12074 results for "cancer rna-seq"

in 47.26 milliseconds.

• Identification_of_drug_resistance_genes_in_cancer_cell_lines_by_insertional_mutagenesis

  Our aim is to identify genes involved in resistance to anti-cancer therapies. In order to do this we have taken advantage of a lentiviral vector (LV)-based insertional mutagen to mutagenize cancer cell lines. LV-transduced cell lines were then treated with anti-cancer therapies and the emergence of resistant clones scored. DNA from pools of resistant clones was collected, subjected to custom capture by baits designed against the LV sequence, and then sequenced to identify the LV-genomic junction. We hope that the identification of recurrently targeted genes in resistant cell population will allow us to identify genes that mediate drug resistance.

  Study EGAS00001001035

• Premalignant SOX2 overexpression in the fallopian tubes of ovarian cancer patients: Discovery and validation studies

  To identify early driver mutations in ovarian cancer cells, we used dense whole genome sequencing of micrometastases and microscopic residual disease collected at three time points from a single patient during treatment for high-grade serous ovarian cancer (HGSOC). Laser capture microdissection of tumour islets was performed on samples prior to chemotherapy, after three cycles of chemotherapy and at recurrence. Long frament read whole genome sequencing was performed and mutations were identified. To our knowledge, this is the first longitudinal study that attempts to investigate spatial and temporal micro-heterogeneity in cancer.

  Study EGAS00001001909

• Genomics_of_acral_lentiginous_melanoma___RNAseq

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico.

  Study EGAS00001003758

• Identification of hypermutation and defective mismatch repair in ctDNA from metastatic prostate cancer

  DNA mismatch repair defects (MMRd) and tumor hypermutation are rare and under-characterized in metastatic prostate cancer. Furthermore, since hypermutated MMRd prostate cancers can respond to immune checkpoint inhibitors, there is an urgent need for practical detection tools. We analyzed cell-free DNA targeted sequencing data from 434 metastatic prostate cancer patients with circulating tumor DNA (ctDNA) purity above 2%. Samples with somatic hypermutation were subjected to 150x whole exome sequencing. These data allowed us to interrogate the salient genomic properties of this rare prostate cancer subtype and correlate findings with patient clinical outcomes.

  Study EGAS00001003899

• A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity

  Abstract: Cancer cells display highly heterogeneous and plastic states in glioblastoma, an incurable brain tumour. However, how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generated a deep single cell and spatial multi-omic atlas of human glioblastoma that pairs transcriptomic, epigenomic and genomic profiling of 12 tumours across multiple regions. We identify that glioblastoma heterogeneity is driven by spatially-patterned transitions of cancer cells from developmental-like states towards those defined by a glial injury response and hypoxia. This cancer cell trajectory regionalizes tumours into distinct tissue niches and manifests in a conserved manner across tumours as well as genetically distinct tumour subclones. Moreover, using a new deep learning framework to jointly map cancer cell states and clones in situ, we show that tumour subclones are finely spatially intermixed through glioblastoma tissue niches. Finally, we show that this cancer cell trajectory is intimately linked to myeloid heterogeneity and unfolds across regionalised myeloid signalling environments. Our findings define a stereotyped trajectory of cancer cells in glioblastoma and unify glioblastoma tumour heterogeneity into a tractable cellular and tissue framework.

  Dataset EGAD00001015516

• Triple Negative Breast Cancer sequencing

  Triple Negative Breast Cancer sequencing

  Dataset EGAD00001000063

• Expression profiles and genetic makeup of metastases of a cancer of unknown primary.

  Study EGAS00001004059

• Concurrent germline and somatic pathogenic BAP1 variants in a patient with metastatic bladder cancer

  Study EGAS00001004055

• Characterization of stromal tumor-infiltrating lymphocytes and genomic alterations in metastatic lobular breast cancer

  Study EGAS00001004641

• NPY methylated ctDNA is a promising biomarker for treatment response monitoring in metastatic colorectal cancer

  Study EGAS00001006820

• Low-coverage whole-genome sequencing of cancer and healthy plasma circulating DNA

  Study EGAS00001007593

• Genomic profiling of subcutaneous patient derived xenograft models of solid childhood cancer

  Study EGAS00001006710

• DEREGULATION OF PRE-mRNA SPLICING IN MISMATCH REPAIR DEFICIENT COLORECTAL CANCER

  Study EGAS00001004863

• WGS of oesophagogastric cancer

  WGS of 12 oesophagogastric cancer samples WGS or 12 matched germline data.

  Dac EGAC50000000890

• Genome-wide sequencing of (cell-free) DNA from Nipple aspirate fluid of Breast cancer patients

  Study EGAS00001007214

• Cell-free DNA sequencing data of healthy control, atrophic gastritis, and gastric cancer patients’ blood

  Study EGAS00001007308

• Cancer Alliance WGS

  Whole genome sequencing for individualized cancer interpretation

  Dataset EGAD00001006233

• Clonal_haematopoiesis_in_patients_with_AAA

  Recent advances in genomics have demonstrated that clonal haemopoiesis driven by leukaemia associated somatic mutations is a relatively common phenomenon that increases in frequency with advancing age. Whilst individuals with clonal haemopoiesis have an increased risk of developing haematological malignancies, they also have an increased mortality from other causes. Additionally, certain mutations are almost exclusively seen in individuals aged 70 years or older, whilst others are seen in individuals with non-haematological cancers including breast and ovarian. Recently, clonal haemopoiesis was found to be associated with a significantly increased risk of atherosclerotic cardiovascular disease. This association is thought to be causative with clonally-derived macrophages showing elevated expression of several chemokine and cytokine genes that contribute to atherosclerosis. Another vascular pathology, abdominal aortic aneurysm (AAA), increases with age and shares risk factors with atherosclerosis (including smoking, male sex, high cholesterol). However, the impact of these risk factors and the overlap between AAA and atherosclerosis is poorly understood. To investigate a possible link between clonal haemopoiesis and AAA, we will study DNA samples from 300 patients with AAA and up to 200 controls for evidence of clonal haemopoiesis. This will be done using target DNA enrichment with biotinylated RNA baits followed by high throughput sequencing.

  Study EGAS00001002873

• RNAseq data of polyA+ RNA from Leukocytes from 624 individuals of the SardiNIA cohort.

  We sequenced the polyA+ of the RNA of the leukocytes from 624 sardinian individuals with RNAseq (Illumina 2000, an average of round 60M reads per sample, 51 + 51 nt). Combining the genotype information of the same individuals (already available from the ProgeNIA project) with the transcriptome data we identified 21,183 independent expression quantitative trait loci (eQTLs) and 6,768 independent splicing quantitative trait loci (sQTLs), including 619 novel QTLs that exhibit population-specific trait associations. Using family relationships, we identified 809 segregating expression outliers and provide a new approach to study large effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.

  Study EGAS00001002105

• RNA sequencing on intestinal biopsies from inflammatory bowel disease patients treated with vehicle control, MEK inhibitor, or infliximab

  By investigating an intergenic haplotype on chr21q22, independently linked to inflammatory bowel disease (IBD), ankylosing spondylitis, primary sclerosing cholangitis and Takayasu’s arteritis, we discover that the causal gene, ETS2, is a master regulator of inflammatory responses in human macrophages and delineate how the risk haplotype increases ETS2 expression. Using a database of cellular signatures, we identified drugs that could modulate this pathway. To validate the anti-inflammatory activity of one class of small molecules ex vivo, we obtained biopsies from patients with active IBD and cultured these biopsies with a selective, non-ATP competitive MEK inhibitor (PD-0325901), infliximab (positive control), or DMSO (vehicle control) for 18 hours, then performed RNA sequencing.

  Study EGAS00001007534

• minION fastq files of 10 different tumor samples from the Master program (H021)

  Nanopore RNA Sequencing was done for 10 tumor samples. Direct cDNA sequencing was performed using the SQK-DCS109 kit (Oxford Nanopore Technologies). For analysis of a single sample on a MinION flow cell (version R9.4.1), 5 μg RNA was used as input. For multiplexing on a MinION flow cell, 2.5 μg RNA per sample was used as input, and the native barcoding expansion kit EXP-NBD104 was employed in conjunction with SQK-DCS109. After reverse transcription with Maxima H Minus Reverse Transcriptase (Thermo Scientific), second-strand synthesis was performed using the 2x LongAmp Taq Master Mix (New England Biolabs). The resulting double-stranded cDNA was subjected to end-repair and dA-tailing using the NEBNext Ultra End Repair/dA-Tailing Module (New England Biolabs). For multiplexed libraries, this step was followed by barcode ligation and library pooling. Next, libraries were quantified with a Qubit Fluorometer 3.0 (Life Technologies). Finally, sequencing adapters were added to the library preparations and ligated with Blunt/TA Ligase Master Mix (New England Biolabs), followed by further quality control using a Qubit. Samples ACC1 and ACC2 were analyzed on individual MinION flow cells, while the remaining eight samples were sequenced as multiplexed libraries on two MinION flow cells by pooling four samples for each run. Five ACC samples were also analyzed individually on Flongle flow cells

  Dataset EGAD00001008970

• Using genetics to identify cell types and mechanisms underlying susceptibility to primary sclerosing cholangitis

  Primary sclerosing cholangitis (PSC) is a T-cell mediated, chronic inflammatory condition of the biliary tree that is strongly associated with inflammatory bowel disease. Genome-wide association studies have identified 22 non-HLA genetic risk variants associated PSC. Identifying the genes impacted by these variants has proven difficult as the majority lie in non-coding regions of the genome. Knowledge of the genes and biological pathways these non-coding variants are perturbing is vital to understanding the disease biology. One means of assessing the impact of non-coding variants within disease associated loci upon genes is via colocalisation with eQTL. Many eQTL are cell-type specific, requiring the analysis of disease relevant cell types to detect colocalisation. We have collected PSC-relevant T-cell-subtypes from the peripheral blood of PSC patients via fluorescence activated cell sorting in preparation for RNA sequencing and mapping of eQTL. Samples were collected at the Norfolk and Norwich University Hopital, for which local ethical approval has been granted. Lysed cell samples will be transferred to WTSI and DNA/RNA will be extracted from lysed cell samples by T143 before genotyping (DNA) and custom library preparation and sequencing (RNA). This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001011815

• SEER Remote Access Pilot Test Data (2018)

  This is a limited use Surveillance, Epidemiology, and End Results (SEER) file for use in a pilot test of remote data access. The SEER Program of the National Cancer Institute (NCI) is an authoritative source of information on cancer incidence and survival in the United States. SEER currently collects and publishes cancer incidence and survival data from population-based cancer registries covering approximately 34.6 percent of the U.S. population. The SEER Program registries routinely collect data on patient demographics, primary tumor site, tumor morphology and stage at diagnosis, first course of treatment, and follow-up for vital status. The mortality data reported by SEER are provided by the National Center for Health Statistics. The population data used in calculating cancer rates is obtained periodically from the Census Bureau. The SEER research data files include SEER incidence and population data associated by age, sex, race, year of diagnosis, and geographic areas.

  Study phs002012

• Cancer genome scanning in plasma: detection of tumor-associated copy number aberrations, single nucleotide variants and tumoral heterogeneity by massively parallel sequencing

  Tumor-derived DNA can be found in the plasma of cancer patients. We explored the use of shotgun massively parallel sequencing of plasma DNA obtained from cancer patients to scan a cancer genome noninvasively. We achieved the profiling of copy number aberrations and point mutations, in a genomewide manner using this approach. By measuring the genomewide aggregated allelic loss and point mutations, we determined the fractional tumor-derived DNA concentrations in plasma and correlated these values with tumor size and surgical treatment. We have also demonstrated the application of this approach to monitoring a complex oncologic scenario, in a patient with two synchronous cancers. In particular, through the use of multi-regional sequencing of tumoral tissues and shotgun sequencing of plasma DNA, we have shown that plasma DNA sequencing is a valuable approach for studying tumoral heterogeneity. Shotgun plasma DNA sequencing is thus a powerful tool for cancer monitoring and research.

  Study EGAS00001000370

• Molecular evolution and clinical trajectories of prostate cancer identifies novel markers for risk stratification - additional data

  Study EGAS00001004884