14983 results for "cancer studies using rna-seq"

in 18.12 milliseconds.

• Genome and transcriptome sequence data from a colorectal adenocarcinoma patient (Response to Angiotensin Blockade with Irbesartan in a Patient with Metastatic Colorectal Cancer)

  Genome and transcriptome sequence data from a colorectal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study. These data are included in the manuscript entitled, "Response to Angiotensin Blockade with Irbesartan in a Patient with Metastatic Colorectal Cancer".

  Dataset EGAD00001001876

• Chordoma_Exome_Sequencing

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from Chordoma cancers and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Study EGAS00001000188

• sWGS on cfDNA and matching tumor DNA in pediatric cancer

  This dataset contains shallow whole genome sequencing data from paired cfDNA - tumor DNA samples of various pediatric cancer entities. Files are provided in fastq format. Samples were sequenced on an Ion Proton sequencer (Thermo Fisher Scientific) or a Hiseq3000 (Illumina). Data analysis is available at https://github.com/rmvpaeme/sWGS_pediatric_cancer.

  Study EGAS00001005198

• Breast_Cancer_Sequential_Sampling_Targeted_Capture

  This study aims to target capture sequence regions of interest from DNA derived from breast cancer patients who received neo-adjuvant chemotherapy. All patients had multiple biopsies performed before chemotherapy. Patients who had residual disease after the course of treatment underwent a further biopsy. We aim to characterise the mutations involved.

  Study EGAS00001000596

• The_life_history_of_colorectal_cancer_metastases_study_WGS_X10

  Whole genome sequencing of a series of metastasis collected from 2 patients at autopsy will be used to construct a life history of the cancer, including phylogenetic relationship between the different metastases an also whether there is evidence of convergence towards common biological processes that underpin the metastatic process but though different mutational events

  Study EGAS00001000864

• Meningioma_Exome

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from Meningioma tumour samples and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting exome libraries and mapped build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Study EGAS00001000177

• X10_sequencing_of_Oesophageal_Adenocarcinoma_Organoids

  X10 Sequencing of 5 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical resection of the tumour. All model derivations took place with the CGaP facility in Sanger. This PacBio data will be combined with other sequencing data in order to generate accurate reference cancer genomes.

  Study EGAS00001003264

• Genomic and transcriptomic landscape of aggressive thyroid cancer

  Molecular characteristics of anaplastic thyroid cancer (ATC) and advanced differentiated thyroid cancers (DTCs) have not been fully elucidated. In this study, we applied various types of massively-parallel sequencing technology to 113 advanced TCs, including 27 ATCs and 86 advanced DTCs, to reveal their genomic and transcriptomic characteristics.

  Study EGAS00001003540

• Oesophageal_Adenocarcinoma_Organoid_10x

  10x Sequencing of 6 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical rescetion of the tumour. All model derivations took place with the CGaP facility in Sanger. This 10x data will be combined with other sequencing data in order to generate accurate reference cancer genomes.

  Study EGAS00001003191

• Oesophageal_Adenocarcinoma_Organoid_PacBio

  PacBio Sequencing of 6 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical resection of the tumour. All model derivations took place with the CGaP facility in Sanger. This PacBio data will be combined with other sequencing data in order to generate accurate reference cancer genomes.

  Study EGAS00001007163

• Molecular Biomarkers Predicting Lung Cancer Response Phenotypes

  We have used a "chemistry first" approach to discover druggable acquired vulnerabilities that arised in the pathogenesis of non-small cell lung cancer (NSCLC). We screened chemical libraries (~200,000 compounds) for chemical toxins that killed subsets of NSCLC but not normal human lung epithelial cells (HBECs). We first screened a panel of 12 NSCLC lines that represented a variety of known oncogenotypes and identified chemicals with large Z scores and appropriate properties including re-supply, chemistry, and reproducible drug response phenotypes. This was then narrowed down to a list of 202 chemicals and 18 drugs with known targeting (henceforth called "Precision Oncology Probe Set", or POPS). These, and a panel of 30 clinically available drugs, targeted therapies, and drug combinations, already in use or in trials for NSCLC treatment, were then tested on a panel of 96 NSCLC lines for their drug response phenotypes in 12-point dose response curves. This information was analyzed using scanning ranked KS (Kolmogorov-Smirnov) and elastic net biostatistics approaches to identify molecular biomarkers (mutations, mRNA expression, copy number variation, protein expression, and metabolomics) which could predict for sensitivity or resistance to a particular chemical toxin or treatment regimen. From this we have discovered that: our approach identifies already known molecular biomarker of drug sensitivities (e.g. EGFR mutations and EGFR TK inhibitors); many clinically available chemotherapy agents have molecular biomarkers predicting preclinical model drug responses; the POP set of chemical toxins provides novel drug response phenotype patterns in the large NSCLC panel different from those found with clinically available agents including a therapeutic window; many of the POP toxins only hit a small percentage (~5%) of the NSCLC panel but the POP set as a whole provides "coverage" of the entire NSCLC panel; there are simple, one or 2 component molecular biomarkers (mutations, mRNA expression) that predict responses to the different chemical toxins in the NSCLC panel; and that the molecular biomarkers provide some information on the targets and pathways involved in response to the chemical toxins. Thus, we have identified a group of chemical toxins with selectivity for subsets of NSCLC and associated tumor molecular biomarkers to facilitate their development for precision medicine, and also, in some cases, information on the targets and pathways interdicted by these chemical compounds. In addition, we have discovered NSCLC predictive biomarkers for clinically available agents.

  Study phs001823

• Combination therapies for personalized cancer medicine

  It is the ambition of the team formed by members of the Netherlands Cancer Institute (NKI) and the Cancer Genome Project at the Wellcome Trust Sanger Institute (WTSI) to unravel the genomic and phenotypic complexity of human cancers in order to identify optimal drug combinations for personalized cancer therapy. Our integrated approach will entail (i) deep sequencing of human tumours and cognate mouse tumours; (ii) drug screens in a 1000+ fully characterized tumour cell line panel; (iii) high-throughput in vitro and in vivo shRNA and cDNA drug resistance and enhancement screens; (iv) computational analysis of the acquired data, leading to significant response predictions; (v) rigorous validation of these predictions in genetically engineered mouse models and patient-derived xenografts. This integrated effort is expected to yield a number of combination therapies and companion-diagnostics biomarkers that will be further explored in our existing clinical trial networks.

  Dataset EGAD00001000869

• APOLLO-OV: Applied Proteogenomics of High Grade Serous Ovarian Carcinoma

  APOLLO is a proteogenomic study seeking to describe the major genome, transcriptome, proteome and phosphoproteome alterations, subtypes, and molecular predictors of patient outcomes. This study includes 70 high grade serous ovarian carcinoma tissues from the Gynecologic Cancer Center of Excellence (https://medschool.usuhs.edu/gso/research/gyn-cancer-center-of-excellence). Bulk and laser microdissection enriched tumor tissues were profiled by whole genome sequencing, transcriptome sequencing, MS-based proteomics and reverse phase protein arrays. Clinical and sample data include survival times, patient features, and tumor characteristics.

  Study phs003488

• Tumor-associated neutrophil 1 precursors impair homologous DNA repair and promote sensitivity to PARP-inhibition

  Tumor evolution is one of the major mechanisms responsible for acquiring therapy resistant and more aggressive cancer clones. Whether the tumor microenvironment through immune-mediated mechanisms might promote the development of more aggressive cancer types is crucial for the identification of additional therapeutical opportunities. Here, we identify a subset of tumor-associated neutrophils, defined as tumor-associated neutrophil precursors (PreNeu). These PreNeu are enriched in highly proliferative hormone-dependent breast cancers and impair DNA repair capacity

  Study EGAS00001008154

• Integrated Methylation and Copy Number Analysis for Non-invasive Bladder Cancer Detection in Urine

  The molecular analysis of urine cell-free DNA (cfDNA) offers a non-invasive tool to advance bladder cancer (BC) management. Assessment of somatic copy number aberrations (SCNA) and DNA methylation, as singular or complementary analysis, have emerged as promising approaches for BC detection. Here, we developed an integrated analysis to assess both SCNA and targeted methylation changes from the same template molecules, named the iSECURE (integrated SEquencing-based Copy number and methylation analysis in URinE) method.

  Study EGAS50000001350

• A 3D genome atlas of breast cancer progression (BRCA3D)

  In this study, we aimed to understand how the 3D genome changes during breast cancer development and progression, in situ. Towards this goal, we collected cells from patient biopsies and performed Hi-C on four types of biopsies representing different stages of disease progression: healthy mammary tissue, primary breast tumours, liver metastasis and malignant pleural effusions. We survey the changes in the 3D genomes at the level of structural variation, compartments and TADs, as well as ERα associated distal interactions.

  Study EGAS50000000444