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GSE33538
Homo sapiens
24 Downloadable Samples
Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
MicroRNAs (miRs) function primarily as post-transcriptional negative regulators of gene expression through binding to their mRNA targets. Reliable prediction of a miRs targets is a considerable bioinformatic challenge of great importance for inferring the miRs function. Sequence-based prediction algorithms have high false-positive rates, are not in agreement, and are not biological context specific. Here we introduce CoSMic (Context-Specific MicroRNA analysis), an algorithm that combines sequence-based prediction with miR and mRNA expression data. CoSMic differs from existing methodsit identifies miRs that play active roles in the specific biological system of interest and predicts with less false positives their functional targets. We applied CoSMic to search for miRs that regulate the migratory response of human mammary cells to epidermal growth factor (EGF) stimulation. Several such miRs, whose putative targets were significantly enriched by migration processes were identified. We tested three of these miRs experimentally, and showed that they indeed affected the migratory phenotype; we also tested three negative controls. In comparison to other algorithms CoSMic indeed filters out false positives and allows improved identification of context-specific targets. CoSMic can greatly facilitate miR research in general and, in particular, advance our understanding of individual miRs function in a specific context.
Publication Title
Context-specific microRNA analysis: identification of functional microRNAs and their mRNA targets.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 16 Downloadable Samples
IlluminaHiSeq2000
Description
p53 is a pivotal tumor suppressor and a major barrier against cancer. We now report that silencing of the Hippo pathway tumor suppressors LATS1 and LATS2 in non-transformed mammary epithelial cells reduces p53 phosphorylation and increases its association with the p52 NF-?B subunit. Moreover, it partly shifts p53’s conformation and transcriptional output towards a state resembling cancer-associated p53 mutants, and endow p53 with the ability to promote cell migration. Notably, LATS1 and LATS2 are frequently downregulated in breast cancer; we propose that such downregulation might benefit cancer by converting p53 from a tumor suppressor into a tumor facilitator. Overall design: MCF10A cells transfected with siRNA against LATS1/2 alone, p53 alone or LATS1/2 and p53 together. Two independent MCF10A batches provided biological replicates
Publication Title
Down-regulation of LATS kinases alters p53 to promote cell migration.
Sample Metadata Fields
No sample metadata fields
View Samples- Danio rerio
- 12 Downloadable Samples
- Affymetrix Zebrafish Genome Array (zebrafish)
Description
Microarray data allowed detection of genes that are induced by light in the zebrafish pineal gland
Publication Title
The light-induced transcriptome of the zebrafish pineal gland reveals complex regulation of the circadian clockwork by light.
Sample Metadata Fields
Sex, Specimen part, Treatment, Time
View Samples- Homo sapiens
- 71 Downloadable Samples
- NextSeq 500
Description
During host-pathogen encounters, the complex interactions between different immune cell-types can determine the outcome of infection. Advances in single cell RNA-seq (scRNA-seq) allow to probe this complexity of immunity, and afforded the basis for deconvolution algorithms that infer cell-type compositions from bulk RNA-seq measurements. However, immune activation, an important aspect of immune surveillance, is not represented in current algorithms. Here, using scRNA-seq of human peripheral blood cells infected with Salmonella, we developed a novel deconvolution algorithm to infer dynamic immune states from bulk measurements. We applied our dynamic deconvolution algorithm both to cohorts of healthy individuals challenged ex vivo with Salmonella and to cohorts of tuberculosis patients during different stages of disease. We revealed cell-type specific immune responses associated not only with ex vivo infection phenotype but also with clinical disease stage. We propose that our approach provides a predictive power to identify risk for disease, and can be applied to comprehensively study human infection outcome. Overall design: PBMCs were isolated from 8 individuals bearing or not TLR10 polymorphism and were infected ex vivo with Salmonella enterica serovar Typhimurium. RNA was extracted before infection, 4 hours post infection and 8 hours post infection.
Publication Title
Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 62 Downloadable Samples
- NextSeq 500
Description
During host-pathogen encounters, the complex interactions between different immune cell-types can determine the outcome of infection. Advances in single cell RNA-seq (scRNA-seq) allow to probe this complexity of immunity, and afforded the basis for deconvolution algorithms that infer cell-type compositions from bulk RNA-seq measurements. However, immune activation, an important aspect of immune surveillance, is not represented in current algorithms. Here, using scRNA-seq of human peripheral blood cells infected with Salmonella, we developed a novel deconvolution algorithm to infer dynamic immune states from bulk measurements. We applied our dynamic deconvolution algorithm both to cohorts of healthy individuals challenged ex vivo with Salmonella and to cohorts of tuberculosis patients during different stages of disease. We revealed cell-type specific immune responses associated not only with ex vivo infection phenotype but also with clinical disease stage. We propose that our approach provides a predictive power to identify risk for disease, and can be applied to comprehensively study human infection outcome. Overall design: Whole-blood (WB) cells and PBMCs were isolated from 4 healthy individuals and were infected ex vivo with Salmonella enterica serovar Typhimurium or with PBS as control. RNA was extracted 4 hours later.
Publication Title
Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells.
Sample Metadata Fields
Specimen part, Disease stage, Subject
View Samples- Homo sapiens
- 13 Downloadable Samples
- NextSeq 500
Description
During host-pathogen encounters, the complex interactions between different immune cell-types can determine the outcome of infection. Advances in single cell RNA-seq (scRNA-seq) allow to probe this complexity of immunity, and afforded the basis for deconvolution algorithms that infer cell-type compositions from bulk RNA-seq measurements. However, immune activation, an important aspect of immune surveillance, is not represented in current algorithms. Here, using scRNA-seq of human peripheral blood cells infected with Salmonella, we developed a novel deconvolution algorithm to infer dynamic immune states from bulk measurements. We applied our dynamic deconvolution algorithm both to cohorts of healthy individuals challenged ex vivo with Salmonella and to cohorts of tuberculosis patients during different stages of disease. We revealed cell-type specific immune responses associated not only with ex vivo infection phenotype but also with clinical disease stage. We propose that our approach provides a predictive power to identify risk for disease, and can be applied to comprehensively study human infection outcome. Overall design: PBMCs were isolated from a healthy individual and were infected ex vivo with Salmonella enterica serovar Typhimurium or with PBS as control. Monocytes and NKT cells were sorted from naïve and infected PBMCs. RNA was extracted 4 hours post infection.
Publication Title
Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells.
Sample Metadata Fields
Subject
View Samples- Homo sapiens
- 12 Downloadable Samples
- NextSeq 500
Description
During host-pathogen encounters, the complex interactions between different immune cell-types can determine the outcome of infection. Advances in single cell RNA-seq (scRNA-seq) allow to probe this complexity of immunity, and afforded the basis for deconvolution algorithms that infer cell-type compositions from bulk RNA-seq measurements. However, immune activation, an important aspect of immune surveillance, is not represented in current algorithms. Here, using scRNA-seq of human peripheral blood cells infected with Salmonella, we developed a novel deconvolution algorithm to infer dynamic immune states from bulk measurements. We applied our dynamic deconvolution algorithm both to cohorts of healthy individuals challenged ex vivo with Salmonella and to cohorts of tuberculosis patients during different stages of disease. We revealed cell-type specific immune responses associated not only with ex vivo infection phenotype but also with clinical disease stage. We propose that our approach provides a predictive power to identify risk for disease, and can be applied to comprehensively study human infection outcome. Overall design: Frozen PBMCs from healthy individual were defrosted and infectd ex vivo with Salmonella enterica serovar Typhimurium.
Publication Title
Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 188 Downloadable Samples
- Illumina HiSeq 2500
Description
Background: The main bottleneck for genomic studies of tumors is the limited availability of fresh frozen (FF) samples collected from patients, coupled with comprehensive long-term clinical follow-up. This shortage could be alleviated by using existing large archives of routinely obtained and stored Formalin-Fixed Paraffin-Embedded (FFPE) tissues. However, since these samples are partially degraded, their RNA sequencing is technically challenging. Results: In an effort to establish a reliable and practical procedure, we compared three protocols for RNA sequencing using pairs of FF and FFPE samples, both taken from the same breast tumor. In contrast to previous studies, we compared the expression profiles obtained from the two matched sample types, using the same protocol for both. Three protocols were tested on low initial amounts of RNA, as little as 100 ng, to represent the possibly limited availability of clinical samples. For two of the three protocols tested, poly(A) selection (mRNA-seq) and ribosomal-depletion, the total gene expression profiles of matched FF and FFPE pairs were highly correlated. For both protocols, differential gene expression between two FFPE samples was in agreement with their matched FF samples. Notably, although expression levels of FFPE samples by mRNA-seq were mainly represented by the 3'-end of the transcript, they yielded very similar results to those obtained by ribosomal-depletion protocol, which produces uniform coverage across the transcript. Further, focusing on clinically relevant genes, we showed that the high correlation between expression levels persists at higher resolutions. Conclusions: Using the poly(A) protocol for FFPE exhibited, unexpectedly, similar efficiency to the ribosomal-depletion protocol, with the latter requiring much higher (2-3 fold) sequencing depth to compensate for the relative low fraction of reads mapped to the transcriptome. The results indicate that standard poly(A)-based RNA sequencing of archived FFPE samples is a reliable and cost-effective alternative for measuring mRNA-seq on FF samples. Expression profiling of FFPE samples by mRNA-seq can facilitate much needed extensive retrospective clinical genomic studies. Overall design: We perform an unbiased evaluation of RNA-seq of archived tumor tissues by comparing the same library preparation methods for both FF and FFPE matched tumor samples and for small amounts of total RNA starting material. We have 3 matched FF/FFPE tumor samples with a moderate archival time of about 4-5 years (T1=T3), and additional 3 FFPE tumor samples archived for more than 10 years (T4-T6). all samples were tested with two protocols: illumina Truseq RNA after poly(A) selection (mRNA-seq); and Truseq after ribosomal depletion (RiboZero). Several initial amounts of starting material was tested for eacg protocol.
Publication Title
mRNA-seq whole transcriptome profiling of fresh frozen versus archived fixed tissues.
Sample Metadata Fields
Specimen part, Disease, Subject
View Samples- Mus musculus
- 21 Downloadable Samples
- Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)
Description
Surgical resection is the preferred treatment for Hepatocellular carcinoma; however, it induces tumor recurrence. Our objective was to understand the molecular mechanisms linking liver regeneration under chronic-inflammation to tumorigenesis. Mdr2-knockout mice, a model of inflammation-associated cancer, underwent partial-hepatectomy which led to enhanced hepatocarcinogenesis. Yet, liver regeneration in these mice was severely attenuated. We demonstrate the activation of the DNA damage response machinery and altered genomic instability during early liver inflammatory stages resulting in hepatocyte apoptosis and cell-cycle arrest, and suggest their involvement in tumor recurrence subsequent to partial hepatectomy. We propose that under the regenerative proliferative stress induced by liver resection, the genomic unstable hepatocytes generated during chronic-inflammation, escape apoptosis and reenter the cell-cycle, triggering the enhanced tumorigenesis
Publication Title
Accelerated carcinogenesis following liver regeneration is associated with chronic inflammation-induced double-strand DNA breaks.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 5 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
The tumorigenicity of human pluripotent stem cells (hPSCs) is a major safety concern for their application in regenerative medicine. Here we identify the tight-junction protein Claudin-6 as a specific cell surface marker of hPSCs that can be used to selectively remove Claudin-6-positive cells from mixed cultures. We show that Claudin-6 is absent in adult tissues but highly expressed in undifferentiated cells, where it is dispensable for hPSC survival and self-renewal. We use three different strategies to remove Claudin-6-positive cells from mixed populations: an antibody against Claudin-6; a cytotoxin-conjugated antibody that selectively targets undifferentiated cells; and clostridium perfringens enterotoxin, a toxin that binds several Claudins, including Claudin-6, and efficiently kills undifferentiated cells, thus eliminating the tumorigenic potential of hPSC-containing cultures. This work provides a proof of concept for the use of Claudin-6 to eliminate residual undifferentiated hPSCs from culture, highlighting a strategy that may increase the safety of hPSC-based cell therapies.
Publication Title
Immunologic and chemical targeting of the tight-junction protein Claudin-6 eliminates tumorigenic human pluripotent stem cells.
Sample Metadata Fields
Specimen part, Cell line
View Samples