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• Yale Policy for head and neck cancer and HPV clinical trials

  Yale Policy for human controlled access data associated with head and neck cancer and HPV clinical trials

  Dac EGAC50000000403

• Evolution of an adenomacarcinoma in response to selection by targeted kinase inhibitors

  Background - Adenocarcinomas of the tongue are rare and represent the minority (20-25%) of salivary gland tumors affecting the tongue. We investigated the utility of massively parallel sequencing to characterize an adenocarcinoma of the tongue, before and after treatment. Results - In the pre-treatment tumor we identified 7,629 genes within regions of copy number gain. 1,078 genes exhibited increased expression relative to the blood and unrelated tumors and four genes contained somatic protein-coding mutations. Our analysis suggested the tumor cells were driven by the RET oncogene. Genes whose protein products are targeted by the RET inhibitors sunitinib and sorafenib correlated with being amplified and or highly expressed. Consistent with our observations administration of sunitinib was associated with stable disease lasting 4 months, after which the lung lesions began to grow. Administration of sorafenib and sulindac provided disease stabilization for an additional 3 months after which the cancer progressed and new lesions appeared. A recurring metastasis possessed 7,288 genes within copy number amplicons, 385 genes exhibiting increased expression relative to other tumours and 9 new somatic protein coding mutations. The observed mutations and amplif ications were consistent with therapeutic resistance arising through activation of the MAPK and AKT pathways. Conclusions - We conclude that complete genomic characterization of a rare tumour has the potential to aid in clinical decision making and identifying therapeutic approaches where no established treatment protocols exist. These results also provide direct in-vivo genomic evidence for mutational evolution within a tumor under drug selection and potential mechanisms of drug resistance accrual.

  Study EGAS00000000074

• STAMPEED: Whole Genome Association Analysis of Hematopoietic Cell Transplant (HCT) Outcomes

  This retrospective cohort study was designed to identify single nucleotide polymorphisms (SNPs) that are associated with complications after allogeneic hematopoietic cell transplantation (HCT). Validated discoveries provide information to improve risk assessment, counseling and treatment planning and to direct future mechanistic studies of the genes and pathways that influence outcomes, thereby providing insight and rationale for new targeted therapies. The study was conducted with the use of 3 different approaches. (1) We used GWAS discovery and replication analyses to identify SNPs variants associated with outcomes after HCT. (2) We tested SNP alleles in HLA-matched sibling donors and recipients to determine whether mismatching in the recipient is associated with graft-versus-host disease (GVHD) or the risk of recurrent malignancy after HCT. Such associations would suggest that the peptide encoded by the SNP allele functions as a minor histocompatibility antigen. (3) We performed in silico candidate SNP studies to determine the validity of previously published results showing associations with outcomes after HCT. The study population represents a large cohort from the Fred Hutchinson Cancer Research Center and consists of 4,471 recipients and 4,628 donors containing 4,258 recipient-donor pairs. Recipients suffered from a hematologic malignancy or myelodysplastic syndrome and were treated in a highly structured clinical research environment with comprehensive monitoring and systematic data recording. We used proportional hazards analyses to test for associations with acute and chronic GVHD, acute kidney injury, gram-negative bacteremia, invasive fungal disease, CMV infection and disease, recurrent malignancy, death not attributable to recurrent malignancy, and death after recurrent or progressive malignancy.

  Study phs001918

• University of Washington Cerebrospinal Fluid Biomarker Study for Parkinson disease

  There is a clear need to develop biomarkers for Parkinson disease (PD) diagnosis and monitoring disease progression. In this study we evaluated cerebrospinal fluid (CSF) proteins, which are known to be critically involved in PD or identified in our preliminary profiling studies, aptamers, and RNAs as potential PD biomarkers. Access to subjects for this study was via the Pacific Northwest Udall Center (PANUC) and the Alzheimer's Disease Research Center (ADRC) at the University of Washington and Oregon Health and Sciences University (OHSU). Using CSF samples from 30 well-characterized patients with PD and 30 age-, sex-matched healthy controls, we prepared RNA seq libraries and performed deep sequencing of all RNA species, including small and long RNA, mRNAs, noncoding RNAs and differentially spliced transcripts. We then tried several methods for RNAseq data analysis to optimize our analysis pipeline. We identified a total of 3381 transcripts corresponding to 182 long intergenic RNAs (LincRNAs), 11 microRNAs (miRNAs), 2861 protein-coding transcripts, 200 pseudogenes and 127 antisense RNAs; some of them were differentially expressed between PD and control groups. Selected differentially expressed RNAs have been validated in the same set of CSF samples using real-time PCR (RT-PCR). Further validations in independent, larger cohorts of samples are still ongoing. Our results obtained so far suggested that CSF proteins and RNAs could be used as good indexes for PD diagnosis and disease severity/progression. This study is a part of the NIDDS-funded Parkinson's Disease Biomarkers Program (PDBP).

  Study phs000901

• Complex genotype-phenotype relationships shape the response to treatment of Down Syndrome Childhood Acute Lymphoblastic Leukaemia

  Extensive genetic and epigenetic variegation has been demonstrated in many malignancies. Importantly, their interplay has the potential to contribute to disease progression and treatment resistance. To shed light on the complex relationships between these different sources of intra-tumour heterogeneity, we explored their relative contributions to the evolutionary dynamics of Acute Lymphoblastic Leukaemia (ALL) in children with Down syndrome, which has particularly poor prognosis. We quantified the tumour propagating potential of genetically distinct sub-clones using serial transplantation assays and SNP-arrays. While most leukaemias were characterized by a single dominant subclone, others were highly heterogeneous. Importantly, we provide clear and direct evidence that genotypes and phenotypes with functional relevance to leukemic progression and treatment resistance can co-segregate within the disease. Hence, individual genetic lesions can be restricted to well-defined cell immunophenotypes, corresponding to different stages of the leukemic differentiation hierarchy and varied proliferation potentials. As a result of this difference in fitness, which can be accurately quantified via competitive transplantation assays, matching diagnostic, post-treatment, and relapse leukaemias can be dominated by different genotypes, including pre-leukemic clones persisting throughout the disease progression and treatment. Intriguingly, plasticity also appears to be a temporally defined property that can segregate with genotype. These results suggest that Down Syndrome ALL should be viewed as a complex matrix of cells exhibiting genetic and epigenetic heterogeneity that foster extensive clonal evolution and competition. Therapeutic intervention reshapes this ‘eco-system’ and may provide the right conditions for the preferential expansion of selected compartments and subsequently relapse.

  Study EGAS50000001287

• The genomic landscape of pediatric acute lymphoblastic leukemia

  Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer and arises from B- or T-lineage lymphocyte precursors. ALL comprises dozens of subtypes, and genomic analyses have largely been performed within these subtypes. Here we analyze pediatric ALL genomes across all subtypes, including 768 whole genomes, 1,729 exomes, and 1,889 transcriptomes in 2,754 patients. Most ALL subtypes harbor 4 or more driver alterations per sample, similar to adult cancers, despite low mutation burdens. Hyperdiploid B-ALL copy gains are likely acquired early and synchronously, with copy gains occurring before ultraviolet-induced mutations. By contrast, ultraviolet-induced mutations precede copy gains in iAMP21 B-ALL. Overall, we identified 378 putative ALL driver genes. Most driver alterations vary in prevalence across ALL subtypes, with B-ALL enriched for Ras and B-lineage-related alterations, and T-ALL enriched for PI3K, JAK, and cell cycle alterations. Most B-ALL (54.3%) and T-ALL (51.2%) samples bear at least one rare driver gene alteration (present in less than 2% of samples), including 30 putative novel cancer driver genes associated with ubiquitination, SUMOylation, non-coding, and other functions. Known or novel alterations associated with poor outcomes in specific subtypes include TBL1XR1 alterations in ETV6-RUNX1 patients, CREBBP in Ph-like-CRLF2, SETD2 in hyperdiploid, and PTEN in TAL1 patients. Intriguingly, DUX4 and KMT2A subtypes separate into CEBPA/FLT3- or NFATC4-expressing subgroups with potential clinical implications. Together, these results deepen understanding of ALL etiology and outcomes, and facilitate ALL model development.

  Study EGAS00001005250

• whole genome sequence data of multifocal hepatocellular carcinoma

  Background & Aims: The differentiation of distinct multifocal hepatocellular carcinoma (HCC): multicentric disease vs. intrahepatic metastases, in which the management and prognosis varies substantively, remains problematic. We aim to stratify multifocal HCC and identify novel diagnostic and prognostic biomarkers by performing whole genome and transcriptome sequencing, as part of a multi-omics strategy Methods: A complete collection of tumour and somatic specimens (intrahepatic HCC lesions, matched non-cancerous liver tissue and blood) were obtained from representative patientswith multifocal HCC exhibiting two distinct postsurgical courses. Whole-genome and transcriptome sequencing with genotyping were performed for each tissue specimen to con-trast genomic alterations, including hepatitis B virus integrations, somatic mutations, copy number variations, and structural variations. We then constructed a phylogenetic tree to visualise individual tumour evolution and performed functional enrichment analyses on select differentially expressed genes to elucidate biological processes involved in multifocal HCC development. Multi-omics data were integrated with detailed clinicopathological information to identify HCC biomarkers, which were further validated using a large cohort of HCC patients (n = 174).Results: The multi-omics pro?ling and tumour biomarkers could successfully distinguish the two multifocal HCC types, while accurately predicting clonality and aggressiveness. The dual speci?city protein kinase TTK, which is a key mitotic checkpoint regulator with links to p53 signaling, was further shown to be a promising overall prognostic marker for HCC in the large patient cohort.Conclusions: Comprehensive multi-omics characterisation of multifocal tumour evolution may improve clinical decision-making, facilitate personalised medicine, and expedite identi?cation of novel biomarkers and therapeutic targets in HCC.

  Study EGAS00001002338

• Open_Targets_020_Epigenomes_of_Cell_Lines

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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/

  Study EGAS00001003136

• Open_Targets_020_Epigenomes_of_Cell_Lines

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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/

  Study EGAS00001003137

• Open_Targets_020_Epigenomes_of_Cell_Lines

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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/

  Study EGAS00001003139