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• Prostate cancer datasets WGS

  Low pass WGS: 48 samples (5 blood samples from 6 patient data): 22 Tumour cores and 26 normal/benign cores (Next Seq )

  Dataset EGAD00001004466

• Genetic analysis of HLA and immune escape genes in Diffuse Large B-cell Lymphoma

  Fifty percent of diffuse large B-cell lymphoma (DLBCL) cases lack cell-surface expression of the class-I major histocompatibility complex (MHC-I), thereby escaping immune recognition by cytotoxic T cells. In order to comprehensively identify the mechanisms involved in MHC-I loss, we first performed immunophenotypic analysis of both MHC class-I and -II in 657 cases across the spectrum of B-NHL, revealing that loss of MHC-I, but not MHC-II, is preferentially restricted to DLBCL. We then used whole exome and targeted deep-sequencing to examine genes involved in MHC-I expression in 74 DLBCL samples representative of MHC-I positive and negative cases. We show here that somatic biallelic or monoallelic inactivation of B2M and/or HLA-I is present in 80.9% (34/42) of MHC-I negative tumors. Furthermore, 68.8% (22/32) of MHC-I positive DLBCLs also harbored monoallelic HLA-I genetic alterations (MHC-I positivemono) that lead to allelic imbalance, suggesting allele-specific inactivation. Both MHC-I negative and MHC-I positivemono cases showed a significantly higher mutational burden as well as a higher number of inferred neo-antigens, suggesting co-selection of HLA-I loss and sustained neo-antigen production. Interestingly, the analysis of > 500.000 individuals in two databases revealed homozygosity of germline HLA-I genes in 26-38% of DLBCL patients, a frequency significantly higher than that observed in any other cancer type. In mice, germinal-center B cells lacking HLA-I expression did not progress to lymphoma and were counterselected in the context of oncogene-driven lymphomagenesis, suggesting that additional events are needed to license immune evasion. These results suggest a multi-step process of HLA-I loss including both germ-line and somatic events in DLBCL development, and have direct implications for the pathogenesis and immunotherapeutic targeting of this disease.

  Study EGAS00001005054

• Transcriptomic Analysis of Human Hematopoietic Progenitors from Healthy Donors and Bone Marrow Failure Patients

  The purpose of this study was to define transcriptional changes that occur in the rare and heterogeneous bone marrow progenitors that are affected in Shwachman-Diamond Syndrome. Data are reported for four genetically confirmed SDS patients ranging from 11-26 years old, 3 male and 1 female, and four healthy donors ranging from 25-29 years old, 2 male and 2 female. Subjects provided written, informed consent in accordance with the Declaration of Helsinki's Ethical Principles of Medical Research Involving Human Subjects. Single CD34+ cells were purified from fresh bone marrow and cDNA libraries were prepared using the SMARTer Ultra Low RNA Kit (Clontech; pre-2015) or SMART-Seq v4 Ultra Low RNA Kit (Clontech; post-2015). Libraries were sequenced on a HiSeq 2500 Instrument (Illumina, San Diego, CA) to a read depth of ~3 M paired-end, 25 bp reads per single cell. Paired-end reads were mapped to the hg38 human transcriptome (Gencode v24) using STAR v2.4.2a.

  Study phs001845

• Federated discovery and sharing of genomic data using Beacons

  The Beacon Project is a Global Alliance for Genomics & Health (GA4GH) initiative that enables genomic and clinical data sharing across federated networks. The project is working toward developing regulatory, ethics and security guidance to ensure proportionate safeguards for distribution of data according to the GA4GH-developed “Framework for Responsible Sharing of Genomic and Health-Related Data”. Within this Nature Biotechnology Correspondence a description of the Beacon protocol and how it can be used as a model for the federated discovery and sharing of genomic data is offered to the community. A Beacon is defined as a web-accessible service that can be queried for information about a specific allele. A user of a Beacon can pose queries of the form “Have you observed this nucleotide (e.g., C) at this genomic location (e.g., position 32,936,732 on chromosome 13)?” to which the Beacon responds with either “yes” or “no.” In this way, a Beacon allows allelic information of interest to be discovered by a remote searcher with no reference to a specific sample or patient, thereby mitigating privacy risks. The Beacon API (represented as a RESTful web application) provides a technical specification that a Beacon server must implement. The specification is open source and available online here. To simplify the process of lighting a Beacon, a free, open-source reference implementation of the latest specification has been developed. GA4GH is promoting different levels of data access (open, registered, and controlled) for convenience and for compatibility across its projects. Each so-called access tier has distinct visibility and requirements for authorization. For example, ‘open access’ Beacons are accessible to anonymous users of the internet, whereas ‘registered access’ Beacons are accessible to registered users (for example, bona fide researchers and clinicians) who have agreed to a set of conditions of data use. Many of the largest genomic archives, such as dbGaP, the European Genome-phenome Archive and the European Variation Archive, have provided access to variation data through Beacons for some or all of their datasets. Beacons can be interconnected through the Beacon Network, a directory and search engine for Beacons. Although individual Beacons answer the question “Have you observed this allele?”, the Beacon Network answers the question “Who has observed this allele?”. Beacons can be freely registered to the Beacon Network and can be searched independently or in aggregate with other connected Beacons.

  Blog federated-discovery-using-beacons

• Whole Exome Sequencing of Human Gastro-esophageal Cancer PDXs

  The dataset includes 51 whole exome sequencing datasets generated using Illumina paired-end sequencing technology. These data derive from 26 patient-derived xenograft (PDX) tumors and their matched normal tissues, which consist of either normal gastric mucosa or blood samples. In one case (GTR0607), the matched normal tissue data are unavailable. As a result, the dataset comprises 102 FASTQ files, providing raw sequencing reads for comprehensive genomic analysis.

  Dataset EGAD50000001407

• PYDP Papuan Y chromosome Diversity Panel

  The PYDP dataset includes 26 bam files of Y chromosome sequences for Papua New Guinean individuals from different locations, extracted from whole genome sequences. DNA was extrated from saliva samples (Oragen kit). Sequencing libraries were prepared using the TruSeq DNA PCR-Free HT kit. 150 bp paired-end sequencing was performed on the Illumina HiSeq X5 sequencer.

  Dataset EGAD00001008572

• Contribution of systemic and somatic factors to clinical response and resistance in urothelial cancer: an exploratory multi-omic analysis

  Patients with metastatic urothelial cancer (n=29) were treated with atezolizumab (anti-PD-L1). All 29 patients had T-cell receptor sequencing (TCR-seq) of the pre-treatment blood; 24 also had TCR-seq on at least one post-treatment blood sample. 24 patients had TCR-seq of their pre-treatment tumors. TCR-seq data can be found at http://doi.org/10.5281/zenodo.546110. 26 patients also had RNAseq of their tumors and whole exome sequencing (WES) of their tumors and matched normal blood. WES results for one sample were excluded from our analysis after failing to meet coverage requirements.

  Study phs001743

• Whole Exome Sequencing of Human Gastro-esophageal Cancer PDXs

  The current study investigates biomarkers of response to anti-EGFR therapies in gastro-esophageal cancer. Whole exome sequencing was performed on 26 tumors to explore potential factors influencing treatment outcomes. As part of the analysis, somatic mutations in EGFR, ERBB2, and key downstream signaling genes (KRAS and PIK3CA) were examined to exclude the presence of known mutations conferring sensitivity/resistance. The study aims to contribute to the identification of patients who may benefit from lower-toxicity regimens, improving treatment personalization and minimizing adverse effects.

  Study EGAS50000000966

• WGS in insulinomas

  Whole-Genome Sequencing datasets of insulinoma samples and paired blood controls

  Dataset EGAD50000000464

• Transcriptomic profiling of patient-derived xenografts and organoids in prostate cancer

  Dataset contains RNA-seq of 30 samples (normal prostate tissue, human prostate cancer, PDX and organoids).

  Dataset EGAD00001006404