aneurysms versus controls and 1489 in ruptured versus unruptured aneurysms. The differential expression of all 8 genes selected for digital polymerase chain reaction validation was confirmed. Extracellular matrix pathways were enriched in aneurysms versus controls, whereas pathways involved in immune response and the lysosome pathway were enriched in ruptured versus unruptured aneurysms. Immunoglobulin genes were expressed in aneurysms, but showed no expression in controls. Conclusions—For rupture of intracranial aneurysms, we identified the lysosome pathway as a new pathway and found further evidence for the role of the immune response. Our results also point toward a role for immunoglobulins in the pathogenesis of aneurysms. Immune-modifying drugs are, therefore, interesting candidate treatment strategies in the prevention of aneurysm development and rupture. Overall design: RNA sequencing of 44 intracranial aneurysm samples (including 21 unruptured, 22 ruptured and 1 undetermined) and 16 control samples of the intracranial cortical artery

Publication Title

RNA Sequencing Analysis of Intracranial Aneurysm Walls Reveals Involvement of Lysosomes and Immunoglobulins in Rupture.

Sample Metadata Fields

Sex, Age, Subject

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accession-icon GSE40672
Dietary heme alters microbiota and mucosa of mouse colon without functional changes in host-microbe cross-talk.
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

Colon cancer is a major cause of cancer deaths in Western countries and is associated with diets high in red meat. Heme, the iron-porphyrin pigment of red meat, induces cytotoxicity of gut contents which injures surface cells leading to compensatory hyperproliferation of crypt cells. This hyperproliferation results in epithelial hyperplasia which increases the risk of colon cancer. In humans, a high red-meat diet increases Bacteroides spp in feces. Therefore, we simultaneously investigated the effects of dietary heme on colonic microbiota and on the host mucosa of mice. Whole genome microarrays showed that heme injured the colonic surface epithelium and induced hyperproliferation by changing the surface to crypt signaling. Using 16S rRNA phylogenetic microarrays, we investigated whether bacteria play a role in this changed signaling. Heme increased Bacteroidetes and decreased Firmicutes in colonic contents. This shift was most likely caused by a selective susceptibility of Gram-positive bacteria to heme cytotoxic fecal water, which is not observed for Gram-negative bacteria, allowing expansion of the Gram-negative community. The increased amount of Gram-negative bacteria most probably increased LPS exposure to colonocytes, however, there is no appreciable immune response detected in the heme-fed mice. There was no functional change in the sensing of the bacteria by the mucosa, as changes in inflammation pathways and Toll- like receptor signaling were not detected. This unaltered host-microbe cross-talk indicates that the changes in microbiota did not play a causal role in the observed hyperproliferation and hyperplasia.

Publication Title

Dietary heme alters microbiota and mucosa of mouse colon without functional changes in host-microbe cross-talk.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE34253
Dietary heme modulates microbiota and mucosa of mouse colon without significant host-microbe cross talk
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Previously, we showed that dietary heme injured the colonic surface epithelium and induced hyperproliferation by changing the surface to crypt signaling. In this study we investigated whether bacteria play a role in this changed signaling. Dietary heme increased the Bacteroidetes and decreased the Firmicutes in colonic content. This shift was caused by a selective susceptibility of Gram-positive bacteria to the heme cytotoxic fecal waters, which is not observed for Gram-negative bacteria allowing expansion of the Gram-negative community. The increased amount of Gram-negative bacteria increased LPS exposure to colonocytes, however, there is no appreciable immune response detected in the heme-fed mice. There were no signs of sensing of the bacteria by the mucosa, as changes in TLR signaling were not present. This lack of microbe-host cross talk indicated that the changes in microbiota do not play a causal role in the heme-induced hyperproliferation.

Publication Title

Dietary heme alters microbiota and mucosa of mouse colon without functional changes in host-microbe cross-talk.

Sample Metadata Fields

Sex, Age, Specimen part, Treatment

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accession-icon GSE5563
Gene expression profile of VIN lesions in comparison to controls
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

In order to understand the molecular mechanism behind Vulvar Intraepithelial Neoplasia (VIN), we have analyzed the gene expression profile of VIN lesions in comparison to controls.

Publication Title

HPV related VIN: highly proliferative and diminished responsiveness to extracellular signals.

Sample Metadata Fields

Sex

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accession-icon GSE26605
Deregulation of the ubiquitin-proteasome system is the predominant molecular pathology in OPMD animal models and patients
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

Oculopharyngeal muscular dystrophy (OPMD) is a late-onset progressive muscle disorder caused by a poly-alanine expansion mutation in PABPN1. The hallmark of OPMD is the accumulation of the mutant protein in insoluble nuclear inclusions. The molecular mechanisms associated with disease onset and progression are unknown. We performed a high-throughput cross-species transcriptome study of affected muscles from two OPMD animal models and from patients at pre-symptomatic and symptomatic stages. The most consistently and significantly OPMD-deregulated pathway across species is the ubiquitin-proteasome system (UPS). By analyzing expression profiles, we found that the majority of OPMD-deregulated genes are age-associated. Based on expression trends, disease onset can be separated from progression; the expression profiles of the proteasome-encoding genes are associated with onset but not with progression. In a muscle cell model, proteasome inhibition and the stimulation of immunoproteasome specifically affect the accumulation and aggregation of mutant PABPN1. We suggest that proteasome down-regulation during muscle aging triggers the accumulation of expPABPN1 that in turn enhances proteasome deregulation and leads to intranuclear inclusions (INI) formation.

Publication Title

Deregulation of the ubiquitin-proteasome system is the predominant molecular pathology in OPMD animal models and patients.

Sample Metadata Fields

Sex, Age, Disease, Disease stage

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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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