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• Studying the single cell characteristics of pancreatic cancer

  Pancreatic cancer is a dangerous malignancy in the pancreas. In this study we use single-cell RNA sequencing technique to help understand the transcriptome characteristics of pancreatic tumor cells. This study help understands the complex microenvironment of pancreatic tumors and will likely to benefit clinical research of pancreatic cancer treatments.

  Study EGAS00001003889

• Multi-omics of Richter syndrome

  Richter syndrome (RS) is the aggressive transformation of Chronic Lymphocytic Leukemia, mostly with Diffuse Large B-Cell Lymphoma histology. While histologically similar, RS and de novo DLBCLs present with different clinical courses. We characterized the RS epigenome by combining genome-wide DNA methylation with transcriptome-sequencing on a large RS cohort.

  Study EGAS00001005495

• Cerebrospinal fluid circulating tumour DNA allows the characterisation and monitoring of medulloblastoma

  The molecular characterisation of medulloblastoma, the most common paediatric brain tumour, is crucial for the correct management and treatment of this heterogenous disease. In this study we show that CSF ctDNA allows the molecular characterisation and monitoring of medulloblastoma. This can ultimately facilitate the clinical management of medulloblastoma patients.

  Study EGAS00001004651

• Genomic characterization of metastatic breast cancers

  While large efforts have been done to characterize early breast cancer, little is known about the genomic landscape of metastatic breast cancer. In the present study, we performed whole exome sequencing of 629 metastatic breast cancers, in order to identify new candidate targets and better stratify patients eligible for innovative therapies.

  Study EGAS00001003290

• CRISPR_single_cell_activation

  Single cell CRISPR activitaion analysis with 96 genes with the aim to build a quantative CRISPR activation model. 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/

  Study EGAS00001005528

• Melanoma_post_mortem_analysis

  This is a targeted pulldown validation in support of the existing whole-genome sequencing study of melanoma metastases (Canapps ID:1888). We are studying the genomic evolution of cutaneous melanoma metastases. In this pulldown analysis we are specifically sequencing the subclonal variants that we believe account for the variability between the metastases.

  Study EGAS00001003531

• Multi-region RNA sequencing of tumour regions and tumour-adjacent normal lung tissue

  TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).

  Study EGAS00001006517

• Correction of FFPE artefacts in WGS data

  The ability to precisely characterise mutational signatures from FFPE-derived DNA has tremendous translational potential. However, sequencing of DNA derived from FFPE material is known to be riddled with artefacts. To correct for this, we introduce FFPEsig, a computational algorithm to rectify the formalin-induced artefacts in the mutational profile.

  Study EGAS00001005331

• Identification of drug resistance genes in melanoma by small RNAs expression analysis

  We aim to sequence the small RNAs of 22 human melanoma cell lines in biological triplicate in order to define the microRNAs expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistance 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 EGAD00001003245

• Identification of drug resistance genes in melanoma by mRNA gene expression

  We aim to sequence the mRNA transcriptome of 22 human melanoma cell lines in biological triplicate in order to define the gene expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistance 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 EGAD00001003244