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• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95732A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 928 samples; filetype=bam

  Dataset EGAD00001004759

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95732B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 635 samples

  Dataset EGAD00001004760

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95736A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1072 samples

  Dataset EGAD00001004761

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96139A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1436 samples; filetype=bam

  Dataset EGAD00001004762

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96145A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 589 samples; filetype=bam

  Dataset EGAD00001004763

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96150A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 656 samples; filetype=bam

  Dataset EGAD00001004764

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96156A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 648 samples; filetype=bam

  Dataset EGAD00001004765

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96156B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 375 samples; filetype=bam

  Dataset EGAD00001004766

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96165A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 755 samples; filetype=bam

  Dataset EGAD00001004767

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96171A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 492 samples; filetype=bam

  Dataset EGAD00001004768

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires forlibrary A96176A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 531 samples; filetype=bam

  Dataset EGAD00001004769

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96187A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1222 samples; filetype=bam

  Dataset EGAD00001004770

• 59 CLPD-NK cases WGS & WTS data

  For the cohort of 59 samples, we performed TruSeq DNA PCR-Free whole-genome sequencing library preparation according to manufacturer’s instructions (llumina, ILMN, San Diego, CA) on the automated NGS Star liquid handling platform (Hamilton, Bonaduz, Switzerland) followed by 2x150 bp paired-end sequencing on the HiSeqX or NovaSeq6000 (ILMN). An average coverage of >100x was achieved. For whole transcriptome analysis, the TruSeq Total Stranded RNA kit was used, starting with 250 ng of total RNA, to generate RNA libraries following the manufacturer’s recommendations (ILMN). 2x100bp paired-end reads were sequenced on the NovaSeq 6000 with a median of 50 mio. reads per sample (ILMN).

  Dataset EGAD00001008558

• The 5-hydroxymethylcytosine Landscape of Prostate Cancer

  This dataset consists of genome-wide 5hmC methylomes at various stages of prostate cancer, including not only 93 metastases from castration-resistant prostate cancer (mCRPC) patients, but also 5hmC patterns in cell-free DNA (cfDNA). There are 2000 runs in total as fastq files.

  Dataset EGAD00001008462

• TB-DAR Whole Genome Sequencing Study

  116 Whole Genome Sequencing (WGS) samples from the TB-DAR study, based on a cohort of adult pulmonary tuberculosis patients recruited in Dar es Salaam, Tanzania. WGS was performed at the Health2030 Genome Center in Geneva on the Illumina NovaSeq 6000 instrument (Illumina Inc, San Diego CA, USA), starting from1μg of whole blood genomic DNA and using Illumina TruSeq DNA PCR-Free reagents for library preparation and the 150nt paired-end sequencing configuration. Average coverage was above 30X for 75 samples, between 10X and 30Xfor 40 samples, and approximately 8X for a single sample. Sequencing reads were aligned to the GRCh38 (GCA_000001405.15) reference genome using bwa (Version 0.7.17).

  Dataset EGAD00001008400

• Download Metadata

  Metadata Distribution Welcome to the realm of Metadata Distribution within the EGA ecosystem! Our Metadata REST API empowers you to effortlessly retrieve metadata from the expansive landscape of EGA. By utilising this API, you gain access to publicly available insights across various EGA domains, including studies, samples, experiments, runs, analyses, policies, DACs, and datasets. Furthermore, this API facilitates cross-referencing of objects, enabling you to gather, for example, all the datasets associated with a specific DAC, seamlessly. In addition, we have added the ability to query private data using the metadata API. If you possess the necessary permissions, you can access behind-the-login private data for a specified list of datasets. Metadata Distribution Index Identifiers Dataset Mappings Website Download Metadata API - Private Identifiers At the core of EGA's organisational structure are unique accessions that serve as essential tags for our diverse objects. Here's a quick overview of the accessions and their corresponding object types: EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID For further information check our metadata schema documentation. Dataset Mappings For authorised datasets, comprehensive mappings reveal meaningful connections: Sample_file: This file presents information about the linkage between samples and files available in the dataset. Study_experiment_run_sample: This file presents information about the linkage between studies, experiments, runs, and samples within the dataset. Study_analysis_sample: This file presents information about the linkage between studies, analyses, and samples contained within the dataset. Run_sample: This file presents information about the linkage between runs and samples within the dataset. Analysis_sample: This file presents information about the linkage between analyses and samples within the dataset. An empty file indicates the absence of corresponding information. Website Download Our website serves as your gateway to downloading metadata. Simply navigate to the dataset page, and you'll find a blue Metadata button. Once authenticated, you can click this button for authorised datasets. If you lack permissions for a particular dataset, request access by clicking the 'Request Access' button. For authorised datasets, choose your preferred metadata format: CSV, TSV, or JSON. Metadata API - Private Leverage the power of programmatic metadata downloads! Start by authenticating yourself with your credentials to obtain an access token. With this token, programmatically query private information. Queries mirror the structure of the Public Metadata API. However, behind the login, you can delve into specific mapping information (as mentioned above in dataset mappings) alongside object-level exploration. Authentication An active session is required to work with the API. Each time you log in with your credentials a new session is started, which is identified by an access_token. Below an example on how to obtain one using curl: curl https://idp.ega-archive.org/realms/EGA/protocol/openid-connect/token \ -d 'client_id=metadata-api' \ -d 'username=...' \ --data-urlencode 'password=...' \ -d 'grant_type=password' All responses from the API are in JSON format. A successful response should include a new token to be used for the session: {"access_token":"eyJhbGciOiJSUzI1NiIsInR5cCIgOiA...TNw", "expires_in":300, "refresh_expires_in":1800, "refresh_token":"eyJhbGciOiJIUzI1NiIsInR5cCIgOiA...pTX10", "token_type":"Bearer", ... } Save the access_token value and include it in the API call headers. Example query usage Below you can find some example of queries available behing authentication and authorisation. Querying study-experiment-run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_experiment_run_sample \ -H 'Authorization: Bearer access_token' Querying run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/run_sample \ -H 'Authorization: Bearer access_token' Querying study-analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_analysis_sample \ -H 'Authorization: Bearer access_token' Querying analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/analysis_sample \ -H 'Authorization: Bearer access_token' Querying sample-file mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/sample_file \ -H 'Authorization: Bearer access_token' You can get a different output format by adding one of these options to the curl command: -H 'Accept: text/tsv' -H 'Accept: application/json' -H 'Accept: text/csv' For more detailed information, refer to the Metadata API Specification.

  Documentation access/download/metadata

• Privacy Notice for EGA Web user

  Privacy Notice for EGA Public Website This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by Mallory Freeberg, by: email at: mfreeberg@ebi.ac.uk , or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org , or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? For providing you access to the website and for offering support whilst using the website, we need your consent under Article 5 (2) of the IP 68 (equivalent to Article 6 (1)(a) of the GDPR). For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: IP addressesDate and time of a visit to the service website Operating systemAmount of data transmittedBrowserEmail address (only when support is requested by the user) The data controller will use your personal data for the following purposes: To provide the user access to the serviceTo better understand the needs of the users and guide future improvements of the serviceTo monitor website activities according to and in compliance with the Terms of UseTo better understand the needs of the website visitors and guide future improvements of the serviceTo conduct and monitor website security activitiesTo create anonymous usage statistics 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? There are no personal data transfers to third countries or international organisations. 6. How long do we keep your personal data? Any personal data directly obtained from you will be retained as long as the service is live. Such duration serves the purpose of enabling scientific research and ensures legal compliance and facilitates internal and external audits if they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration.Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period.Request information to understand data processing activities when the results of these activities are applied to you.Object at any time to the processing of your personal data unless we can demonstrate that we have legitimate reasons to process your personal data.Request free of charge and without excessive delay rectification or erasure of your personal data if we have not been processing it respecting the data protection policies of the respective controllers. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. 9. CookiesWe use cookies and similar technologies that are strictly necessary for the correct functioning and security of the EGA website (for example, to enable core site features and to help protect the service). These cookies do not store information that directly identifies you.You can set your browser to block or delete cookies. Please note that if you disable strictly necessary cookies, parts of the website may not function properly.Published on February 6, 2019

  Documentation data-protection/privacy-notice/ega-website

• Whole Transcriptome Sequencing of Resectable Stage III/IV Melanoma Evaluated After Starting Hu14.18-IL2 Predicts Outcome

  Background: We analyzed whole transcriptome sequencing in tumors from 23 patients with stage III or IV melanoma from a pilot trial of the anti-GD2 immunocytokine, hu14.18-IL2, to identify predictive immune and/or tumor biomarkers in melanoma patients at high risk for recurrence. Methods: Patients were randomized to receive the first of 3 monthly-courses of hu14.18-IL2 immunotherapy either before (Group A) or after (Group B) complete surgical resection of all known disease. Tumors were evaluated by histology and whole transcriptome sequencing. Results: We report here that tumor infiltrating lymphocyte (TIL) levels directly associate with relapse-free survival (RFS) and overall survival (OS) in resected tumors from Group A, where early responses to the immunotherapy agent could be assessed. TIL levels directly associated with a previously reported immune signature which associated with RFS and OS, particularly in Group A tumors. In Group A tumors there were decreased cell cycling gene RNA transcripts, but increased RNA transcripts for repair and growth genes. We found that outcome (RFS and OS) was directly associated with several immune signatures and immune-related RNA transcripts and inversely associated with several tumor growth-associated transcripts, particularly in Group A tumors. Most of these associations were not seen in Group B tumors. Conclusion: We interpret these data to signify that both immunologic and tumoral cell processes, as measured by RNAseq analyses detected shortly after initiation of hu14.18-IL2 therapy are associated with long term survival and could potentially be used as prognostic biomarkers in tumor resection specimens obtained after initiating neoadjuvant immunotherapy. Note: RNA sequences and expression data can be found at NCBI GEO GSE133713

  Study phs001947

• Germ Cell Tumor Molecular Heterogeneity Revealed through Analysis of Primary and Metastasis Pairs

  Purpose: While primary germ cell tumors (GCTs) have been extensively characterized, molecular analysis of metastatic sites has been limited. We performed whole-exome sequencing and targeted next-generation sequencing on paired primary and metastatic GCT samples in a patient cohort enriched for cisplatin-resistant disease. Experimental Design: Tissue sequencing was performed on 100 tumor specimens from 50 patients with metastatic GCT, and sequencing of plasma cell-free DNA (cfDNA) was performed for a subset of patients. Data is being provided for a subset of 10 patients whose samples were analyzed using whole-exome sequencing. Results: The mutational landscape of primary and metastatic pairs from GCT patients was highly discordant (68% of all somatic mutations were discordant). Whereas genome duplication was common and highly concordant between primary and metastatic samples, only 25% of primary-metastasis pairs had =50% concordance at the level of DNA copy number alterations (CNAs). Evolutionary-based analyses revealed that most mutations arose after CNAs at the respective loci in both primary and metastatic samples, with oncogenic mutations enriched in the set of early occurring mutations versus variants of unknown significance (VUS). TP53 pathway alterations were identified in nine cisplatin-resistant cases and had the highest degree of concordance in primary and metastatic specimens, consistent with their association with this treatment-resistant phenotype. Conclusions: Analysis of paired primary and metastatic GCT specimens revealed significant molecular heterogeneity for both CNAs and somatic mutations. Among loci demonstrating serial genetic evolution, most somatic mutations arose after CNAs but oncogenic mutations were enriched in the set of early occurring mutations as compared to VUS. Alterations in TP53 were clonal when present and shared among primary-metastasis pairs. Reprinted from pending publication, with permission from JCO Precision Oncology.

  Study phs002229

• Genomic Analyses of Germline and Somatic Variation in High-Grade Serous Ovarian Cancer

  The goal of this study was to identify and characterize germline and somatic genetic variation in women with high grade serous ovarian cancers treated at a single cancer center and their associations with relapse-free and overall survival. We conducted paired tumor/normal targeted next-generation sequencing of 577 genes in pathways of DNA repair, response to DNA damage, cell-cycle regulation, programmed cell death, MAPK, and P13K/AKT/MTOR signaling in 114 tumors from 71 women. In addition, we investigated single copy number alterations (SCNAs) and loss of heterozygosity in a subset of 61 tumors. We validated our results with data from ovarian tumors in TCGA. Our results were similar to other studies of high-grade serous carcinomas. As an example, we found that approximately one third of the tumors harbored loss of function variants in homologous recombination genes and that >90% had TP53 somatic mutations. Through GISTIC analysis of the OncoScan data on tumor DNA from 61 cases, we identified several regions of high copy number alterations including including NOTCH3 and PIK3R2 that were significantly associated with an increase in cancer recurrence and a reduction in overall survival. We identified few changes in mutation profiles where we had multiple tissues, either from multiple surgeries or from the primary site to metastatic sites within the same surgery. However, we did not investigate copy number alterations in multiple tissues from the same individuals, and so it may be that copy number alterations are more important. Data available through dbGAP will be the BAM files and the phenotypic data on the tumor samples, the age, race, ethnicity of the participants and their outcomes, and the Oncoscan OSCHP files.

  Study phs003198

• Chromothripsis in Patient WHIM-09

  We are studying the natural history, pathogenesis and treatment of patients with WHIM syndrome, an immunodeficiency disorder characterized by warts, hypogammaglobulinemia, recurrent infections and neutropenia usually due to autosomal dominant gain-of-function mutations in chemokine receptor CXCR4. We have identified a patient born with WHIM syndrome and the WHIM mutation CXCR4R334X who has been disease-free for 20 years and who lacks CXCR4R334X in myeloid cells, the cells that drive disease manifestations. She is a genetic and hematopoietic mosaic, since she still has the mutation in lymphoid cells and non-hematopoietic cells. Cytogenetics and microarray analysis revealed that the mechanism of loss of the mutation was deletion of the mutant allele from one copy of chromosome 2. Whole genome sequencing of patient neutrophil and skin fibroblast genomic DNA revealed that the mechanism of deletion was chromothripsis, a process of chromosome shattering resulting in deletions and rearrangements of the non-deleted chromosomal segments. In the patient, this process evidently occurred in a single hematopoietic stem cell (HSC), resulting in deletion of the disease allele CXCR4R334X and one copy of 163 other genes on chromosome 2. This HSC evidently acquired a growth advantage and repopulated the HSC population and the myeloid lineage. Consistent with this, studies using gene targeted mice in competitive bone marrow transplantation experiments revealed that selective Cxcr4 haploinsufficiency (inactivation of one copy of Cxcr4 and not of any other genes) was sufficient to confer a strong engraftment advantage over bone marrow cells from wild type mice as well as bone marrow cells from a mouse model of WHIM syndrome. These results suggest that CXCR4 knockdown may be a useful strategy to enhance bone marrow engraftment in the absence of toxic bone marrow conditioning regimens.

  Study phs000856

• Genotyping NIGMS CEPH Samples from the United States, Venezuela, and France

  The Human Genetic Cell Repository (HGCR) is sponsored by the National Institute of General Medical Sciences (NIGMS) with the mission of supplying scientists with the materials for accelerating disease gene discovery and functional studies. The resources available include highly-characterized, contaminant-free fibroblast cell lines, transformed lymphoblastoid cell lines (LCLs), and DNA samples derived from these cultures. While the Repository has a major emphasis on inherited diseases, it also contains large collections of cell lines gathered from populations around the world that are intended for use in facilitating the understanding of human variation. Prominent among these resources is the CEPH Reference Family collection contributed by the Centre d'Etude du Polymorphisme Humain (CEPH), Foundation Jean Dausset, Paris, France. The CEPH collection includes families collected by R. White (Utah), J. Dausset (French), J. Gusella (Venezuelan), and J. Egeland (Amish). There are a total of 809 individuals accounting for 832 pedigree positions in the reference families. Family relationships for the 61 reference families were verified at Coriell and approved by CEPH. In an effort to enhance the value of this cell culture resource available from the Repository, the Coriell Genotyping and Microarray Center used the Affymetrix Genome-Wide Human SNP Array 6.0 platform to genotype 181 samples from the NIGMS HGCR CEPH collection. Included are thirteen families from the United States (Amish Pedigree 884 and Utah Pedigrees 1331, 1356, 1400, 1416, 1424, 1427, 1477, and 1582), France (Pedigrees 35 and 66), and Venezuela (Pedigrees 102 and 104). Twelve of the families consist of 3 generations and one family consists of 2 generations. Pedigree charts and sample descriptions are available on the Repository catalog website (see below).

  Study phs000268

• Breast Cancer in Blacks: Impact of Genomics, Healthcare Use and Lifestyle on Outcomes (BRIGHT)

  Young Black females bear a disproportionate burden of breast cancer (BC) mortality compared to White females and are underrepresented in clinical studies. It remains critical to understand factors that contribute to the high mortality from BC among young Black females in order to improve outcomes. The higher BC mortality rate among young Black females with breast cancer is partially attributed to the disproportionately higher proportions who develop the aggressive triple-negative breast cancer (TNBC). In addition to biologic factors, timely access to care, and lifestyle factors contribute to this disparity. Consequently, we sought to evaluate the interplay between biologic and non-biologic contributors to BC outcomes (i.e., BC disease-free survival (DFS)), and to better characterize the highly aggressive TNBC among young Black females based on distinct molecular subtypes. Ultimately, it is critical to assess both biologic and non-biologic factors to fully understand and address existing health disparities in this population. Through prior and subsequent recruitment of a population-based study of young Black females diagnosed with invasive breast cancer spanning 2009-2016, we: 1) assessed the contribution of biologic and non-biologic factors on BC-DFS observed among young Black females with BC, and 2) investigated molecular features of the subgroup with TNBC. Through this study, consented participants were asked to provide a saliva sample from which DNA was extracted for germline analyses, including germline inherited cancer genetic testing and Infinium Expanded Multi-Ethnic Genotyping Array. Breast cancer tumor specimens were also collected, and tumor RNA was extracted from viable FFPE tumor samples. Tumor RNA analyses included gene expression profiling through NanoString PAM50.Data that will be available through dbGaP for this study include SNP array data and PAM50 data.

  Study phs003466

• Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET)

  STARNET is a genetics of RNA expression study of multiple disease-relevant tissues obtained from living patients with cardiovascular disease. Tissue samples are obtained from blood, atherosclerotic-lesion-free internal mammary artery (MAM) and atherosclerotic aortic root (AOR), subcutaneous fat (SF), visceral abdominal fat (VAF), skeletal muscle (SKLM), and liver (LIV) during open thorax surgery of 600 coronary artery disease (CAD) patients. All patients gave written informed consent. The inclusion criterion was eligibility for coronary artery by-pass graft (CABG) surgery. Patients with other severe systemic diseases, such as active systemic inflammatory disease or cancer, were excluded. The primary clinical end points were the SYNTAX score based on the extent of coronary atherosclerosis assessed from preoperative angiograms. The STARNET patients are Caucasians (31% females); 32% had diabetes, 75% had hypertension, and 67% had hyperlipidemia; and 33% had an MI before age 60. By New York Heart Association criteria, 45% were class I, 42% class II, 9% class III, and 1% class IV. TYPES AND RNA SEQUENCING: 566 DNA genotype and 3577 RNA-seq profiles from seven tissues from 600 STARNET CABG patients passed quality control (on average 511 RNA-seq profiles/tissue). DNA was genotyped with the OmniExpress Exome array (Illumina, ~900k SNPs) and imputed to a total of 14,098,063 DNA variant calls (6,245,505 with minor allele frequency >5%). The STARNET subjects mainly overlap with Caucasian of Northern European (Finnish) descent. RNA sequencing was performed using the HighSeq2000 platform, poly-A (LIV, SKLM, VAF, SF and blood) and ribo-zero (AOR, MAM) protocols with 50-100 bp read lengths, single end to 15-30 million read depth.

  Study phs001203

• Immunohistochemical and molecular pathological search in gastrointestinal tumors

  Purpose: RSPO fusions are recently identified recurrent genetic alterations in colorectal cancer (CRC), which lead to WNT pathway activation and are potential therapeutic targets. We aimed to investigate the clinicopathological and molecular features of RSPO fusion-positive CRCs. Experimental Design: We screened 1019 CRCs for RSPO fusions using multiplex reverse transcription polymerase chain reaction. RSPO fusion-positive tumors were characterized for their clinicopathological features and subjected to whole exome sequencing (WES). Results: Our analysis identified 29 CRCs with RSPO fusions (2.8%), consisting of 5 with an EIF3E-RSPO2 fusion and 24 with PTPRK-RSPO3 fusions. The patients were 17 females and 12 males with the median age of 64 years. Thirteen tumors were located in the right colon, 8 were in the left colon, and 8 were in the rectum. Histologically, most of the tumors (24/29, 83%) were classified as adenocarcinomas, not otherwise specified. However, about half of the tumors (13/29, 45%) had a focal or extensive mucinous component, which is significantly more frequent compared with RSPO fusion-negative tumors (13%; p = 8.1 �� 10-7). Four tumors (14%) were mismatch repair-deficient, three of which were associated with MLH1 promoter methylation. WES identified KRAS, BRAF, and NRAS mutations in a total of 27 cases (93%). In contrast, pathogenic mutations in major WNT pathway genes other than RSPO fusions were virtually absent. The presence of an RSPO fusion tended to show shorter overall and recurrence-free survivals in stage II and III patients although the differences were not significant. Conclusions: RSPO fusion-positive CRCs constitute a rare subgroup of CRCs with several characteristic clinicopathological and genetic features. The mutual exclusivity with other WNT pathway gene alterations supports RSPO fusions as valid therapeutic targets in CRC.

  Study JGAS000538