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• Integrated clinical, whole genome, and transcriptome analysis of multisampled lethal metastatic prostate cancer

  We report the first combined analysis of whole genome sequence, detailed clinical history, and transcriptome sequence of multiple prostate cancer metastases in a single patient (A21). Whole genome and transcriptome sequence was obtained from 9 anatomically separate metastases, and targeted DNA sequencing was performed in cancerous and noncancerous foci within the primary tumor specimen removed 5 years prior to death. Transcriptome analysis revealed increased expression of AR-regulated genes in liver metastases that harbored an AR p.L702H mutation, suggesting a dominant effect by the mutation despite being present in only 1 of an estimated 16 copies per cell. The metastases harbored several alterations to the PI3K/AKT pathway, including a clonal truncal mutation in PIK3CG and present in all metastatic sites studied. The list of truncal genomic alterations shared by all metastases included homozygous deletion of TP53, hemizygous deletion of RB1 and CHD1, and amplification of FGFR1. If the patient were treated today given this knowledge, use of second-generation androgen-directed therapies, cessation of glucocorticoid administration, and therapeutic inhibition of the PI3K/AKT pathway or FGFR1 receptor could provide personalized benefit. Three previously unreported truncal clonal missense mutations (ABCC4 p.R891L, ALDH9A1 p.W89R, and ASNA1 p.P75R) were expressed at the RNA level and assessed as druggable. The truncal status of mutations is critical for actionability, and can only be determined through analysis of multiple sites of metastasis. Our findings suggest that a large set of deeply analyzed cases could serve as powerful guide to more effective prostate cancer basic science and personalized cancer medicine clinical trials.

  Dataset EGAD00001001869

• Y90 radioembolization followed by intravenous Nivolumab for advanced hepatocellular carcinoma

  To evaluate the efficacy of combination therapy with ICI and RT in patients, a Phase II trial (CA209-678) was conducted to investigate the efficacy and safety of Y90-RE followed by nivolumab in patients with advanced HCC (NCT03033446, n = 36). Interestingly, the ORR was found to be 30.6% in all patients and 43.5% when restricted to patients with only intrahepatic tumors, suggesting possible synergism between Y90-RE and ICI. Here we present whole exome sequencing (WES) and RNA-seq data for 33 patients treated with Y90 radioembolization followed with Nivolumab.

  Study EGAS00001006834

• Suspected Lynch syndrome dataset

  This dataset comprises a genomic and a phenotypic excel sheet displaying 137 cases classified as suspected Lynch syndrome. Included are genotypic data such as tumour mutational burden, tumour mutational signatures and germline/somatic variant calls for each colorectal, endometrial or sebaceous skin tumour screened. Genomic data is derived from targeted multigene panel sequencing including ~300 hereditary cancer genes.

  Dataset EGAD50000000031

• SNP Array data for: Three-dimensional patient-derived models of glioblastoma retain intra-tumoral heterogeneity

  4 sets of matched patient-derived-organoids (PDOs),  -neurospheres (PDNs), and parent glioblastoma tissue (12 samples total) underwent SNP array analysis. 200ng of each sample DNA extracted via a commercial kit (Qiagen) and loaded onto the Global Screening Array v2.0 array. Data is provided as raw red and green .idat files.

  Dataset EGAD00010002744

• single-cell RNA-Seq samples of CRC patients

  The dataset contains samples of 11 CRC patients (2 samples for each patient, tumor and normal adjacent tissue site, 22 samples in total). Dataset is composed by fastq file (paired end) type from 10x single-cell RNA-Seq.

  Dataset EGAD00001009634

• Profiling the Microbiome of Pediatric Gut with Metagenomic Short-Read Sequencing

  This dataset contains short-read metagenomic sequencing of stool, as well as intestinal tissue and tissue washes, from preterm infants. 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 EGAD00001016052

• Sequencing data for personalized therapy design and endotype identification

  Whole exome sequencing of 15 DNA samples, and whole genome sequencing of 2 matched DNA samples. Whole exome sequencing is of RMS samples (both alveolar and embryonal) and from cell lines as well as patient samples. Patient samples are of pediatric RMS patients.

  Dataset EGAD00001005458

• Vitamin-D-Kids Asthma

  The Vitamin D Kids Asthma Study (VDKA) was a 48-week multicenter randomized, double-blinded, placebo-controlled trial of vitamin D3 for severe asthma exacerbations in children 6-16 years old, recruited from February 28, 2016 to September 20, 2019. An ancillary study for nasal sampling was conducted at the Pittsburgh site. Prior to randomization, participants completed questionnaires and underwent collection of nasal samples for gene expression studies. VDKA was approved by the IRBs of all participating institutions, and the ancillary study was approved by the IRB of the University of Pittsburgh. Written parental consent was obtained for participating children, from whom written assent was also obtained.

  Study phs004051

• CTSP: Clinical Trial Sequencing Project

  For the Clinical Trials Sequencing Project (CTSP), National Cancer Institute (NCI) will utilize whole genome sequencing and/or whole exome sequencing in conjunction with transcriptome sequencing to try to identify recurrent genetic alterations (mutations, deletions, amplifications, rearrangements) and/or gene expression signatures that would be important to the hypothesis(es) submitted by the investigators. The samples will be processed and submitted for genomic characterization using pipelines and procedures established within The Cancer Genome Analysis (TCGA) project. Data analysis will be performed as a collaboration between the National Clinical Trials Network (NCTN) Group and its investigators submitting the proposal. The investigators at the NCI-sponsored Genomic Data Analysis Center (GDAC) will characterize the samples. The NCTN Group will be responsible for providing the clinical data needed for the proposal to the open clinical system maintained by NCI CCG's Biospecimen Core Resource (BCR) at Nationwide Children's Hospital in Columbus, Ohio. The project team (Network Group/investigators and GDAC) will analyze the data together. Additionally, clinical and genomic data related to the analyses will also need to be registered by NCI and will be made available to qualified researchers via a controlled-access database (e.g., dbGaP) upon publication of the primary analysis described in the study proposal. A substudy description and its molecular data information are provided under its own page: phs001184 CTSP Diffuse Large B-Cell Lymphoma (DLBCL) CALGB 50303

  Study phs001175

• The Pioneer 100 Wellness Project (P100)

  108 individuals (age 21-89+ years; 59% males, 41% females; 89% Caucasian; not recruited based on any specific phenotype) participated in an IRB-approved study from April 2014 to January 2015. Each individual had the genome sequenced in full. Blood was collected in clinics every three months. Additionally, participants completed at-home collections of saliva, stool, and first morning void urine every three months. Stool and saliva samples were shipped directly to the vendor by the participant, while urine was given back to the study coordinators for distribution to the proper sample vendor. For each successful participant in each round we carried out 218 clinical laboratory tests, measured up to 643 metabolites and 262 proteins, and measured the abundance of 4616 operational taxonomic units (OTUs) in the gut microbiome using 16S rRNA sequencing. The P100 study had four objectives: 1) Establish cost-efficient procedures for generating, storing and analyzing multiple sources of health data obtained over time from participants and analyzed in combination with genomic data; 2) Develop and deploy analytic tools for integrating these diverse datasets and deriving actionable information from their observed interrelationships; 3) Identify novel patterns within the streams of health data that indicate either wellness, or transitions between wellness and disease; 4) Learn how to best interface with and present longitudinal health information to individuals by studying the reactions and feedback from participants as they are presented actionable information.

  Study phs001363