This SuperSeries is composed of the SubSeries listed below.
A comparative study of RNA-Seq and microarray data analysis on the two examples of rectal-cancer patients and Burkitt Lymphoma cells.
Cell line, Treatment
View SamplesRNA-Seq profiling of Burkitt Lymphoma cell line (BL2) with B-cell activating factor (BAFF) for 24 hrs . The Burkitt Lymphoma cell line were either only cultured in cell culture medium supplemented with 10 mM HEPES at 1 × 106 cells/ml or additionally incubated with B-cell activating factor (BAFF) for 24 hrs Overall design: Two conditions of BL2 cells each in 3 replicates: 1. non-stimulated control (BL2), 2. Baff stimulated (BL2Baff)
A comparative study of RNA-Seq and microarray data analysis on the two examples of rectal-cancer patients and Burkitt Lymphoma cells.
Treatment, Subject
View SamplesMicroarray profiling of Burkitt Lymphoma cell line (BL2) with B-cell activating factor (BAFF) for 24 hrs .
A comparative study of RNA-Seq and microarray data analysis on the two examples of rectal-cancer patients and Burkitt Lymphoma cells.
Cell line
View SamplesRNA-Seq profiling of MCF-7 and MDA-MB-231. We profiled RNA expression in the estrogen-receptor-positive (ER+) MCF-7 and the triple-negative MDA-MB-231 breast cancer cells. The objective was to find genes differentially expressed between these cell lines as potential drivers of invasiveness of the triple-negative MDA-MB-231. We further utilized the identified differential genes to validate expression-responsive module of non-canonical Wnt signaling pathway. Overall design: 2 biological replicates of MCF-7 and 3 biological replicates of MDA-MB-231
Newly Constructed Network Models of Different WNT Signaling Cascades Applied to Breast Cancer Expression Data.
No sample metadata fields
View SamplesRNA-Seq profiling of estrogen-receptor-positive MCF-7 cell lines with different perturbations of non-canonical WNT signaling . The MCF-7 cells were either transfected with an empty vector (pcDNA) or with a ROR2 overexpression construct, in parallel with or without stimulation with recombinant WNT5A. The objective was to find expression-responsive targets of these perturbations as potential drivers of increased cell invasiveness. Overall design: Four conditions of MCF-7 cells each in 3 replicates: 1. empty vector (pcDNA), 2. empty vector (pcDNA) with WNT5A stimulation, 3. ROR2 overexpression construct, 4. ROR2 overexpression construct with WNT5A stimulation
Ror2 Signaling and Its Relevance in Breast Cancer Progression.
No sample metadata fields
View SamplesIn this dataset, we present RNA-Seq data of two colorectal cancer (CRC) cell lines, namely 1638N-T1 and CMT-93. Overall design: Two colorectal cancer cell lines in 3 replicates
Computational Identification of Key Regulators in Two Different Colorectal Cancer Cell Lines.
Cell line, Subject
View SamplesThe intention was to detect genes that are determining trastuzumab efficiency in HER2-positive breast cancer cell lines with different resistance phenotypes. While BT474 should be sensitive to the drug treatment, HCC1954 is expected to be resistant due to a PI3K mutation. The cell line BTR50 has been derived from BT474 and was cultured to be resistant as well. Based on RNA-Seq data, we performed differential expression analyses on these breast cancer cell lines with and without trastuzumab treatment. In detail, five separate tests were performed, namely resistant cells vs. wild type, i.e. HCC1954 and BTR50 vs. BT474, respectively, and untreated vs. drug treated cells. The significant genes of the first two tests should contribute to resistance. The significant genes of the test BT474 vs. its drug treated version should contribute to the trastuzumab effect. To exclude false positives from the combined gene set (#64), we removed ten genes that were also significant in the test BTR50 vs. its drug treated version. This way we ended up with 54 genes that are very likely to determine trastuzumab efficiency in HER2-positive breast cancer cell lines. Overall design: mRNA profiles of human breast cancer cell lines were generated by deep sequencing using Illumina HiSeq 2000. The cell lines BT474 and HCC1954 were analyzed with and without trastuzumab treatment. HCC1954 is known to be trastuzumab resistant. Additionally, the cell line BTR50 was generated as resistant version of BT474, and was analyzed with and without trastuzumab as well.
mRNA profiling reveals determinants of trastuzumab efficiency in HER2-positive breast cancer.
No sample metadata fields
View SamplesMicroarray analysis of 28 brain metastasis samples from lung adenocarcinoma patients.
Isolated metastasis of an EGFR-L858R-mutated NSCLC of the meninges: the potential impact of CXCL12/CXCR4 axis in EGFR<sub>mut</sub> NSCLC in diagnosis, follow-up and treatment.
No sample metadata fields
View SamplesBacteria selectively consume some carbon sources over others through a regulatory mechanism termed catabolite repression. Here, we show that the base pairing RNA Spot 42 plays a broad role in catabolite repression in Escherichia coli by directly repressing genes involved in central and secondary metabolism, redox balancing, and the consumption of diverse non-preferred carbon sources. Many of the genes repressed by Spot 42 are transcriptionally activated by the global regulator CRP. Since CRP represses Spot 42, these regulators participate in a specific regulatory circuit called a multi-output feedforward loop. We found that this loop can reduce leaky expression of target genes in the presence of glucose and can maintain repression of target genes under changing nutrient conditions. Our results suggest that base pairing RNAs in feedforward loops can help shape the steady-state levels and dynamics of gene expression.
The base-pairing RNA spot 42 participates in a multioutput feedforward loop to help enact catabolite repression in Escherichia coli.
Specimen part
View SamplesThe transcriptome is the complete set of all RNA transcripts produced by the genome in a cell and reflects the genes that are being actively expressed. Transcriptome analysis is essential for understanding the genetic mechanism controlling the phenotype of a cell.
Characterization of transcriptomes of cochlear inner and outer hair cells.
Specimen part
View Samples