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• Induction Failure in Childhood and Young Adult T-cell Acute Lymphoblastic Leukemia

  We carried out WGS and RNAseq on a cohort of 48 children and young adults with induction failure in T-cell Acute Lymphoblastic Leukemia (T-ALL) to identify genomic drivers of treatment resistance. The study includes WGS for 33 tumour/normal pairs and 15 tumour-only samples. In addition, there is RNAseq data for 37 cases.

  Dataset EGAD00001009058

• Single Cell Genome Sequence for DLP+ library A96210B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1047B on DLP+ library A96210B

  Dataset EGAD00001009475

• Sequencing data for oesophageal and related samples - Abbas et al (WGS)

  Data supporting: "Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma" Abbas et al (WGS for 1397 samples)

  Dataset EGAD00001011196

• Immune Response Targeted Panel + B/TCR Profiling + AbSeq + Sample Tag Multiplexing

  Multiomics data for a cohort of 20 COVID-19 patients (10 patients mild, 3 patients moderate, 4 patients severe, 3 patients critical) obtained from peripheral blood mononuclear cells (PBMCs) from longitudinally sampled at hospital admission, discharge, and 1 month thereafter. The data has been obtained a multiwell-based single-cell technology (BD Rhapsody) that includes the targeted expression of BD Immune Response Targeted Panel, the TCR/BCR profiling and a set of 52 surface proteins. The samples of the different patients at different collection times were labelled using a cell hashing strategy with the BD Single-Cell Multiplexing Kit (6 samples for each run).

  Dataset EGAD00001011319

• A new subgroup of hepatocellular adenomas with sonic hedgehog pathway activation

  Using sequencing and gene expression analyses, we identified a subgroup of HCA characterized by fusion of the INHBE and GLI1 genes and activation of sonic hedgehog pathway. Molecular subtypes of HCAs associated with different patients’ risk factors for HCA, disease progression, and pathology features of tumors. This classification system might be used to select treatment strategies for patients with HCA. Related Publication: Molecular Classification of Hepatocellular Adenoma Associates With Risk Factors, Bleeding, and Malignant Transformation Nault, Jean-CharlesLaurent, Christophe et al. Gastroenterology , Volume 152 , Issue 4 , 880 - 894.e6 http://dx.doi.org/10.1053/j.gastro.2016.11.042

  Dataset EGAD00001003092

• RNA data for MMML (EGAS00001002422)

  RNA sequencing data for MMML (3 tumor samples and 1 gcbcell)

  Dataset EGAD00001003285

• WGS data for MMML (EGAS00001002422)

  Whole genome sequencing data for MMML (7 tumors and 8 controls)

  Dataset EGAD00001003286

• RNA-Seq data for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  RNA-Seq data for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  Dataset EGAD00001003433

• Sequencing data for oesophageal and related samples - Alex Frankell et al (WGS)

  Data supporting: "The landscape of selection in 551 Esophageal Adenocarcinomas defines genomic biomarkers for the clinic." Frankell et al. WGS (BAM files) 379 matched tumour-normal pairs

  Dataset EGAD00001004417

• Identification of drug resistance genes in melanoma

  Our aim is to analyze the genome of human melanoma cell lines and short term culture from human melanoma samples in order to identify genes that confer drug resistance to clinically relevant targeted therapies. We will perform whole-exome sequencing, copy number variation analysis and methylome analysis in a collection of human melanoma cell lines and short term culture that will be then screened for drug sensitivity/resistance through a library of clinically relevant drugs and drug combinations. By the combined analysis of the genomic lesion and the drug sensitivity/resistance profile of different cell lines, we will look for genes whose mutation is associated to the sensitivity or resistance to a specific drug in different samples.

  Dataset EGAD00001001124