Project description:HT-29 human colorectal cancer xenografts were treated with vehicle control, MV-CD46-muPA, Minnelide, or MV-CD46-muPA + Minnelide combination. Three biological replicates per treatment group. RNA was extracted and analyzed using the nCounter Human Tumor Signaling 360 panel. RCC files are provided as raw data. Data were processed with nSolver 4.0 Advanced Analysis module with standard normalization and Benjamini–Hochberg correction.
Project description:HT-29 human colorectal cancer cells were treated in vitro with Vehicle control (Ctrl), MV-GFP (GFP), Triptolide (TRP), or MV-GFP + TRP (Combo). Three biological replicates were performed per treatment. RNA was extracted using NanoString protocols and analyzed with the nCounter Human Tumor Signaling 360 panel. RCC files for each replicate are provided as raw data. Data were processed using nSolver 4.0 Advanced Analysis module with standard normalization and Benjamini–Hochberg correction.
Project description:This study profiles targeted mRNA expression in neonatal saliva to investigate the sex-specific effects of prenatal opioid exposure. Saliva samples collected within 48 hours of birth from opioid-exposed and non-exposed neonates were analyzed using the NanoString nCounter Analysis System with a custom CodeSet targeting 72 genes, including housekeeping genes. Raw RCC files are provided for all assay instances, and processed data are provided as normalized, log2-transformed expression values for the QC-passed samples included in the final analysis.
Project description:NanoString raw data for a noeadjuvant combination PD-L1 plus CTLA-4 blockade trial on patients with cisplatin-ineligible operable urothelial carcinoma. All samples were FFPE tumor samples. Raw probe count data (.RCC files) were generated from nCounter Digital Analyzer (4.0.0.3).
Project description:Characterization of ~68 cell lines derived from human sarcoma and 5 normal counterpart cells, including drug sensitivity testing, gene expression profiling and microRNA expression profiling have been completed. Data and tools for searching these data will be made publicly available through the NCI Developmental Therapeutics Program. The raw data (RCC files) are provided through the GEO website. Sarcoma represents a variety of cancers at arise from cells of mesenchymal origin and have seen limited treatment advances in the last decade. Drug sensitivity data coupled with the transcription and microRNA profiles of a cohort of sarcoma cell lines may help define novel treatment paradigms. For each cell line, microRNA expression was measured on nCounter miRNA Expression Arrays (Nanostring Technologies), providing multiplexed, digital detection and counting of 800 human microRNA's. Please note that there are 2 replicates included in the study: A-204-rep1 and A-204-rep2, ES-4-rep1 and ES-4-rep2 resulting total 77 samples.
Project description:Dataset contains RCC files, normalized mRNA values in the heart, vastus, and skeletal muscles of WT and KO MC4R-/- mice fed a chow or western diet for 8 weeks
Project description:Renal cell carcinoma (RCC) with sarcomatoid transformation features a biphasic tumour with both sarcomatoid and carcinomatous components. Clear cell RCC (ccRCC) is the most common RCC subtype, frequently exhibits sarcomatoid transformation. The pathogenesis of sarcomatoid ccRCC remains unclear. This study aimed to identify the genes and pathways involved in sarcomatoid ccRCC using gene expression profiling. We analysed three distinct regions including sarcomatoid component, clear cell component and matched normal kidney tissue from formalin-fixed, paraffin-embedded (FFPE) tissue samples of four patients. RNA was extracted and gene expression profiles were analysed using the NanoString nCounter® PanCancer Pathways Panel on the NanoString nCounter® Analysis System. Data analysis was performed using NanoString nSolver™ Analysis Software. Significant gene expression differences were defined with a threshold of fold change ˃ 4 and P-value ˂ 0.05. Compared to normal kidney tissue, 17 genes were significantly different in the clear cell component, with 5 were upregulated and 12 downregulated. The most significantly upregulated and downregulated genes were GDF6 and SFRP1 respectively. In the sarcomatoid component, 85 genes showed differences, with 38 upregulated and 47 downregulated. COL11A1 and LRP2 were the most significantly overexpressed and underexpressed genes respectively. When comparing sarcomatoid component with clear cell component, there were 53 significantly dysregulated genes, including epithelial-mesenchymal transition markers such as MMP9 and FN1. Pathway analysis indicated that PI3K was the most frequently deregulated pathway in the sarcomatoid component, suggesting its role in sarcomatoid transformation. This study provides insights into the gene expression patterns in ccRCC with sarcomatoid transformation.
Project description:We report the immediate effects of estrogen signaling on the transcriptome of breast cancer cells using Global Run-On and sequencing (GRO-seq). We found that estrogen signaling directly regulates a strikingly large fraction of the transcriptome in a rapid, robust, and unexpectedly transient manner. In addition to protein-coding genes, estrogen regulates the distribution and activity of all three RNA polymerases, and virtually every class of non-coding RNA that has been described to date. This data submission covers >95% of mapped reads comprising nearly all transcript classes described. Reads mapping to intergenic and enhancer transcripts were removed from this data submission and will be reported separately (manuscripts in preparation). Bed files are tab-separated text files in which columns represent: chrom, chromStart (5' End of the read), chromEnd (chromStart+1), name (unused always 'n'), score (the number of mismatches), and strand. Note that because of the inclusion of reads mapping to the rRNA chromosome, bed files cannot be uploaded to the UCSC genome browser directly. Instead, use the wiggle files (coming soon!) for this purpose.
