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GSE66368
Homo sapiens
25 Downloadable Samples
Affymetrix Human Genome U219 Array (hgu219), Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
EphB2 Promotes Progression of Cutaneous Squamous Cell Carcinoma.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Homo sapiens
- 13 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
The incidence of keratinocyte-derived skin cancer, cutaneous squamous cell carcinoma (cSCC) is increasing worldwide making it the second most common metastatic skin cancer.
Publication Title
EphB2 Promotes Progression of Cutaneous Squamous Cell Carcinoma.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Homo sapiens
- 12 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219), Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
The role of Eph/ephrin signaling in numerous biological processes has been established. However, Eph/ephrin signaling has been shown to have complex role in tumor progression. The role of EphB2 receptor in the progression of cutaneous squamous cell carcinoma (cSCC) has not been studied before.
Publication Title
EphB2 Promotes Progression of Cutaneous Squamous Cell Carcinoma.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 9 Downloadable Samples
Illumina HiSeq 2500
Description
Cell-penetrating peptides (CPP) uptake mechanism is still to be clarified to have a better understanding of their action in the mediation of oligonucleotide transfection. In this study, the effect on early events (1 h treatment) in transfection by Pepfect 14, with or without oligonucleotide cargo on gene expression, on HeLa cells, have been investigated. The RNA expression was characterized by RNA sequencing. Overall design: The quality of purified total RNA was estimated by Agilent 2200 TapeStation analysis (Agilent Technologies, Santa Clara, USA). One µg of total RNA was used as an input to prepare next-generation sequencing libraries according to the Illumina TruSeq Stranded mRNA sample preparation protocol (Illumina, San Diego, USA). Final library mixtures were quantified by Qubit 2.0 Fluorometer (Life Technologies, Grand Island, USA) and validated with Agilent 2200 TapeStation analysis. Libraries were quantified by qPCR with Kapa Library Quantification Kit (Kapa Biosystems, Woburn, USA) to optimize cluster generation and sequenced on HiSeq2500 platform (Illumina, San Diego, USA) with 2 x 50 bp paired-end reads. Over 93.9% of the bases sequenced were above the quality of Q30. Demultiplexing was done with CASAVA 1.8.2. (Illumina, San Diego, USA) Allowing one mismatch in 6 bp index read. Initial data analysis was conducted by the RNA-Seq pipeline of Estonian Genome Centre, University of Tartu. Shortly, fastQ files were trimmed (removal of adapter sequences and bases below the quality Q20) with FASTX-Toolkit version 0.013 (http://hannonlab.cshl.edu/fastx_toolkit) and then aligned to the human reference genome (hg19/GRCh37) with Bowtie version 2.1.019 in combination with TopHat version 2.0.1320. Transcript quantification (measured as FPKM) was conducted with Cuffdiff program from Cufflinks version 2.2.121 with reference annotation Homo_sapiens.GRCh37.72.gtf (http://ftp.ensembl.org/pub/release-72/gtf/homo_sapiens) Cuffdiff analysis, which summarizes expression changes for all annotated gene variations, was filtered by lowest q-values (corrected p-values for multiple testing) from output file gene_exp.diff and the top list of differentially expressed genes were analyzed through the use of QIAGEN’s Ingenuity® Pathway Analysis (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity).
Publication Title
Role of autophagy in cell-penetrating peptide transfection model.
Sample Metadata Fields
Cell line, Treatment, Subject
View Samples- Homo sapiens
- 32 Downloadable Samples
- Affymetrix Human Gene 1.1 ST Array (hugene11st), Illumina Genome Analyzer IIx
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Genome-wide screen of cell-cycle regulators in normal and tumor cells identifies a differential response to nucleosome depletion.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Homo sapiens
- 32 Downloadable Samples
- Illumina Genome Analyzer IIx, Affymetrix Human Gene 1.1 ST Array (hugene11st)
Description
Gene-expression in siRNA treated U2OS and hTERT-RPE1 cells showed that CASP8AP2, NPAT and HINFP do not regulate expression of each other, and do not have any common target genes, except histones. Most histone genes are downregulated in U2OS cells following loss of CASP8AP2, NPAT or HINFP. In normal cells, highly-expressed histone genes were downregulated, albeit less than in tumor cells following loss of CASP8AP2. The p53 target genes were upregulated relatively late, clearly after the changes in expression of histone genes were observed.
Publication Title
Genome-wide screen of cell-cycle regulators in normal and tumor cells identifies a differential response to nucleosome depletion.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 18 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
The tumor suppressor p53 can induce various biological responses. Yet it is not clear whether it is p53 in vivo promoter selectivity that triggers different transcription programs leading to different outcomes. Our analysis of genome-wide chromatin occupancy by p53 using ChIP-seq (deposited in Sequence Read Archive database as SRP007261) revealed p53 default program, i.e. the pattern of major p53-bound sites that is similar upon p53 activation by nutlin3a, RITA or 5-FU in breast cancer cells, despite different biological outcomes triggered by these compounds. Parallel analysis of gene expression allowed identification of 280 previously unknown p53 target genes, including p53-repressed AURKA. The consensus p53 binding motif was present more frequently in p53-induced, than in repressed targets, indicating different mechanisms of gene activation versus repression. We identified several possible cofactors of p53, and found that STAT3 antagonised p53-mediated repression of a subset of genes, including AURKA. Finally, we showed that the expression of the novel p53 targets correlates with p53 status and survival in breast cancer patients.
Publication Title
Insights into p53 transcriptional function via genome-wide chromatin occupancy and gene expression analysis.
Sample Metadata Fields
Cell line, Treatment
View Samples- Mus musculus
- 2 Downloadable Samples
- Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)
Description
Comparison of acetylcholine receptor immunization between RIIIS/J and B10.RIII mice.
Publication Title
Periodic gene expression program of the fission yeast cell cycle.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 7 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
TF binding clusters in promoter correlate well with gene expression. We used ChIP-seq to map binding sites of the majority of highly expressed TFs in the cell. The size of clusters of TFs in the promoters of genes were found to correlate well with gene expression.
Publication Title
Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 15 Downloadable Samples
- Illumina HiSeq 2500
Description
Regulatory CD4+ T cells (Tregs) are functionally distinct from conventional CD4+ T cells (Tconvs). To understand Treg identity, we have compared by proteomics and transcriptomics human naïve (n) and effector (e)Tregs, Tconvs and transitional FOXP3+ cells. Among these CD4+ T cell subsets, we detected differential expression of 421 proteins and 640 mRNAs, with only 48 molecules shared. Fifty proteins discriminated Tregs from Tconvs. This common Treg protein signature indicates altered signaling by TCR-, TNF receptor-, NFkB-, PI3 kinase/mTOR-, NFAT- and STAT pathways and unique cell biological and metabolic features. Another protein signature uniquely identified eTregs and revealed active cell division, apoptosis sensitivity and suppression of NFkB- and STAT signaling. eTreg fate appears consolidated by FOXP3 outnumbering its partner transcription factors. These features explain why eTregs cannot produce inflammatory cytokines, while transitional FOXP3+ cells can. Our collective data reveal that Tregs protect their identity by a unique “wiring” of signalling pathways Overall design: mRNA profiles of 5 CD4+ T cell populations were generated by deep sequencing, in triplicate
Publication Title
Proteomic Analyses of Human Regulatory T Cells Reveal Adaptations in Signaling Pathways that Protect Cellular Identity.
Sample Metadata Fields
Subject
View Samples