14977 results for "cancer studies using rna-seq"

in 14.57 milliseconds.

• RNA sequencing and Illumina 2.5M SNP array data collected from 675 commonly used human cancer cell lines.

  Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic response1. Although substantial effort has been directed to defining the genomic constitution of cancer cell line panels2–4, the transcriptome – which represents the active program of a cell – remains understudied. Here, we describe RNA sequencing and SNP array analysis of 675 commonly used human cancer cell lines. We explore numerous transcriptome features including coding and non-coding gene expression, transcribed mutations, gene fusion and expression of non-human sequences. Aside from many known aberrations we find new surprising characteristics, including more than 2200 unique fusion gene pairs representing a vast, testable repertoire of oncogenic fusions, many of which have analogs found in primary human tumors. We show that a combination of multiple genome and transcriptome features in a novel pathway-based approach enhances prediction of response to various targeted therapeutics. Our results provide valuable new insights into these critical pre-clinical models and provide added context for interpreting the numerous studies that employ these widely used cell lines.

  Study EGAS00001000610

• Pooled Single-Cell RNA-Seq of iPSC-Derived Neural Stem Cells from ADHD and Control Individuals

  This dataset contains FASTQ files from pooled single-cell RNA sequencing (scRNA-seq) of neural stem cells (NSCs) derived from induced pluripotent stem cells (iPSCs). The iPSCs were reprogrammed using the non-integrative Sendai virus system (CytoTune-iPS 2.0), introducing OCT3/4, SOX2, KLF4, and cMYC. Donor somatic cells included keratinocytes, PBMCs, and lymphoblastoid cell lines from individuals with ADHD and age-matched healthy controls (6–18 years). iPSCs underwent standard quality control, including immunocytochemistry, qRT-PCR, mycoplasma testing, and SNP genotyping. NSCs were produced via neural induction and validated by qRT-PCR and immunostaining for PAX6, SOX2, NESTIN, TUJ1, and FOXG1. Sequencing was performed on the Illumina NovaSeq 6000.

  Dataset EGAD00001015644

• Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

  Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

  Study EGAS00001003973

• Molecular Subtype-specific Biomarkers Improves Colorectal Cancer Prognostication

  Colorectal cancer (CRC) is characterized by major inter-tumor diversity that complicates the prediction of disease and treatment outcomes. Recent efforts help resolve this by sub-classification of CRC according to natural molecular subtypes, however, this strategy is not yet able to provide clinicians with improved tools for decision-making. We here present an extended framework for CRC stratification that specifically aims to improve patient prognostication. Using transcriptional profiles from 1,100 CRCs, including a novel set of >300 samples, we identify novel cancer cell and tumor archetypes and suggest the tumor microenvironment as a major prognostic determinant that can be influenced by the microbiome. Notably, our subtyping strategy allowed identification of novel archetype-specific prognostic biomarkers that provided information beyond and independent of UICC-TNM staging, MSI-status and consensus molecular subtyping. The results illustrate that our extended subtyping framework, combining subtyping and subtype-specific biomarkers, could contribute to improved patient prognostication and may form a strong basis for future studies.

  Study EGAS00001002376

• RNA-seq analysis of human peri-implantitis samples

  Bulk RNA-seq analysis of human biopsy material collected from implant sites with peri-implantitis.

  Study EGAS50000000369

• FASTQ files of total RNA-Seq data of POPS control samples

  Placental biopsies (n = 64 female placentas, n = 67 male placentas) were selected from healthy pregnancies from the POPs cohort. These patients had no evidence of hypertension at booking and during pregnancy, did not experience pre-eclampsia, Hemolysis, Elevated Liver enzymes, and Low Platelets (HELLP) syndrome, gestational diabetes, or diabetes mellitus type I or type II and other obstetric complications. They delivered live babies with a birth weight percentile in the normal range (20-80th percentile), with no evidence of slowing in fetal growth trajectory. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

  Dataset EGAD00001003457

• Dataset for Ewing_sarcoma_PNET-RNA

  Rare cancer sequencing data of 28 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008845

• Single-cell RNA sequencing of breast cancer lung metastasis and adjacent normal tissue

  This dataset contains single-cell RNA sequencing data from two samples: L1 (breast cancer metastasis to lung) and N3 (adjacent normal lung tissue) from a female patient. The samples were processed using 10X Chromium 3' technology and sequenced on Illumina NextSeq 500. This data supports the study "Endocrine therapy reprogramming of breast cancer facilitates metastatic escape via upregulation of P-Rex1/Rac1 signalling" which investigates how endocrine therapy reprograms breast cancer cells, leading to upregulation of P-Rex1/Rac1 signalling pathways that facilitate metastatic escape. The single-cell analysis reveals cellular reprogramming mechanisms in endocrine therapy-resistant breast cancer cells that form metastases in the lung.

  Dataset EGAD00001015769

• Sequencing data of the ampulla and fimbriae of the fallopian tube in pre-menopausal women

  A total of 10 pre-menopausal patients were recruited for this study. Sequencing of both the fimbriae and ampullary region of the fallopian tubes was performed using 10x Genomics single-cell RNA-seq and ATAC-seq. For one patient, data were sequenced across 4 lanes, while the remaining patients' data were sequenced in 2 lanes each, resulting in a total of 44 sequencing datasets for each platform.

  Dataset EGAD50000000889

• RIP-SeqRaw data

  This dataset contains 15 paired FASTQ files from the PTBP1 project. Sequencing data were generated using bulk directional RNA-seq and RIP-seq experiments performed on a NovaSeq 6000 platform (2×100 bp paired-end reads). The dataset comprises two groups of samples: controls and patients. For each group, both input and immunoprecipitated samples are available. Patient samples correspond to skin biopsies from individuals affected by a neurodevelopmental disorder associated with variable skeletal dysplasia and disproportionate short-limbed short stature.

  Dataset EGAD50000001723

• scRNA-seq of a 3D human cortical tissue model from human iPSCs exploring 2D versus 3D co-culturing

  Single-cell RNA-seq analysis of human iPSC-derived microglia/astrocytes/neurons in a novel, human in vitro 3D cortical tissue model, as well as 2D co-cultures for comparison. Samples include distinct conditions as described in the Study section. The dataset was generated using the BD Rhapsody technology and sequenced paired-end with Illumina NovaSeq2000. Information on the multiplexing of samples is reported in the Analyses section.

  Dataset EGAD50000002021

• mRNA-Seq on single human MII oocytes collected from gonadotropin stimulated women

  This dataset contains 11 paired-end FASTQ sequences from mRNA-Seq on single human M-II stage oocytes that were collected from gonadotropin stimulated women undergoing fertility treatments. M-II stage oocytes were collected and flash frozen prior to lysis followed by RNA extraction, full length cDNA preparation and amplification using the Ultra-low-input SMART-Seq2 v4 kit from Takara Clonetech. Further, these cDNA were used to prepare libraries for sequencing according the Nextera XT DNA library preparation kit from Illumina.

  Dataset EGAD00001006863

• Assessment of RNA-Seq Sample Preparation Methodology

  The goal of this study was two-fold, to determine if common purification techniques have any effect on downstream differential expression analysis and to evaluate combinations of alignment and differential expression software for reliability. To this end, blood was collected from three individuals and pooled during and after extraction. After pooling and mixing was completed, samples were divided into three aliquots for testing. The first aliquot was a control and not purified or concentrated. It was diluted to produce samples of varying concentrations for testing. The second aliquot was diluted to 20 ng/μL and used to test six different variations on the AMPure XP bead purification procedure. The last aliquot was also diluted to varying concentrations of 60, 30, and 9.6 ng/μL and purified using MinElute columns. Samples were submitted for total RNA-Seq library preparation and sequencing. Library preparation was performed using the TruSeq Stranded Total RNA with Ribo-Zero Globin kit (20020612, Illumina Inc.), and 2x150 bp PE sequencing was done on an Illumina NovaSeq 6000 with the S4 reagent kit. Comparisons were made between methods (AMPure vs. unpurified, AMPure vs. MinElute, MinElute vs. unpurified) to assess the effects of purification method on downstream differential expression. Comparisons were also made within methods using the varying concentrations tested for unpurified samples and for MinElute purified samples to assess the effects of concentration on differential expression. Variations of the AMPure procedure were also compared to assess the effectiveness of the variations tested in comparison to the unmodified procedure. A subset of samples was selected for use with alignment and differential expression package comparison. Unpurified high concentration samples eluted in RNAse-free water were compared to unpurified high concentration samples eluted in BR5, a buffer from the PAXgene blood miRNA kit, with the expectation that there should be no or very few differentially expressed genes. Unpurified high concentration samples eluted in RNAse-free water were also compared to unpurified low concentration samples also eluted in RNAse-free water, with possibly a small number of differentially expressed genes anticipated. A third dataset of simulated RNA-seq data was created with a known rate of differential expression. These files were aligned using Bowtie2, HISAT2, kallisto, RSEM, Rsubread, Salmon, and STAR. Results were then analyzed for differential expression using ALDEx2, baySeq, DEGseq, DESeq2, edgeR, limma, NOISeq, PoissonSeq, and SAMseq. Differential expression results of all three comparisons were evaluated to determine which combinations provided the most reliable results for both real and simulated data.

  Study phs003001

• Genomic and Transcriptomic Profiling of Patients with Malignant Pleural and Peritoneal Mesothelioma: The NCI Cohort

  Malignant mesothelioma is an aggressive cancer with limited treatment options and poor prognosis. Better understanding of mesothelioma genomics and transcriptomics could advance novel therapies. We performed whole-exome sequencing (WXS) of germline and tumors of 122 patients, and RNA-sequencing (RNA-Seq) of tumor samples of 100 patients with pleural, peritoneal, and tunica-vaginalis mesothelioma.The biospecimens used in this study were collected as a part of the Mesothelioma Natural History Protocol (https://clinicaltrials.gov/ct2/show/NCT01950572), wherein, samples were collected from subjects with malignant mesothelioma as listed in the eligibility criteria below and written consent from each participant was obtained before sample acquisition.

  Study phs002207

• Non-coding mutations reveal cancer driver cistromes in luminal breast cancer

  A dataset of ER+PR+ breast tumor samples that were analyzed in order to identify mutation enrichment in cis-regulatory elements and cistrome. The repository includes sequencing data from 88 patients. 26/88 were sequenced using ATAC-seq

  Dataset EGAD00001007650

• BMP4 and temozolomide synergize in the majority of patient derived glioblastoma cultures

  The poor prognosis of patients with glioblastoma is partly due to resistance to standard treatment, which combines chemoradiation using temozolomide (TMZ). The concept of cancer stem cells provided new insight into tumor resistance and management, and isolated Glioblastoma stem-like cells (GSCs) which contribute to this therapy resistance. Bone morphogenetic protein 4 (BMP4) is a differentiation factor that stimulates astroglial differentiation of such GSCs, thereby reducing their self-renewal. Exposing GSCs to BMP4 could therefore sensitize them to chemotherapy with TMZ, but previous studies with various treatment paradigms have produced contradictory results in this matter. Therefore, we re-defined the optimal treatment paradigm for the combination of TMZ and BMP4 and subsequently re-assessed the inter-tumoral variability in response to co-treatment with TMZ+BMP4 in vitro. First, the simultaneous treatment was found more effective than sequential therapy. Second, after application of our optimized treatment protocol, 70% of a total of 20 patient-derived glioblastoma cultures showed synergy when the treatments were combined. The synergistic effect was a result of increased cellular apoptosis and not of decreased proliferation. Comparative RNA-sequencing suggested that combination treatment results in decreased MAPK signaling. We conclude that addition of BMP4 to standard therapy with TMZ could enlarge the group of patients with good therapeutic response.

  Study EGAS00001007095