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• Integrative_genome_profiling_in_AML

  AML emerges as a consequence of accumulating independent genetic aberrations that direct regulation and/or dysfunction of genes resulting in aberrant activation of signalling pathways, resistance to apoptosis and uncontrolled proliferation. Given the significant heterogeneity of AML genomes, AML patients demonstrate a highly variable response rate and poor median survival in response to current chemotherapy regimens. For the past 4 years we have conducted gene expression profiling on purified bone marrow populations equating to normal haematopoietic stem and progenitor cells from healthy subjects and patients with de novo AML in order to identify AML signatures of aberrantly expressed genes in cancer versus normal. We are now applying a series of bioinformatic methodologies combined with clinical and conventional diagnostic data to establish novel genomics strategies for improved prognostication of AML. Additionally, we use our AML signatures to unravel oncogenic signalling pathway activities in AML patients and test inhibitory drugs for these pathways inn preclinical therapeutic programmes. We consider that superimposing GEP and clinical data for our AML patient cohort with additional data on their mutational status will significantly improve the prognostic power of the study as well as unravel yet unknown mutations associated with aberrant signalling activities of oncogenic pathways.

  Study EGAS00001000858

• SALTO: chromosomal copy number alterations to predict response to bevacizumab

  Study of the correlation between vessel formation and or CMS subtypes in relation to a predictive copy number marker for bevacizumab. Shallow Whole Genome Sequencing of 92 mCRC samples.

  Study EGAS50000000711

• RNA sequencing

  For RNA sequencing: All sample numbers starting with 6717 are tumor samples which has been sequenced using transcriptomics (see BAM files). It concerns biopsies of metastatic lesions from patients with BRAFV600 mutated melanoma, obtained before, during and after the study treatment (see samples metadata). RNA sequencing is performed using the Illumina Novaseq 6000 system.

  Dataset EGAD50000000383

• scRNAseq dataset of circulating T cells in FL patient before and after Lenalidomide treatment

  scRNAseq dataset of circulating T cells from 3 FL patients (P011, P014 and P020) included in the GALEN clinical trial. There is two time points for each patient : One before treatment (D0) and one at day 7 of Lenalidomide treatment (D7).

  Dataset EGAD50000001529

• NICOLA QUB Genetic

  Blood-derived DNA was obtained from samples within the NICOLA cohort. Genetic data was generated using the Illumina Infinium CoreExome-24 array (Illumina, USA) and is available for 2,978 participants (551,839 directly genotyped and 18,148,478 imputed single nucleotide polymorphisms following initial quality control). Genetic .bed .bim and .fam files are available.

  Dataset EGAD00010002762

• RNAseq data for 6 samples from the DEV cell line

  - Six samples from the DEV cell line: 2 controls, 2 transduced with IL4R WT and 2 transduced with IL4R mutant (I242N) - This DEV cell line is not commercially available and was acquired from a colleague in the Netherlands

  Dataset EGAD00001003908

• Shallow whole genome sequencing from plasma DNA of BC, CRC and NSCLC patients

  This is the raw data obtained from shallow whole-genome sequencing of plasma DNA (plasma-Seq) for calling of somatic copy number alterations as well as focal amplifications and deletions from patients with breast, colorectal and non-small cell lung cancer.

  Dataset EGAD00001006288

• KNS42 and SF188 H3K36me3 chipSeq

  Chromatin immunoprecipitation (ChIP) was carried out employing antibodies against H3K36me3 and RNA polymerase II using the HistonePath and TranscriptionPath assays by ActiveMotif. Whole genome sequencing was carried out using an Illumina HiSeq2000 and data is provided as 6 BAM files. H3K36me3 chipseq RNA polymerase II chipseq and input coverage for each cell line.

  Dataset EGAD00001004119

• RNA-Seq Dataset of Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  We generated and characterized tumoroids from small cell carcinoma of the ovary, hypercalcemic type. Furthermore, we identified a drug that is selective and effective against SCCOHT tumoroids.

  Dataset EGAD00001015441

• SG10K_Pilot Dataset: Whole genome sequencing data of 4810 individuals from Singapore

  Genomic data obtained from the joint processing and variant calling of 4,810 individuals from Singapore. VCF files are by Chromosome (chr. 1-22 plus X) for all 4,810 individuals. Self-reported ethnicity is found in the "Region" column of metadata file.

  Dataset EGAD00001005337