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• LINE_luminal_breast_cancer_Neoadjuvant_Chemotherapy_Study

  A targeted gene screen of 365 known cancer genes in luminal breast cancer samples pre-chemotherapy and at resection post-chemotherapy to evalaute clonal expansion of chemotherapy cancer cells.

  Study EGAS00001001223

• Multiomic profiling of early-passage melanoma cell lines.

  This study utilises multiomic profiling of early-passage melanoma cell lines to explore the interactions between distinct modalities of molecular regulation influencing melanoma cellular phenotype.

  Study EGAS00001004536

• Somatic_Genetics_of_lesions_from_a_POT1_patient

  In this project we will use exome sequencing to identify somatic mutations in lesions from a patient with a germline mutation in the protection of telomeres 1 gene (POT1).

  Study EGAS00001001343

• Organoid_Derivation_Project___GRCh38___RNAseq

  Generation of normal and cancer organoids for sequencing as part of the WTSI-CRUK international collaboration with NCI (in HCMI) to generate the next generation of cancer cell lines.

  Study EGAS00001004677

• Epigenomic data of HEMa_LP

  To profile the epigenomic landscape of Human Epidermal Melanocytes , adult, lightly pigmented(HEMa-LP), whole genome bisulphite sequencing (WGBS) and ChIP-seq of histone marks data were generated.

  Study EGAS00001004016

• RNA-seq of Ewing sarcoma tumors (ICGC)

  Ewing sarcoma (ES) is a primary bone tumor initiated by an EWSR1-ETS gene fusion. To characterize the transcriptome of Ewing sarcoma, RNA-seq was performed.

  Study EGAS00001003333

• Organoid_Derivation_Project___GRCh38___WGS

  Generation of normal and cancer organoids for sequencing as part of the WTSI-CRUK international collaboration with NCI (in HCMI) to generate the next generation of cancer cell lines

  Study EGAS00001004712

• Organoid_Derivation_Project___GRCh38___TGS

  Generation of normal and cancer organoids for sequencing as part of the WTSI-CRUK international collaboration with NCI (in HCMI) to generate the next generation of cancer cell lines.

  Study EGAS00001007349

• IFNL4 Organoid Transcriptome Profiles

  RNAseq of liver organoids with a dG genotype (B20, nt115, U15) and with a TT genotype (nt5, U16, U19) was performed, which was used to study the impact of IFNλ4 on the cellular response to Sendai viral infection.

  Dataset EGAD00001007820

• Enhancer profiling to identify identifies epigenetic markers of endocrine resistance in metastatic castration resistant prostate cancer patients

  ChIP-seq and matched input data of AR, FOXA1 and H3K27ac for mCRPC patient samples taken prior to and after treatment with AR targeted therapy

  Dataset EGAD00001008688

• RNAseq of breast cancer bone metastases PDX resistant of responder to IACS-010759 treatment

  Fastq files from RNAseq of breast cancer bone metastases PDX after treatment with IACS-010759. Five PDX are resistants to treatment and 6 are responders.

  Dataset EGAD00001009072

• WGS of off-target analysis of prime editing in organoids

  Five edited and two unedited organoid clones with one clone prior to editing were paired-end whole genome sequenced using Illumina Novaseq 6000 system. The reads were mapped to hg38 genome assembly and data is provided as BAM files.

  Dataset EGAD00001007744

• Role of HPV and Interferon in APOBEC mutational signature (2019-04-11)

  The aim of this project is to test whether HPV oncogenes and /or interferon induce the APOBEC mutational signature in vitro, and to test the role of APOBEC3A in this process. . This dataset contains all the data available for this study on 2019-04-11.

  Dataset EGAD00001004955

• WGS paired B-Cell lymphoma cells sorted according to CD48

  paired WGS data of one tumor of one patient with nodal B-cell lymphoma. Tumor cells were sorted according to CD48 expression in a high and low fraction. Library preparation with TruSeq Nano and sequencing on Hiseq XTen.

  Dataset EGAD00001006058

• RNA sequencing data to study therapeutic targeting of ependymoma

  This dataset conatains RNA sequencing data from 24 patients. Up to two lanes per tumour sample have been seqeunced on a Illumina HiSeq2000 instrument in paired-end mode resulting in 58 Fastq files.

  Dataset EGAD00001003966

• Multiple Malignancy Familial Comparison

  Patient (who has had multiple malignancies) has previously been found to harbour a pathogenic p53 variant which is probably mosaic. This finding is based on exome sequencing performed elsewhere. In this study we will resequence the locus in question to ascertain whether the variant is indeed mosaic.

  Dataset EGAD00001001062

• Genomic analysis of HPV-positive versus HPV-negative oesophageal adenocarcinoma

  Whole exome sequencing was performed to explore the mutational landscape and potential molecular signature of HPV-positive versus HPV-negative OAC. Four hr-HPV-positive and 8 HPV-negative treatment-naive fresh-frozen OAC tissue specimens and matched normal tissue were analysed to identify somatic genomic mutations

  Dataset EGAD00001001660

• Matched Pair Cell Line Tumour RNAseq

  In this study we will sequence the transcriptome of Verified Matched Pair Cancer Cell line tumour samples. This will be married up to whole exome and whole genome sequencing data to establish a full catalog of the variations and mutations found.

  Dataset EGAD00001000630

• There are 22 pairs of LAML cases in this project which belongs to LAML-CN. The library is constructed by the Illumina protocol.

  There are 22 pairs of LAML cases in this project which belongs to LAML-CN.The library is constructed by the Illumina protocol.

  Dataset EGAD00001003317

• Kidney Single Cell Study (2018-08-20)

  We intend to use single cell transcriptome analysis to explore the heterogenity of different cell types within the kidney. . This dataset contains all the data available for this study on 2018-08-20.

  Dataset EGAD00001004304

• There are 66 pairs of LAML cases(complete genomics) in this project which belongs to LAML-CN.The library is constructed by the Completes Genomics protocol.

  There are 66 pairs of LAML cases(complete genomics) in this project which belongs to LAML-CN..The library is constructed by the Completes Genomics protocol.

  Dataset EGAD00001003310

• Tam-seq of germline samples for HGSOC copy-number signatures study

  This dataset contains targeted amplicon sequencing of Germline DNA extracted from 56 blood samples. They were sequenced on Illumina HiSeq 2500 and aligned to human genome assembly GRCh37 (hg19)to produce 127 bam files (2-3 technical replicates per sample).

  Dataset EGAD00001004172

• Harnessing transposons for drug resistance gene discovery in cancer

  This study involves a forward genetic screen to identify common insertion sites in drug resistant clones. We will be utilising piggybac transposon systems in order to generate multiple drug resistant clones in a range of human cancer cell lines.

  Dataset EGAD00001000980

• University of Miami Study on Genetics of Autism and Related Disorders (AutismDisorders)

  Autism spectrum disorders (ASD) are neurodevelopmental in origin and characterized by impairments in reciprocal social interaction and communication accompanied by restricted and repetitive patterns of interest or behavior. With improved surveillance and a broadening of the diagnostic criteria, the most recent prevalence studies suggest that ASD may affect as many as 1/166 children in the US. Treatments are limited resulting in little impact on the profound morbidity. Little is known about the etiology of ASD, but there is a strong genetic component. Genetic studies over the past decade have failed to identify definitive ASD genes, but have clearly shown that the underlying genetics are more complex than anticipated with the likelihood that multiple genes are acting independently and/or interactively. With this realization the field of ASD genetics is at a critical juncture. To move forward we must embrace new and creative paradigms to successfully dissect the genetic etiology of this disease. Specifically the current study will: Extend our ascertainment to the full range of ASD. We will increase our ASD dataset by collecting 600 families who meet clinical diagnostic criteria for the three most common ASDs: autism (AUT), Asperger disorder (ASP) and Pervasive Developmental Disorder-NOS (PDD-NOS). Phenotype assessment will be expanded to include the Social Responsiveness Scale (SRS) and detailed seizure data. Ascertainment will focus on parent-child trios. Further characterize the ASD-associated variations in the Gamma-Aminobutyric Acid (GABA) receptor (GABR) subunits. We will complete our GABR subunit variant analysis, including coding, UTR, regulatory, and conserved intronic sequence, concentrating on GABRA4 and GABRB1. We will also investigate the role of variation in other GABR subunits. All AUT specific findings will be examined in the entire ASD dataset. Identify the chromosome 19p ASD gene. Multiple genome-wide screens have provided significant evidence for linkage to Chromosome 19p and we have found evidence for significant association in the linked families within an ~3 Mb region. We will genotype 768 SNPs spaced at ~4 kb to refine the candidate region and delineate specific candidate genes for further testing. We will screen the strongest associated candidate genes for additional variants and evaluate evidence for association in the entire ASD dataset (SA5). Develop and apply the Phenotypic Homogeneity Distinction (PHD) algorithm for identification of the phenotypic signature of linkage and/or association signals. The PHD algorithm identifies phenotypic covariates that discriminate a target sample subset (e.g. the positively linked families or families carrying the associated risk allele) from its complement. The resulting PHD discriminators will define a homogeneous subset from our newly-ascertained ASD dataset to use, as a confirmatory dataset and for localization within genes under study in our other aims. Test for gene-gene interactions. To fully explain the spectrum of autism risk, we will test for interactions between genetic variations associated with ASD (such as those in GABR subunit genes). We will build upon our experience using the MDR method and extend our analyses across biological pathways using the entire ASD data set.

  Study phs000436

• Methylation biomarker study of magnesium deficiency and colorectal cancer

  Five US studies using the Mg tolerance test, the "gold standard" test of Mg status, indicated that >50% participants had Mg deficiency. In our ongoing US trial, we have found a similar result. In growing recognition of the importance of Mg in human health, very recently, Mg was selected by the US Federal Dietary Reference Intake (DRI) Committee to update the DRI. In US and other populations at high risk of Mg deficiency, high Mg intake has been linked to reduced risk of colorectal neoplasia, insulin resistance, metabolic syndrome, type 2 diabetes, and cardiovascular disease (CVD). Conversely, in populations not at high risk of Mg deficiency, high Mg intake has been related to increased risk of total mortality (e.g. total cancer, colorectal cancer, and CVD), particularly when calcium intake is low. These observations suggest that the associations between high Mg intake and disease risks may completely differ by the underlying Mg status. Due to major limitations, the Mg tolerance test is not used in conventional clinical practice and rarely used in research. Instead, serum Mg is used for clinical diagnosis. However, serum Mg performs very poorly at identifying those with Mg deficiency. There is a great need to develop implementable, sensitive, and specific biomarkers which can be easily used for identifying people with Mg deficiency. Without such a marker, it is impossible to develop effective strategies that minimize adverse effects by targeting those who, as a result of Mg deficiency, are at risk of common diseases. It is known that DNA methylation changes are inducible by environmental exposures, including nutrients, and reversible when the exposure disappears. There are two major types of cytosine modifications in DNA, 5-hydroxymethylcytosine (5-hmC) and 5-methylcytosine (5-mC). 5-mC is often associated with suppressed gene expression. 5-hmC, generated by the oxidation of 5-mC, is specifically enriched in expressed genes and plays a critical role in activating and/or maintaining gene expression. However, current epigenomic profiling platforms cannot distinguish 5-hmC from 5-mC. Just recently, our collaborator, Dr. Chuan He (HHMI Investigator), established a novel and state of the art technique, TAB-Seq and TAB-Array protocol, which can separate 5-hmC from 5-mC in the genome. Our pilot studies indicate that Mg intake or treatment significantly affects methylation capacity, 5-mC and 5-hmC biomarkers. Our findings suggest blood leukocyte 5-hmC/5-mC biomarkers may serve as more sensitive biomarkers to identify Mg deficiency than serum Mg. Thus, a comprehensive epigenome-wide association study (EWAS) may help to identify the most sensitive 5-hmC/ 5- mC biomarkers for Mg deficiency. We propose to identify 5-hmC/5-mC biomarkers for Mg deficiency by a 4- phase EWAS study in the "Personalized Prevention of Colorectal Cancer Trial [PPCCT, R01CA149633; PI, Dai and Yu]" with a total of 240 participants. Mg tolerance test will be used as the gold standard. Finally, using newly identified biomarkers, we will evaluate if 12-week Mg treatment reduces TRPM7 expression, essential in Mg homeostasis and colorectal carcinogenesis, in rectal tissues only among those with Mg deficiency.

  Study phs002037