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• 2014 chunnam AML analysis

  2014 AML analysis is conducted with samples collected from Chunnam universty. 67 paired samples are belong to this project. The study was designed to examine the molecular abnormalities from leukemic patients at initial diagnosis in comparison with corresponding germ line control (saliva samples). The results of WXS were analyzed by Mutect for ranking cancer variants and creating mutational matrix.

  Study EGAS00001001082

• Childhood Cancer Data Initiative (CCDI): Genomic Analysis in Pediatric Malignancies

  Pediatric solid tumors are highly heterogeneous, encompassing a large number of histotypes. The genomic landscape of these diseases is characterized by few single-nucleotide variants (SNVs) compared to adult cancers. In contrast, many exhibit a high prevalence of structural or epigenetic changes that alter gene expression, underlining the need for comprehensive genomic approaches such as whole-genome sequencing (WGS). Several studies have specifically addressed the clinical utility of genomic analysis in the pediatric and AYA cancer setting. Review of these studies point to key challenges that must be addressed in order to advance the routine use of genomics in this population. We have established a large collection of solid tumor tissue samples through our biobanking efforts. Where possible, we obtain longitudinal samples from the same patient. These primary patient samples and their corresponding germline have been analyzed using whole genome and whole transcriptome sequencing methods and have been linked to clinical metadata using both manual curation and robust methods for automatic extraction from the electronic health record (EHR). Importantly, research-grade genomic analysis is performed in parallel to our CLIA-grade sequencing (“UCSF500”) efforts for some of the patients in this study cohort and have been submitted as part of the American Association for Cancer Research's project GENIE and/or the National Childhood Cancer Registry. For our sequenced tumor samples, we have retrospective clinical data and ongoing efforts to prospectively record key events throughout the patient's cancer journey. In our solid tumor program, we have developed many patient-derived xenograft models and a number of PDX-derived cell lines. These unique models have been evaluated using genomic and functional approaches including (in some cases) treatment with conventional chemotherapy or investigational agents. Lastly, these samples were collected from a population that is among the most diverse in the nation and includes significant numbers of Asian, Latino, Indigenous and African-American patients, groups that are traditionally underrepresented in many banking efforts.

  Study phs002430

• Center for Common Disease Genomics [CCDG] Neuropsychiatric: Autism Spectrum Disorder (ASD) – Whole Exomes

  The National Human Genome Research Institute (NHGRI) has funded a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Called the Centers for Common Disease Genomics (CCDG), this initiative will explore a range of diseases with the ultimate goal of 1) undertaking variant discovery for enough different examples of disease architectures and study designs to better understand the general principles of the genomic architecture underlying common, complex inherited diseases, 2) understanding how best to design rare variant studies for common disease, and 3) developing resources, informatics tools, and innovative approaches and technologies for multiple disease research communities and the wider biomedical research community. The initial focus of the CCDGs will be in cardiovascular disease (early-onset coronary artery disease, atrial fibrillation, hemorrhagic stroke), neuropsychiatric disease (epilepsy, autism), and autoimmune/inflammatory disease (type 1 diabetes, inflammatory bowel disease). The Broad Institute is one of four selected CCDG project centers. The goal of the Autism Spectrum Disorder (ASD) program is to work together to utilize dramatic new advances in DNA sequencing technology to reveal the genetic architecture of autism through comprehensive examination of the exotic sequence of all genes.

  Study phs002502

• Risk-Stratified Therapy for Acute Myeloid Leukemia in Down Syndrome

  Study ID: Children's Oncology Group (COG) - AAML1531NCT Number: NCT02521493Trial Title: Risk-Stratified Therapy for Acute Myeloid Leukemia in Down SyndromeSubmitted in collaboration with the NCTN/NCORP Data ArchiveData presented in the following publication(s): 34320162 Disease type(s): Hematopoietic Neoplasm/Leukemia - Acute Myeloid Leukemia; Hematopoietic Neoplasm/Leukemia - Myelodysplastic SyndromeDataset(s) included:NCT02521493-D1: There are 2 datasets associated with PMID 34320162, NCT02521493-D1 through NCT02521493-D2. The NCT02521493-D1 dataset is a patient level dataset (single row per patient) containing patient characteristics, laboratory findings, and outcome for eligible myeloid leukemia in children with Down syndrome (ML-DS) enrolled on the AAML1531 clinical trial.NCT02521493-D2: There are 2 datasets associated with PMID 34320162, NCT02521493-D1 through NCT02521493-D2. The NCT02521493-D2 dataset is an adverse event level dataset (single row per adverse event, period, and patient) containing information of the micro-organisms associated with adverse events by period in the AAML1531 clinical trial.

  Study phs004081

• Targeted_Pulldown_Validation_of_mutations_found_in_whole_genome_sequencing

  This experiment is to inform us of the validity of using pre-made library material to perform a bespoke pulldown experiment to validate the mutations found between the whole genome sequencing of the DNA from the same individuals cancer and normal material. This is to identify the valid and informative mutations in cancer genomes.

  Study EGAS00001000260

• Limited Association between HRR Gene Alterations and HRD in Molecular Tumor Board Cancer Samples: Who should be tested for HRD?

  Alterations in Homologous Recombination Repair (HRR) Pathway genes have been found to be associated with HR-Deficiency (HRD), which is an approved biomarker for PARP Inhibitor (PARPi) treatment. The aim of a Molecular Tumor Board (MTB) is to identify molecular alterations in cancer patients with advanced tumors that may suggest off-label treatment options. So far, few studies have analyzed the presence of HRR gene mutations and their association with HRD outside of clinical studies. Currently, no data on HRD testing in the setting of a MTB have been published. For the present study, a cohort of 237 patients encompassing 24 different tumor entities was collected from the MTB of the Comprehensive Cancer Center Erlangen-EMN. We show that an elevated Genomic Instability Score (GIS ≥ 42) can occur in samples with and without mutations in HRR-related genes. Overall, 38.1% of cancer samples with BRCA1/2 mutations, 10.9% of tumors with alterations in HRR genes other than BRCA1/2, and 4.3% of cancer samples without HRR gene mutations harbored an elevated GIS. Notably, our data show that various inactivating BRCA1/2 mutations are not associated with an elevated GIS. Taken together, panCancer assessment of HRD in addition to BRCA1/2 and other HRR gene mutational analysis is recommended to guide decisions regarding PARPi treatment. Further studies are needed to establish thresholds for GIS in non-ovarian cancer entities. Finally, HRD can be observed in 4.3% of BRCA1/2 and other HRR gene wildtype cancer samples, and may emerge as an independent biomarker for PARPi in the future.

  Study EGAS00001008063

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Kazakhs (DNA samples from the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan; Gulnara Svyatova, Principal Investigator

  Whole genome sequencing of 100 unrelated Kazakhs in order to impute genotypes into PE cases and controls from Kazakhstan and to provide genetic data and infrastructure for future genetic studies in Kazakhstan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This dataset is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators at the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan (Gulnara Svyatova, Principal Investigator)

  Dataset EGAD00001005467

• exploration of biomarkers discriminating squamous cell carcinoma from other lung cancers

  Targeted therapies based on the molecular and histological features of cancer types are becoming standard practice. The most effective regimen in lung cancers is different between squamous cell carcinoma (SCC) and adenocarcinoma (AD). Therefore a precise diagnosis is crucial, but this has been difficult, particularly for poorly differentiated SCC (PDSCC) and AD without a lepidic growth component (non-lepidic AD). Biomarkers enabling a precise diagnosis are therefore urgently needed. To achieve this goal, we initially performed CAGE (Cap Analysis of Gene Expression) to quantify promoter activities on 97 frozen tissues from surgically resected lung cancers (22 SCC and 75 AD). We furhter expanded the transcriptome profiling to cover additional 48 malignant neoplasm of bronchus and lung, including mesothelioma and metastatic lung cancers derived from other tissues.

  Study JGAS000488

• Molecular evolution and clinical trajectories of prostate cancer identifies novel markers for risk stratification

  Prostate cancer is a highly heterogeneous disease that is thought to develop over many years. Identifying the earliest somatic changes can give important insights into the tumour evolution and aid in stratifying high- from low-risk diseases. Here we pursued integrative whole-genome, transcriptome and methylome-based analysis of early-onset prostate cancer patients. Characterisation of genomic alterations across 270 PCa tumours revealed age-related genomic alterations and mutation signatures including BRCAness and APOBEC. We used methylation- and expression-data to identify four molecular subgroups, which included a highly aggressive tumour subgroup that frequently involved recurrent duplications and increased expression of ESRP1. Analysis of 12,000 tissue-microarray tumour samples demonstrated that ESRP1 is a candidate biomarker associated with faster proliferation rate and shorter time to relapse. We combine the patterns of molecular co-occurrence, risk-stratification and subgroup information to deconvolute tumor heterogeneity, which reveal complex but recurrent clinical trajectories of prostate cancer.

  Study EGAS00001002923

• Search for genetic variants influencing gestational weight gain in type 1 diabetes patients by genome wide association method

  Clinical data suggest that BMI and gestational weight gain (GWG) are strongly interconnected phenotypes, however the genetic basis of the latter is rather unclear. Here we aim to investigate the genetic factors associated with GWG from the perspective of the genetics of obesity.

  Study EGAS00001004408