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accession-icon GSE146110
The role of lncRNA Lassie in endothelial cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

The vascular endothelium forms a physical barrier between blood and the surrounding tissue. Its constant exposure to haemodynamic shear stress controls endothelial barrier function which is of major importance for vascular homeostasis. The role of long non-coding RNAs (lncRNAs) in this process remains elusive. Here we identify the shear stress-induced lncRNA LASSIE (linc00520) as a stabilizer of adherens junctions (AJs) in endothelial cells (ECs), that is indispensable for normal endothelial barrier function and shear stress sensing. Silencing of LASSIE in ECs resulted in impaired cell survival, loss of cell-cell contacts and failure to align in the direction of flow. RNA affinity purification followed by mass spectrometry identified several junction proteins associated with LASSIE, including the endothelial adhesion protein PECAM-1 and intermediate filament (IF) protein nestin. Proteomic analysis of VE-cadherin-associated proteins showed that LASSIE silencing reduces VE-cadherin interaction with nestin and microtubule (MT)-associated cytoskeletal proteins. We confirmed that LASSIE silencing results in a decreased connection between VE-Cadherin and the cytoskeleton, resulting in loss of barrier function and shear stress sensing. Together, this study identifies the shear stress-induced lncRNA LASSIE as a critical link between AJs and the IF cytoskeleton, which is indispensable for normal EC junction stabilization and shear stress sensing.

Publication Title

Long non-coding RNA LASSIE regulates shear stress sensing and endothelial barrier function.

Sample Metadata Fields

Specimen part

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accession-icon SRP019994
Stratification of Leiomyosarcoma molecular subtypes by 3'' end RNA-sequencing: Toward precision medicine
  • organism-icon Homo sapiens
  • sample-icon 99 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

Leiomyosarcoma (LMS) is a malignant neoplasm with smooth muscle differentiation. Little is known about its molecular heterogeneity and no targeted therapy currently exists for LMS. We demonstrate the existence of 3 molecular subtypes in a cohort of 99 cases and an independent cohort of 82 LMS. Two new FFPE tissue-compatible diagnostic immunohistochemical markers are identified: LMOD1 for subtype I LMS and ARL4C for subtype II LMS. Subtype I and subtype II LMS are associated with good and poor prognosis, respectively. The LMS subtypes show significant differences in expression levels for genes for which novel targeted therapies are being developed. Overall design: Gene expression profiling was performed by 3'' End RNA Sequencing (3SEQ), a next generation sequencing approach that does not rely on frozen tissue but can be performed on archival FFPE tissue. Samples included 99 LMS, 6 Undifferentiated Pleomorphic Sarcomas (UPS), 3 leiomyomas, 4 normal myometrium samples, and 1 case of Lymphangioleiomyomatosis (LAM). This study only includes the 99 LMS Samples. After gene expression levels were quantified by 3SEQ analysis pipeline, Consensus Clustering with bootstrap method was used to determine that the dataset contained three robust subtypes, and Silhouette analysis was performed to validate the subtype assignments. Two class SAM analysis (Significance Analysis of Microarrays) was performed to identify genes expressed differentially between each subtype of LMS with FDR of 0.05. Immunohistochemical staining was used to validate the potential diagnostic and prognostic markers from 3SEQ data on a tissue microarray.

Publication Title

Molecular subtyping of leiomyosarcoma with 3' end RNA sequencing.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE57434
Transcriptional response of Drosophila S2 cells in response the Drosophila C Virus infection (DCV)
  • organism-icon Drosophila melanogaster
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Drosophila Genome 2.0 Array (drosophila2)

Description

We infected Drosophila S2 cells (invitrogen) with Drosophila C virus (DCV) (Multiplicity of Infection = 10), and harvested samples for further analysis at 8 and 24 hours post-infection.

Publication Title

The heat shock response restricts virus infection in Drosophila.

Sample Metadata Fields

Cell line, Time

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accession-icon SRP017575
Two New Stromal Signatures Stratify Breast Cancers with Different Prognosis
  • organism-icon Homo sapiens
  • sample-icon 53 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

Purpose: Multiple studies from last decades have shown that the microenvironment of carcinomas plays an important role in the initiation, progression and metastasis of cancer. Our group has previously identified novel cancer stroma gene expression signatures associated with outcome differences in breast cancer by gene expression profiling of two tumors of fibroblasts as surrogates for physiologic stromal expression patterns. The aim of this study is to find additional new types of tumor stroma gene expression patterns. Results: 53 tumors were sequenced by 3SEQ with an average of 29 million reads per sample. Both the elastofibroma (EF) and fibroma of tendon sheath (FOTS) gene signatures demonstrated robust outcome results for survival in the four breast cancer datasets. The EF signature positive breast cancers (20-33% of the cohort) demonstrated significantly better outcome for survival. In contrast, the FOTS signature positive breast cancers (11-35% of the cohort) had a worse outcome. The combined stromal signatures of EF, FOTS, and our previously identified DTF, and CSF1 signatures characterize, in part, the stromal expression profile for the tumor microenvironment for between 74%-90% of all breast cancers. Conclusions: We defined and validated two new stromal signatures in breast cancer (EF and FOTS), which are significantly associated with prognosis. Overall design: Gene expression profiling by 3SEQ was performed on 8 additional types of fibrous tumors, to identify different fibrous tumor specific gene expression signatures. We then determined the significance of the fibrous tumor gene signatures in four publically available breast cancer datasets (GSE1456, GSE4922, GSE3494, NKI Dataset).

Publication Title

Next generation sequencing-based expression profiling identifies signatures from benign stromal proliferations that define stromal components of breast cancer.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP015977
Mouse Model of Clear Cell Sarcoma
  • organism-icon Mus musculus
  • sample-icon 32 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Profile gene expression from tumors that develop in mice bearing conditional activation of EWS-ATF1, compared to control mouse tissues from the chest wall as well as tumor samples from mouse models of synovial sarcoma and osteosarcoma achieved by conditional disruption of Rb1 and p53 Overall design: 13 clear cell sarcomas (5 started with Rosa26CreER, 4 with TATCre, 2 with Prx1CreERT2, and 2 with Bmi1IRESCreERT2), 7 osteosarcomas, 6 synovial sarcomas, 6 control samples

Publication Title

Modeling clear cell sarcomagenesis in the mouse: cell of origin differentiation state impacts tumor characteristics.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP040306
Transcriptome of wild-type and G9a mutant upon viral challenge
  • organism-icon Drosophila melanogaster
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

The aim of the study was to generate transcriptome of wild-type and G9a mutant adult flies (females) 24h post-infection with Drosophila C Virus (DCV). Overall design: We generated 8 different data sets. For wild-type controls and G9a mutants, we performed both mock and DCV infection, and collected both whole flies and fat bodies. All flies were 3-5 days old females.

Publication Title

The epigenetic regulator G9a mediates tolerance to RNA virus infection in Drosophila.

Sample Metadata Fields

Specimen part, Subject, Time

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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 GSE27849
Dietary heme stimulates epithelial cell turnover by downregulating feedback inhibitors of proliferation in murine colon
  • organism-icon Mus musculus
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st), Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Dietary haem stimulates epithelial cell turnover by downregulating feedback inhibitors of proliferation in murine colon.

Sample Metadata Fields

Sex, Age, Specimen part, Treatment

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accession-icon GSE27848
Dietary heme stimulates epithelial cell turnover by downregulating feedback inhibitors of proliferation in murine colon (part 2)
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The risk for colon cancer is associated with nutrition, especially high fat and low calcium diets high in red meat. Red meat contains the iron porphyrin pigment heme, which induces cytotoxicity of the colon contents and epithelial hyperproliferation. Using a mouse model, we showed that heme caused damage to the colonic surface epithelium and induced compensatory hyperproliferation. Expression levels of heme- and stress-related genes show that heme affects surface cells and not directly crypt cells. Therefore, injured surface cells should signal to crypt TA cells to induce compensatory hyperproliferation. Surface-specific downregulated inhibitors of proliferation were Wnt inhibitory factor 1, Indian Hedgehog, Bone morphogenic protein 2 and possibly Interleukin-15. Heme also upregulated Amphiregulin, Epiregulin and Cyclooxygenase-2 mRNA in the surface cells, however, their protein/metabolite levels were not increased as heme induced surface-specific translation repression by increasing 4E-BP1. Therefore, we conclude that heme induced colonic hyperproliferation and hyperplasia by repressing feedback inhibition of proliferation.

Publication Title

Dietary haem stimulates epithelial cell turnover by downregulating feedback inhibitors of proliferation in murine colon.

Sample Metadata Fields

Sex, Age, Specimen part, Treatment

View Samples
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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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