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• Whole Exome Sequencing of 60 tumor/normal matched liver Cancers (HCC)

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 60 whole exome tumor/normal pairs with matched RNA-seq.

  Dataset EGAD00001004180

• ICU transcriptomics: Assessing the role of the host immune response in patients with ventilator-associated pneumonia

  This is a study of 100 patients with the aim to provide transcriptomic sequencing data analysis of cells isolated from bronchioalveolar lavage and blood samples from critically ill patients with pneumonia on an intensive care unit in order to investigate the host contribution to disease. 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/

  Dataset EGAD00001015407

• WGS and WES of Advance Prostate Cancer

  The dataset consists of BAM files of 2 pairs of matched tumor/normal samples of a men with advanced prostate cancer. One pair is whole genome sequencing: WGS_T/WGS_N for tumor and normal samples, respectively; and the other pair is whole exome sequencing: WES_T/WES_N for tumor and normal specimens, respectively. Details can be found at the publication titled: "Molecular Medicine Tumor Board: Whole Genome Sequencing to Inform on Personalized Medicine for a Man with Advanced Prostate Cancer"

  Dataset EGAD00001006487

• Melanoma post mortem analysis

  This is the affymetrix gene expression data of the metastatic tumours related to this study.

  Dataset EGAD00010001717

• Tumor Profiler DAC

  The Tumor Profiler DAC is responsible for the access to data generated in the Tumor Profiler Study.

  Dac EGAC50000000199

• Dataset that contains analyses of submission 6

  This is the description of analyses dataset of submission 6

  Dataset EGAD50000001107

• RBtargetedSeq

  Retinoblastoma is a rare childhood cancer of the retina. We studied retinoblastoma by Targeted Sequencing.

  Dataset EGAD00001008004

• A Clone's Genomic Stability as a Biomarker of Its DNA-Damage Resilience

  A main problem in the treatment of advanced cancers, including gastric cancers and glioblastoma, is the incertitude at which we predict how individual patients will respond to DNA-damaging agents, especially on the long run. Knowing the mechanism behind a patient's response, or the lack thereof, will help us depart from the oversimplified “more-is-better” and “one-size-fits-all” principles according to which DNA-damaging agents are administered. This will improve clinical outcome by allowing us to pinpoint those who would respond better and longer to lower doses than to higher doses of DNA-damaging agents. Under the assumption that the success of DNA-damaging therapy increases with the proliferation rate of a relatively homogeneous tumor population, there was little reason to assume anything other than monotonic dose-response relations. With the recent paradigm shift that most cancers are in fact DNA mosaic products of ongoing evolution, comes the urgency to reconsider these fundamental principles behind DNA-damaging therapy administration. As the developers of one of the first DNA deconvolution methods and with access to technologies to profile the transcriptomes of up to 10,000 cells simultaneously, we are equipped to embark on first personalized dose-finding strategies for DNA-damaging therapies. We will test the potential of the very long-term legacy that DNA-damage entails on a cell “genomic instability” as new biomarker of DNA-damage response. Our preliminary studies showed that, for most cancer types, DNA-damaging agents change a clone's genomic instability and that clones succumb to a limit in the amount of genomic instability they can tolerate. In particular, our results showed that patients with intermediate genomic instability have a very poor outcome and that this relation is only evident among treatment-naive patients, but not among patients treated with DNA-damaging agents. Further they show that we can measure genomic instability per clone and that clones with extreme genomic instability typically don't grow large. Our hypothesis that genomic instability, rather than proliferation rate, determines how sensitive a tumor is to DNA-damaging agents on the long-term, is founded on two unexpected findings. Patients with extremely high genomic instability per tumor clone have an exceptionally good outcome. Aim 1 will integrate exome- and single cell RNA-Seq (scRNA-Seq) data to characterize clones and to measure how much genomic instability they can tolerate. Low genomic instability is associated with reduced benefit from DNA-damaging agents. Aim 2 will use comet assays and treatment history to quantify DNA damage per clone, relating it to the clones' ability to tolerate DNA damage and to changes in the genomic instability of therapy-surviving clones.

  Study phs003762

• DAC Johns Hopkins University - AML scRNAseq study

  This is the Data Access Committee (DAC) from Johns Hopkins University for the study scRNAseq of acute myeloid leukemia

  Dac EGAC50000000242

• CNCD Recall by Genotypes

  This is a DAC to handle recall by genotype studies by the conducted by the Center for Non-Communicable Disease Karachi, Pakistan.

  Dac EGAC50000000937