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• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (normal data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010295

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (tumour data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010274

• Comprehensive Omics Analysis of Pediatric Solid Tumors and Establishment of a Repository for Related Biologic Studies (10C0086)

  This study (10-C-0086) collected and analyzed tumor and circulating tumor omics of pediatric and young adult patients with relapsed rhabdomyosarcoma who were co-enrolled in and receiving treatment on the interventional study 17-C-0049. We sought to describe the summary genomic findings of tumors, and report on the detection of circulating tumor DNA (ctDNA) in serial samples. Tumor tissue and blood were collected and analyzed. Tumor samples were subjected to whole exome and/or whole genome sequencing paired with RNA-Seq. Cell free DNA (cfDNA) was extracted from serially collected blood samples and sequenced. Fusion status, mutations, and IGF1R and YES1 expression from tumor samples revealed the presence of a PAX3 fusion in most samples, a number of common mutations, and universal but heterogeneous expression of IGF-1R and YES1. ctDNA was detected above the 3% threshold in a majority of patients and analysis of cfDNA demonstrated an ability to monitor tumor clonal evolution.

  Study phs003243

• DFCI Gynecological Oncology Data Access Committee

  This Data Access Committee is responsible for reviewing requests to access controlled human genomic data generated as part of the RESOLVE clinical trial at DFCI. The committee ensures that access complies with participant consent, institutional policies, and applicable data protection regulations (e.g., GDPR). Data access decisions are made by a multidisciplinary panel including clinical researchers, bioinformaticians, and data governance officers from Dana-Farber Cancer Institute. The committee reviews each access request to determine whether the proposed research aligns with the study’s consent terms and the data access policy. If approved, access is granted via the European Genome-phenome Archive (EGA) in accordance with EGA’s data use and security guidelines.

  Dac EGAC50000000712

• Gene expression analysis for nasal polyps

  The aim of the study is to identify the gene expression profile and biomarkers related with chronic rhinosinusitis with nasal polyps (CRSwNP). RNA-sequencing was performed to identify differentially expressed genes between nasal polyps (NP) and inferior turbinate mucosa from 6 patients with CRSwNP. We validated the RNA-seq results by quantitative real-time PCR.

  Study JGAS000153

• Identification of genetic mutations characteristic for recurrence and metastasis of colon and rectal cancer.

  We collected the cancerous tissues of the primary and recurrence tumors from the same patient with recurrent / metastatic colorectal cancer, and the purpose of this study is to find the characteristics of recurrent / metastatic colorectal cancers by carrying out a "molecular profiling", mainly the exome sequence analysis of these tissues.

  Study JGAS000091

• Whole exome sequencing of 49 tumor-blood pairs and transcriptome sequencing of 44 tumors for adrenocortical tumors

  Adrenal Cushing syndrome, which leads to type 2 diabetes, obesity and hypertension, is caused by ACTH-independent production of glucocorticoid by adrenocortical tumors. To investigate the genetic origins of cortisol-producing adrenocortical tumors, we performed whole exome sequencing of 49 tumor-blood pairs and transcriptome sequencing of 44 tumors

  Study EGAS00001000712

• RNA-seq of Liver Cancer

  The present series corresponds to 161 RNA-seq samples from tumors with matched WES or WGS. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Dataset EGAD00001003993

• Native American Ancient DNA sequencing

  The morphology of the first humans in the Americas (Paleoamericans) differs from that of Native Americans, and has raised the question of whether or not there are also differences in origin or genetics. A few populations who survived until relatively recently have been suggested to retain Paleoamerican morphology. One of these populations is from La Jolla. Here, we have generated genome sequence data from four La Jolla individuals in order to investigate these questions 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 EGAD00001002144

• The National Institute of Neurological Disorders and Stroke (NINDS) Human Genetics Resource Center: DNA and Cell Line Repository (the NINDS Repository): Motor Neuron/Amyotrophic Lateral Sclerosis (ALS) Study

  The National Institute of Neurological Disorders and Stroke (NINDS) Human Genetics Resource Center: DNA and Cell Line Repository (the NINDS Repository), banks phenotypic data and biological samples, including from individuals with motor neuron disease, in order to facilitate gene discovery in neurological disorders. Those samples are used in a number of studies, and genotyping data from studies using this resource are encouraged to be shared via dbGaP. Many studies have already shared data in this fashion, which in turn, can be linked back to the biologicals banked at the NINDS Repository. Motor Neuron Disease is characterized by selective degeneration of the motor neurons of the spinal cord, brainstem, or motor cortex. Clinical subtypes are distinguished by the major site of degeneration. In Amyotrophic Lateral Sclerosis (ALS), there is involvement of upper, lower, and brainstem motor neurons. In progressive muscular atrophy and related syndromes, the motor neurons in the spinal cord are primarily affected. With progressive bulbar palsy, the initial degeneration occurs in the brainstem. In primary lateral sclerosis, the cortical neurons are affected in isolation (Adams et al, Principles of Neurology, 6th ed, p 1089). The Motor Neuron Disease Collection of DNA and cell lines in the NINDS Repository is largely Amyotrophic Lateral Sclerosis cases (others include progressive muscular atrophy, primary lateral sclerosis, progressive bulbar palsy, Kennedy's disease). Amyotrophic lateral sclerosis (ALS) is the most common form of motor neuron disease (MND). Although ALS is the most common MND, it is still a relatively rare disease with an incidence of around 1.6 per 100,000 in the United States. It is currently incurable and treatment is largely limited to supportive care. Family history is associated with an increased risk of ALS, and many Mendelian causes have been discovered (including SOD1). However, most forms of the disease are not obviously familial. It is suspected that the sporadic forms of neurodegenerative disorders are caused by multiple genetic variants that individually make relatively weak contributions to risk. There is also an associated Control collection (see dbGaP and Coriell). Studies in motor Neuron Disease may use cases from the NINDS repository, controls from the NINDS repository, as well as cases, and controls, from other sources. A subset of subjects from The National Institute of Neurological Disorders and Stroke (NINDS) Human Genetics Resource Center: DNA and Cell Line Repository (the NINDS Repository): Motor Neuron/Amyotrophic Lateral Sclerosis (ALS) Study was utilized in the Genome-wide genotyping in amyotrophic lateral sclerosis and neurologically normal controls: first stage analysis and public release of data study. Note: The publication Chio et al., 2009 states that "Raw sample-level genotype data from the initial GWAS study ... are available for download through the dbGAP portal (phs000006.v1.p1)". Instead, please follow this link: phs000101.v1.p1.

  Study phs000006