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• Whole genome sequencing of adult glioblastoma nuclei

  Three primary adult glioblastoma specimens were dissociated and nuclei were extracted. A portion of the nuclei was used for single-cell ATAC seq and the remainder were submitted for whole genome sequencing, to provide orthogonal validation of copy number variations in the samples compared to single-cell ATAC seq. Samples were sequenced on the Illumina NovaSeq 6000 in paired-end mode.

  Dataset EGAD00001007651

• Transcriptomic Data for Manuscript with title: Comprehensive genomic profiling in esophageal adenocarcinoma unmasks potential precision therapies

  Transcriptomic Data for Manuscript with title: Comprehensive genomic profiling in esophageal adenocarcinoma unmasks potential precision therapies

  Dataset EGAD00001015476

• Colorectal cancer WES/WGS analysis in Dr. Liu’s group in Sun Yat-sen University Cancer Center

  The samples include paired tumor and normal tissues from 205 patients (201 for normal and primary tumor tissues; 4 for normal, primary tumor and liver metastatic tissues). High-coverage WES sequencing or whole genome sequencing of DNA samples were performed on the Illumina HiSeq 2000 system

  Dataset EGAD00001003452

• Volasertib preclinical activity in high-risk hepatoblastoma

  Relapsed and metastatic hepatoblastoma represents an unmet clinical need with limited chemotherapy treatment options. In a chemical screen, we identified volasertib as an agent with in vitro activity, inhibiting hepatoblastoma cell growth while sparing normal hepatocytes. Volasertib targets PLK1 and prevents the progression of mitosis, resulting in eventual cell death. PLK1 is overexpressed in hepatoblastoma biopsies relative to normal liver tissue. As a potential therapeutic strategy, we tested the combination of volasertib and the relapse-related hepatoblastoma chemotherapeutic irinotecan. We found both in vitro and in vivo efficacy of this combination, which may merit further preclinical investigation and exploration for a clinical trial concept.

  Study EGAS00001004827

• Functional Significance of Prostate Cancer Risk-SNPs

  Prostate Cancer (PrCa), the most frequently diagnosed solid tumor in men in the U.S., results in ~192,000 new cases and ~27,000 deaths per year. Although the variation of PrCa incidence is likely to be the result of several factors, there is a large body of literature that strongly implicates a genetic etiology. Genome-wide association studies (GWAS) have emerged as the most widely used contemporary approach to identify genetic variants (in particular SNPs) that are associated with increased risk of human disease. For PrCa, at least five GWAS have now been performed yielding a substantial number of well-validated SNPs that are associated with an increased risk of PrCa, and that number continues to grow. A significant problem for many of the PrCa risk-SNPs identified so far, however, is that they do not lie within or near a known gene and they have no obvious functional properties. These findings suggest that many (if not most) of these risk-SNPs will be located in regulatory regions that control gene expression rather than in coding regions that may directly affect protein function. Therefore, in order to define the functional role of currently known risk-SNPs, the target genes must first be identified. A promising strategy to address this problem involves the use of expression quantitative trait loci (eQTL) analysis. Unfortunately, most of the publically available SNP-Transcript eQTL datasets utilize lymphoblastoid cells with only a handful using tissue from target organs. Although useful, these datasets alone are unlikely to be sufficient. Recent studies have demonstrated that gene expression and gene regulation occur in both a tissue-specific and tissue independent fashion and suggest that a complete repertoire of regulatory SNPs can only be uncovered in the context of cell type specificity. To date, such a tissue-specific dataset for normal prostate tissue does not exist. In this study, we have constructed a normal prostate tissue specific eQTL data set.

  Study phs000985

• Genome_Diversity_in_Africa_Project__Uganda

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene–disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics

  Study EGAS00001002523

• The University of Hong Kong Colon Cancer GCV Study

  Background: Ganciclovir (GCV) is widely used in solid organ and hematopoietic stem cell transplant patients for prophylaxis and treatment of cytomegalovirus. It has long been considered a mutagen and carcinogen. However, the contribution of GCV to cancer incidence and other factors that influence its mutagenicity remains unknown. Methods: This retrospective cohort study analysed genomics data for 121,771 patients who had undergone targeted sequencing compiled by the Genomics Evidence Neoplasia Information Exchange (GENIE) or Foundation Medicine (FM). A statistical approach was developed to identify patients with GCV-associated mutational signature (GCVsig) from targeted sequenced data of tumour samples. Cell line exposure models were further used to quantify mutation burden and DNA damage caused by GCV and other antiviral and immunosuppressive drugs. Results: Mutational profiles from 22 of 121,771 patient samples in the GENIE and FM cohorts showed evidence of GCVsig. A diverse range of cancers was represented. All patients with detailed clinical history available had previously undergone solid organ transplantation and received GCV and mycophenolate treatment. RAS hotspot mutations associated with GCVsig¬¬ were present in 9 of the 22 samples, with all samples harbouring multiple GCV-associated protein-altering mutations in cancer driver genes. In vitro testing in cell lines showed that elevated DNA damage response and GCV¬sig are uniquely associated with GCV but not acyclovir, a structurally similar antiviral. Combination treatment of GCV with the immunosuppressant, mycophenolate mofetil (MMF), increased the misincorporation of GCV in genomic DNA and mutations attributed to GCVsig in cell lines and organoids. Conclusions: In summary, GCV can cause a diverse range of cancers. Its mutagenicity may be potentiated by other therapies, such as mycophenolate, commonly co-prescribed with GCV for post-transplant patients. Further investigation of the optimal use of these drugs could help reduce GCV-associated mutagenesis in post-transplant patients.

  Study EGAS00001006707

• Longread sequencing of selected 12q-amplified osteosarcomas

  Longread sequencing of selected 12q-amplified osteosarcomas for verification of SV data. This was carried out in order to verify findings from mate-pair sequencing regarding the structure of the chromosome 12q-amplicons and whether material from other chromosomes is also intertwined and amplified in a bid to further characterise these tumours beyond CDK4 and MDM2 amplification.

  Study EGAS50000000495

• singel cell RNAseq dataset for the study "Composition and functional status of T and NK cells in Extramedullary myeloma tumor microenvironment""

  Dataset contains all newly generated single cell RNAseq data generated for the study. It includes 5 EMM soft tissue samples, 5 EMM bone marrow samples (EMM_BM) and 6 RRMM BM samples without EMM (RRMM_BM). Samples that are sequenced twice are marked by _1 or _2 in the sample name. The sample name mentioned corresponds to the sample name used in the publication. The rest of the EMM single cell RNAseq samples mentioned int the publication, EMM_03_1, EMM_11, EMM_14_1, EMM_14_2, EMM_16, and EMM_15_1 are already uploaded in EGA archive – dataset id EGAD50000000053.

  Dataset EGAD50000001511

• Microarray genotyping of idiopathic hypersomnia patients (11 orexin mutation-positive patients, 85 orexin mutation-negative patients)

  We performed a principal component analysis (PCA) to determine whether population stratification or differences in the genetic background are present between the orexin mutation-positive and -negative idiopathic hypersomnia groups. Genome-wide single nucleotide polymorphism (SNP) data in patients with idiopathic hypersomnia (orexin mutation-positive patients and orexin mutation-negative patients) were utilized for the PCA.

  Study JGAS000508