11936 results for "cancer rna-seq"

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• Genomic and Genetic Characterization of Prostate Tumors Treated with Neoadjuvant Intense Androgen Deprivation Therapy

  The purpose of this study was to develop better ways of detecting prostate cancer before and after pre-operative treatment, and to test the feasibility of multi parametric magnetic resonance imaging (mpMRI) for the localization and detection of focal prostate cancer both before and after pre-operative treatment with ADT and enzalutamide. In this study, patients with intermediate and high risk prostate cancer received six months of neoadjuvant intense androgen deprivation therapy prior to radical prostatectomy. Biopsies were acquired prior to treatment. Tissue from biopsy and radical prostatectomy were subjected to sequencing and analysis for determination of features associated with response or resistance to treatment.

  Study phs001938

• Integrative Analysis of Lung Adenocarcinoma in EAGLE (Version 2)

  We performed a comprehensive analysis of intratumor heterogeneity of somatic mutations in cancer driver genes, copy number aberrations and DNA methylation in 292 tumor samples from 84 lung adenocarcinoma (LUAD) patients from the Environment And Genetics in Lung cancer Etiology (EAGLE) study. SNVs of 37 established lung cancer driver genes were profiled by deep target sequencing in 180 tumor samples and 55 blood samples and 1 buccal sample from 56 subjects. Somatic copy number alterations were profiled using SNP arrays in 268 tumor samples from 80 subjects. DNA methylation levels were profiled with methylation arrays in 205 tumor samples and 74 normal tissue samples from 68 subjects.

  Study phs001169

• The EGA joins EUCAIM, the European project powering AI and imaging in cancer research

  EUCAIM (EUropean Federation for CAncer IMages) is the cornerstone of the European Cancer Imaging Initiative, one of the flagships of the Europe’s Beating Cancer Plan (EBCP). The European Genome-Phenome Archive (EGA), as member of the EUCAIM consortium, attended the kick-off meeting organized this week in Brussels for the launch of the Initiative. The EGA will contribute to the project with the experience gained in the deployment of our federated network, the Federated EGA (FEGA), and the experience gained as partners of EuCanImage (AI4HI initiative) contributing to the definition of common data models, ontologies and data standards. The ultimate goal of the project is to unlock the power of imaging and Artificial Intelligence for the benefit of cancer patients, clinicians and researchers. The consortium will deploy a pan-European digital federated infrastructure hosting cancer-related images, and associated pathology, molecular and laboratory data from Real-World. This endeavour will provide a comprehensive dashboard for imaging data discovery, federated search, metadata harvesting, annotation and distributed data processing. EUCAIM joins 76 partners, gathering the experience and previous effort made by the different repositories of the AI4HI initiative, European Research Infrastructures and national/regional repositories. Find out more information about the EUCAIM launch here

  Blog the-ega-joins-eucaim

• MutWP5__CRUK_Mutographs_of_Cancer__Lung__PD43291_Novaseq__WG_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from lung tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will deeply sample from individuals with smoking-related lung diseases (COPD, pulmonary fibrosis, lung cancer) and those without smoking history. This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003502

• 2014_Lung_sq_WES

  Purpose Lung squamous cell carcinoma (SqCC) is the second most prevalent type of lung cancer. Currently, no targeted-therapeutics are approved for treatment of this cancer, largely due to lack of systematic understanding of the molecular parthenogenesis of the disease. To identify therapeutic targets and comparatively analyze them in lung SqCC, we probed somatic alterations of Korean lung SqCC. Patients and Methods We performed massively parallel whole-exome sequencing of 104 Korean lung SqCC patients’ samples with matched normal samples. In addition, copy number analysis and transcriptome analysis were conducted for a subset of these samples. Clinical association with cancer-specific somatic alterations was investigated.

  Study EGAS00001002844

• PARADIGM: Combined ctDNA and serum PSA for dynamic monitoring of metastatic prostate cancer starting first-line treatment

  The prognosis of newly-diagnosed metastatic prostate cancer is highly variable. The PARADIGM prospective cohort study evaluated predictors of survival in blood collected at the start of each of the first six treatment cycles from 114 high-volume metastatic patients starting androgen deprivation therapy combined with docetaxel or an androgen receptor pathway inhibitor.

  Study EGAS50000001357

• Shallow whole genome sequencing of ctDNA samples from DETECT study

  A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival from the paper "A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival", by Beddowes et al. Mol.Onc.

  Study EGAS50000000911

• Cancer_Genome_Libraries_Tests

  Testing library production.Genomic libraries (500 bps) will be generated from total genomic DNA derived from commomon epithelial cancer samples and subjected to paired end sequencing on the llumina plateforms. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Study EGAS00001000208

• High intensity sequencing of plasma cfDNA and WBC gDNA

  We sought to define the technical feasibility of a high-intensity sequencing assay of cfDNA and matched white-blood cell (WBC) DNA covering a large genomic region (508 genes, 2Mb, 60,000x raw-depth) in a prospective study of 124 metastatic cancer patients, with contemporaneous matched metastatic tumor tissue biopsies, and age-matched 47 non-cancer controls.

  Study EGAS00001003755

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

  Sample cohort (n=48) is consisted of healthy, atrophic gastritis and gastric cancer patients. Some of the gastric cancer patients samples are collected at the separate time points: -1 before the operation; -2 after the operation; -3 during the control visit. For the hybridisation capture of the genes unique 15 gastric cancer-related gene panel was developed and very deep sequencing using TruSight Oncology Unique Molecular Identifier (UMI) Reagents (Illumina) was used.

  Dataset EGAD00001011153

• Primary Lung Cancer whole genome study

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from lung cancer patients and subjected to short paired end sequencing on the llumina platform. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Dataset EGAD00001000388

• Comprehensive genomic characterization of early stage bladder cancer - whole exome sequencing data

  For this project about non-muscle invasive bladder cancer (NMIBC), we analysed WES data from 438 patients. The dataset is composed of 876 BAM files: 438 tumor samples and 438 paired blood samples.

  Study EGAS50000000511

• Exome Recapture and Sequencing of Prospectively Characterized Clinical Specimens From Cancer Patients

  The study cohort comprises samples from patients whose tumors have been prospectively characterized as part of their care at Memorial Sloan Kettering Cancer Center. This includes a variety of distinct tumor type and molecular subtypes.

  Study phs001783

• The dataset for Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer

  The dataset for “Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer” includes 496 cram files from whole genome next-generation sequencing on the Illumina NovaSeq 6000. The samples analyzed include tumor tissue, matched buffy coat and longitudinal plasma samples from individuals with pancreatic cancer.

  Dataset EGAD50000001353

• Tumor gene project

  The study focuses on human tumor susceptibility as well as somatic cancer genomics. We use high-throughput sequencing approaches to achieve a comprehensive molecular characterization of tumors. Our goal is to better understand their genesis and management opportunities.

  Study EGAS50000000984