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• German early-onset prostate cancer cohort of the Pan-Prostate Cancer Genome (PPCG) project

  Prostate cancer is the most frequent malignant tumor in males and the second most frequent cause of cancer-related death. Currently, in Germany, more than 60,000 prostate cancers are diagnosed every year. Although most of these patients are treated in a curative attempt, more than 10,000 German men die from prostate cancer annually. Owing to the demographic changes of our society, a further doubling of prostate cancer incidences during the next 20 years is expected. Prostate cancer is generally considered a tumor of elderly men. However, a fraction of prostate cancers are diagnosed at the age of 55 years or less. For several reasons, these “early onset prostate cancers” may represent a key entity for the understanding of prostate cancer biology. First, it is likely that early onset prostate cancers represent a distinct molecular subgroup of prostate cancer (PCa), potentially characterized by relatively small numbers of genetic changes, some of which may be particularly strong driver mutations for PCa development. Second, a fraction of prostate cancers in young individuals could represent classical prostate cancers that are detected at a very early stage and might therefore have accumulated molecular changes/mutations occurring that are most instrumental for prostate cancer early detection. Third, PCa with hereditary backgrounds are likely to accumulate in the age group below 55 years. A comparison with other sample sets (e.g. from other ICGC consortia), a systematic genomic analysis of young men with PCa could therefore lead to the detection of mechanisms for hereditary PCa. Fourth, a better understanding of these tumors is particularly relevant as finding optimal treatment regimens is most critical in young cancer patients. We are analyzing the entire genomic DNA sequences of at least 200 PCas (and matched non-tumorous DNA) of young men (≤ 55y), to at least 30 fold coverage, and integrate single-nucleotide variants and genomic structural variations with differential methylation, mRNA and miRNA expression data.Tissues were collected at the University Medical Center Hamburg-Eppendorf. Sequencing was performed at DKFZ and NCT (Heidelberg), EMBL (Heidelberg), and MPIMG (Berlin). Data management and bioinformatic data analyses is being conducted at DKFZ.

  Study EGAS00001003373

• Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers

  The current understanding of tumorigenesis is largely centered on a monogenic driver oncogene model. This paradigm is incompatible with the prevailing clinical experience in most solid malignancies: monotherapy with a drug directed against an individual oncogenic driver typically results in incomplete clinical responses and eventual tumor progression1-7. By profiling the somatic genetic alterations present in over 2,000 cases of lung cancer, the leading cause of cancer mortality worldwide, we show that combinations of functional genetic alterations, i.e. genetic collectives dominate the landscape of advanced-stage disease. We highlight this polygenic landscape and evolution of advanced-stage non-small cell lung cancer (NSCLC) through the spatial-temporal genomic profiling of 7 distinct tumor biopsy specimens and 6 plasma specimens obtained from an EGFR-mutant NSCLC patient at (1) initial diagnosis of early-stage disease, (2) metastatic progression, (3) sequential treatment and resistance to 2 EGFR inhibitors, (4) death. The comprehensive genomic analysis of this case, coupled with circulating free (cf) tumor DNA profiling of additional advanced-stage EGFR-mutant NSCLC clinical cohorts with associated treatment responses uncovered features of evolutionary selection for multiple concurrent gene alterations: including the presence of EGFR inhibitor-sensitive (EGFRL858R;EGFRexon19del) or inhibitor-resistant (EGFRT790M;EGFRC797S) forms of oncogenic EGFR along with cell cycle gene alterations (e.g. in CDK4/6, CCNE1, RB1) and activating alterations in WNT/β-catenin and PI3K pathway genes, which our data suggest can cooperatively impart non-redundant functions to limit EGFR targeted therapy response and/or promote tumor progression. Moreover, evidence of an unanticipated parallel evolution of both EGFR T790M and two distinct forms of oncogenic PIK3CA was observed. Our study provides a large-scale clinical and genetic dataset of advanced-stage EGFR-mutant NSCLC, a rationale for specific polytherapy strategies such as EGFR and CDK4/6 inhibitor co-treatment to potentially enhance clinical outcomes, and prompts a re-evaluation of the prevailing paradigm of monogenic-based molecular stratification for targeted therapy. Instead, our findings highlight an alternative model of genetic collectives that operate through epistasis to drive lung cancer progression and therapy resistance.

  Study EGAS00001002604

• TK-EPN862 - Patient-dervied xenograft model of Posterior Fossa A Ependymoma - RNAseq

  Ependymomas (EPN) are the third most common malignant brain cancer in children. Treatment strategies for pediatric EPN have remained unchanged over recent decades, with 10-year survival rates stagnating at just 67% for children aged 0-14 years. Moreover, patients who survive treatment for the most common subtype of pediatric EPN (posterior fossa A (PFA)), often suffer long-term neurological side effects as a result of therapy. It is evident that there is a need for safer, more effective treatments for pediatric EPN patients. There are ten distinct subgroups of EPN, each with their own molecular and prognostic features. To identify and facilitate the testing of new treatments for EPN, in vivo laboratory models representative of the diverse molecular subtypes are required. Here, we describe the establishment of a patient-derived orthotopic xenograft (PDOX) model of PFA EPN, derived from a metastatic cranial lesion. Patient and PDOX tumors were analyzed using immunohistochemistry, DNA methylation profiling, whole genome sequencing (WGS) and RNA sequencing. Both patient and PDOX tumors classified as PFA EPN by methylation profiling, and shared similar histological features consistent with this molecular subgroup. RNA sequencing revealed that gene expression patterns were maintained across the primary and metastatic tumors, as well as the PDOX. Copy number profiling revealed gains of chromosomes 7, 8 and 19, and loss of chromosomes 2q and 6q in the PDOX and matched patient tumor. No clinically significant single nucleotide variants were identified, consistent with the low mutation rates observed in PFA EPN. Overexpression of EZHIP RNA and protein, a common feature of PFA EPN, was also observed. Despite the aggressive nature of the tumor in the patient, this PDOX was unable to be maintained past two passages in vivo. Others who have successfully developed PDOX models report some of the lowest success rates for EPN compared to other pediatric brain cancer types attempted, with loss of tumorigenicity not uncommon, highlighting the challenge in propagating these tumors in the laboratory. Here, we discuss our collective experiences with PFA EPN PDOX model generation and propose potential approaches to improve future success in establishing preclinical EPN models

  Study EGAS00001006844

• Vietnam_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Vietnam

  Dataset EGAD00010001733

• Tanzania_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Tanzania

  Dataset EGAD00010001743

• Kenya_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Kenya

  Dataset EGAD00010001742

• Malawi_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Malawi

  Dataset EGAD00010001741

• Cameroon_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Cameroon

  Dataset EGAD00010001740

• BurkinaFaso_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:BurkinaFaso

  Dataset EGAD00010001739

• Gambia_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Gambia

  Dataset EGAD00010001738

• Mali_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Mali

  Dataset EGAD00010001737

• Nigeria_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Nigeria

  Dataset EGAD00010001736

• PNG_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:PNG

  Dataset EGAD00010001735

• Ghana_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Ghana

  Dataset EGAD00010001734

• MalariaGEN_GWAS-2.5M_b37_aligned_phased

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations: phased genotypes

  Dataset EGAD00010001748

• MalariaGEN_Gambia-HLA_typing

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations: Gambian trio HLA typing

  Dataset EGAD00010001818

• SAFIR02_Cytoscan

  Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_cytoscan)

  Dataset EGAD00010002239

• Single Cell RNA-Seq

  Examination of Sample Multiplexing Reagents for Single Cell RNA-Seq. Nine techniques applied to samples from four PDX models: #105, #177, #233, #264

  Dataset EGAD50000000216

• Induced pluripotent stem cell derived pericytes respond to mediators of proliferation and contractility

  Differentiation of mesoderm pericytes from induced pluripotent stem cell lines.

  Study EGAS50000000176

• Breast Invasive Lobular Carcinoma CDH1 WGS dataset

  We subjected to whole genome sequencing (WGS) one ILC case lacking CDH1 biallelic mutations. Both tumor and normal samples were sequenced.

  Dataset EGAD50000000696

• Roifman DAC

  This Data Access Committee will oversee all requests for data submitted by Dr. Chaim Roifman at the Hospital for Sick Children in Toronto, Canada. Requests should be directed by email to chaim.roifman@sickkids.ca.

  Dac EGAC50000000396

• RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Transcriptomic analysis of K7M2 murine osteosarcoma cells stably modified to overexpress or repress CYR61

  Dataset EGAD50000000747

• Phenotype-modifier genes in FHHNC

  Whole exome sequencing data in FHHNC patients stratified in extreme phenotypes to identify potential phenotype modifier variants

  Dataset EGAD50000001217

• VHIR Renal Physiopathology Group DAC

  This DAC describes the members of the Data Access Committee and the policy that will regulate access to the datasets uploaded at EGA from the Renal Phyisiopathology Group at VHIR

  Dac EGAC50000000510

• Picuris Pueblo Genomic Project – Modern Dataset

  Please refer to the Supplemental Materials of the paper for more information.

  Dataset EGAD50000001245