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• Characterization of Cell Free Plasma Methyl-DNA From Xenografted Tumors to Guide the Selection of Diagnostic Markers for Early-Stage Cancers

  Circulating cell-free methyl-DNA (mcfDNA) contains promising cancer markers but its low abundance and possibly diverse origin pose challenges toward the accurate diagnosis of early stage cancers. By whole-genome bisulfite sequencing (WGBS) of cell-free DNA (cfDNA) from about 0.5 mL plasma of mice xenografted with human tumors, we obtained and aligned the reads to the human genome, filtered out the mouse and carrier bacterial sequences, and confirmed the tumor origin of methyl-cfDNA (mctDNA) by methylation-sensitive restriction enzyme digestion prior to species-specific PCR. We estimated that human tumor-specific reads (ctDNA) or mctDNA comprised about 0.29 or 0.01%, respectively of the xenograft mouse cfDNA, and about 0.029 or 0.001% of the cfDNA of human early stage cancer patients. Similar WGBS of early stage (0-II, node- and metastasis-free) breast, lung or colorectal cancer samples identified hundreds of specific DMRs (differentially methylated regions) compared to healthy controls. Their association with tumourigenesis was supported by stage-dependent methylation, tumor suppressor or oncogene clusters, and genes also identified in the xenograft samples. Using 20 three-cancer-common and 17 colorectal cancer-specific DMRs in combination (top 0.0018% of the WGBS methylation clusters) was sufficient to distinguish the stage I colorectal cancers from breast and lung cancers and healthy controls. Our data thus confirmed the tumor origin of mctDNA by sequence specificity, and provide a selection threshold for authentic tumor mctDNA markers toward precise diagnosis of early stage cancers solely by top DMRs in combination. Biological Materials were provided by the Ontario Tumour Bank, which is funded by the Ontario Institute for Cancer Research Reference for citation: Ling Liu, Jinghua Feng, Julian Polimeni, Manli Zhang, Hai Nguyen, Urmi Das, Xu Zhang, Harminder Singh, Xiao-Jian Yao, Etienne Leygue, Sam K.P. Kung, and Xie J. Characterization of cell free plasma methyl-DNA from xenografted tumours to guide the selection of diagnostic markers for early-stage cancers. Frontiers in Oncology, 2021 Feb. 5. DOI: 10.3389/fonc.2021.615821.

  Study EGAS00001006175

• 1000 Genomes Used for Cloud Testing

  WARNING: This is a test data set. The phenotype data was not checked to match 1000 Genomes project. Use with caution.This study provides public access to a demonstration subset of 1000 genomes sequence data in dbGaP. It is intended to be used by software developers who design, implement and validate pipelines for dbGaP data. While this project distributes only public data, it uses dbGaP security mechanisms which include a project-specific security key and a decryption password. Since the data are public, the key and password for this project will be included by SRA into public demonstration packages that permit users to test and validate the security of their computational pipelines. Note that all public users of this data will be logged under the same project and account ID. The datasets attached to this project must be restricted to 1000 Genomes data identical to the project's public FTP site. To access these test data using SRA toolkit use prj_phs710EA_test.ngc.

  Study phs000710

• Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci

  Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n=17) and DNA methylation (whole-genome bisulphite sequencing, n=10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.

  Study EGAS00001002592

• Host Genetic Determinants of the Outcome of Staphylococcus Aureus Bacteremia by Whole Exome Sequencing

  In this case-control study, Complicated Staphylococcus aureus (case) is defined as bacteremia plus endocarditis or bone/joint infection, and Uncomplicated Staphylococcus aureus (control) has no such complications and was cured at follow-up. We used whole exome sequencing to examine the cumulative effect of coding variants in each gene on risk of complicated SAB in a discovery sample of 168 SAB cases (84 Complicated SAB and 84 Uncomplicated SAB, frequency matched by age, sex and bacterial clonal complex). Then we evaluated the 334 most significantly associated genes and 8 biological candidate genes in a replication sample of 240 SAB cases (122 complicated and 118 uncomplicated, frequency matched by age, sex and bacterial clonal complex). All participants were white, non-Hispanic of European descent. In the discovery sample, gene-based analysis using SKAT-O identified 334 genes associated with complicated SAB at p<3.5 x 10-3;. Gene-based analysis of the 342 genes in the replication sample using SKATO identified one gene, GLS2 (GeneID: 27165), significantly associated with complicated SAB (p=1.2 x10-4;) after Bonferroni correction. GLS2 is an interesting candidate gene for complicated SAB due to its role in regulating glutamine metabolism, a key factor in white blood cell proliferation and activation.

  Study phs001505

• Accurate detection and classification of pediatric sarcomas based on cell-free DNA fragmentation patterns

  Sequencing of cell-free DNA in the blood of cancer patients (“liquid biopsy”) provides attractive opportunities not only for early diagnosis, but also for minimally invasive monitoring of treatment response and disease courses. To unlock liquid biopsy analysis for pediatric tumors with few genetic aberrations, we developed an integrated genetic/epigenetic analysis method and applied it to 241 deep whole-genome sequencing profiles of 95 patients with Ewing sarcoma and 31 patients with other pediatric sarcomas. We achieved sensitive detection and classification of circulating tumor DNA in peripheral blood independent of any genetic alterations. We evaluated different metrics for cell-free DNA fragmentation analysis and developed LIQUORICE, a bioinformatic tool for detecting circulating tumor DNA based on tumor-specific chromatin structure. Using machine learning methods, we combined several fragmentation-based metrics into an integrated approach for liquid biopsy analysis tailored to cancers with low mutation rates but widespread epigenetic deregulation. Clinical associations highlighted the potential value of cfDNA fragmentation patterns as prognostic biomarkers in Ewing sarcoma. Additionally, we performed low coverage whole-genome-sequencing on 43 tumor biopsy samples from patients with Ewing sarcoma, in order to compare copy number aberrations detected in cell-free DNA and biopsy samples of the same patients. For validation of the epigenetic signatures inferred from cell-free DNA, we further performed reduced representation bisulfite sequencing (RRBS) on 38 matched biopsy samples from patients with Ewing sarcoma. In summary, our study provides a comprehensive analysis of circulating tumor DNA beyond recurrent somatic mutations, and it renders the benefits of liquid biopsy more readily accessible for childhood cancers.

  Study EGAS00001005127

• Biallelic tumor suppressor loss and DNA repair defects in de novo small cell prostate cancer

  Small cell prostatic carcinoma (SCPC) is an aggressive pathology that is managed similar to small cell lung cancer. SCPC can evolve from prostatic adenocarcinoma in response to androgen deprivation therapy but in rare cases is present at initial cancer diagnosis. The molecular etiology of de novo SCPC is incompletely understood due to the scarcity of tumor tissue and the brief life expectancy of patients. Through a retrospective search of our regional oncology pharmacy database, we identified 18 patients diagnosed with de novo SCPC between 2004 and 2017. Ten patients had pure SCPC pathology and the remainder had some admixed adenocarcinoma foci, but all were treated with first line platinum-based chemotherapy. Median overall survival was 28 months. We performed targeted DNA sequencing, whole exome sequencing and mRNA profiling on formalin-fixed paraffin embedded archival tumor tissue. We observed frequent biallelic deletion and/or mutation of tumor suppressors TP53, RB1 and PTEN, similar to treatment related SCPC. Indeed, at the RNA level pure de novo SCPC closely resembled treatment-related SCPC. However, five patients had biallelic loss of DNA repair genes including BRCA1, BRCA2, ATM and MSH2/6: potentially underlying the high genomic instability of this rare disease variant. Two patients with pure de novo SCPC harbored ETS gene rearrangements to androgen-driven promoters, consistent with evolution of de novo SCPC from an androgen-driven ancestor. Overall, our results reveal a highly aggressive molecular landscape underlies this unusual pathologic variant, and propose opportunities for targeted therapy strategies in a disease with few treatment options.

  Study EGAS00001003007

• Transcriptome sequencing across a prostate cancer cohort identifies PCAT-1, an unannotated lincRNA implicated in disease progression

  Noncoding RNAs (ncRNAs) are emerging as key molecules in human cancer, with the potential to serve as novel markers of disease and to reveal uncharacterized aspects of tumor biology. Here we discover 121 unannotated prostate cancer-associated ncRNA transcripts (PCATs) by ab initio assembly of high-throughput sequencing of polyA+ RNA (RNA-Seq) from a cohort of 102 prostate tissues and cells lines. We characterized one ncRNA, PCAT-1, as a prostate-specific regulator of cell proliferation and show that it is a target of the polycomb repressive complex 2 (PRC2). We further found that patterns of PCAT-1 and PRC2 expression stratified patient tissues into molecular subtypes distinguished by expression signatures of PCAT-1-repressed target genes. Taken together, our findings suggest that PCAT-1 is a transcriptional repressor implicated in a subset of prostate cancer patients. These findings establish the utility of RNA-Seq to identify disease-associated ncRNAs that may improve the stratification of cancer subtypes.

  Study phs000443

• Single-cell RNA-seq data from metastatic ovarian cancer for quality control study

  Quality control is a crucial preliminary step in any single-cell RNAseq experiment, where hard thresholds are commonly used. In order to develop a methodology for a more precise cell filtering in the early steps of a scRNAseq data analysis, we collected tissue samples before chemotherapy from 4 patients.

  Study EGAS00001005066

• Human islet 3D chromatin maps provide insights into type 2 diabetes

  The transcriptional output of each cell type is controlled by thousands of enhancers, many of which contain genetic risk variants for common diseases such as type 2 diabetes (T2D). To gain insight into how enhancer variation influences diabetes risk, we created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated islet enhancers with their target genes, often located hundreds of kilobases away. We identified hubs that show spatial and functional connections between enhancersand target genes related to islet function and diabetes. We demonstrate that genetic variants distributed across hub enhancers have a major impact on T2D heritability, and use this knowledge to identify individuals in whom islet regulatory variation has a prominent role in T2D risk. Our results demonstrate the importance of 3D chromatin architecture for molecular interpretation of T2D genetic association signals, and define genomic spaces that harbor a distinct component of the T2D polygenic burden.

  Study EGAS00001002917

• Genome-wide analysis of genetic risk factors for rheumatic heart disease in Aboriginal Australians provides support for pathogenic molecular mimicry

  Background. Rheumatic heart disease (RHD) following Group A Streptococcus (GAS) infections is heritable and prevalent in Indigenous populations. Molecular mimicry between human and GAS proteins triggers pro-inflammatory cardiac valve-reactive T-cells. Methods. Genome-wide genetic analysis was undertaken in 1263 Aboriginal Australians (398 RHD cases; 865 controls). Single nucleotide polymorphisms (SNPs) were genotyped using Illumina HumanCoreExome BeadChips. Direct typing and imputation was used to fine-map the human leukocyte antigen (HLA) region. Epitope binding affinities were mapped for human cross-reactive GAS proteins, including M5 and M6. Results. The strongest genetic association was intronic to HLA-DQA1 (rs9272622; P=1.86x10-7). Conditional analyses showed rs9272622 and/or DQA1*AA16 account for the HLA signal. HLA-DQA1*0101_DQB1*0503 (OR 1.44, 95%CI 1.09-1.90, P=9.56x10-3) and HLA-DQA1*0103_DQB1*0601 (OR 1.27, 95%CI 1.07-1.52, P=7.15x10-3) were risk haplotypes; HLA_DQA1*0301-DQB1*0402 (OR 0.30, 95%CI 0.14-0.65, P=2.36x10-3) was protective. Human myosin cross-reactive N-terminal and B repeat epitopes of GAS M5/M6 bind with higher affinity to DQA1/DQB1 alpha/beta dimers for the two risk haplotypes than the protective haplotype. Conclusions. Variation at HLA_DQA1-DQB1 is the major genetic risk factor for RHD in Aboriginal Australians studied here. Cross-reactive epitopes bind with higher affinity to alpha/beta dimers formed by risk haplotypes, supporting molecular mimicry as the key mechanism of RHD pathogenesis.

  Study EGAS00001002678