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• A single-cell transcriptional gradient in human cutaneous memory T cells restricts Th17/Tc17 identity

  We identified a gradated transcriptional program of coordinately regulated inflammation-suppressive genes in psoriatic resident memory T cells. This dataset includes bulk RNA-seq for CRISPR-based deactivation of two core components of this inflammation-suppressive program, ZFP36L2 and ZFP36, in human PBMCs. It also includes scRNA-seq of cutaneous immune cells from psoriasis patients before and during therapeutic IL-23 blockade.

  Study EGAS00001006716

• Cell line data (RNAseq, ATACseq, ChIPseq)

  Content: 2 GB RTK I cell lines (LN229, ZH487) in two conditions (NT control and shSOX10). RNAseq: single replicates per condition, polyA+ RNA sequencing, SE. ATACseq: biological replicates per condition, SE. ChIPseq (histone H3 modifications, LN229 only): all marks for each condition were pooled and sequenced on two lanes for each pool. ChIPseq (BRD4 and SOX10): SOX10 libraries were sequenced on single lanes. BRD4 samples were multiplexed and sequenced in two lanes. ChIPseq input samples are also included. Data type and technology: RNAseq: SE 50bp sequenced on HiSeq2000/4000. ATACseq: SE 50bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000.

  Dataset EGAD00001005493

• MutWP5: CRUK Mutographs of Cancer: Lung: PD37920 (Targeted) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Targeted sequencing will be conducted on samples to identify drivers of interest and clonality of the samples, well-performing samples will be sent for subsequent whole-genome sequencing. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006929

• Shallow whole genome sequencing and targeted capture sequencing data of PCNSL and PTL primary and relapse pairs

  Shallow whole genome sequencing for copy number analysis and targeted capture sequencing data for translocation and mutation anslysis of paired primary and relapse PCNSL and PTL samples

  Dataset EGAD00001008387

• Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect the cell type heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Whole exome sequencing and transcriptome analysis in various in vitro and in vivo contexts was performed to study the influence of the TME on the CRC phenotype.

  Dataset EGAD00001011173

• MutWP5: CRUK Mutographs of Cancer: Lung: PD38234 (Targeted) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from explanted lung from pulmonary fibrosis patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Targeted sequencing will be conducted on samples to identify drivers of interest and clonality of the samples, well-performing samples will be sent for subsequent whole-genome sequencing. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005925

• Follicular lymphoma shallow whole genome sequencing and targeted sequencing of lymphoma panel

  Stage I and stage III/IV Follicular lymphoma samples, shallow whole genome sequencing for copy number analysis and targeted capture sequencing for mutation and translocation analysis.

  Dataset EGAD00001008385

• ExomeSeq-EGAS00001001306

  Exome Sequencing. 3 μg of genomic DNA from each sample were sheared and used for the construction of a paired-end sequencing library as described in the paired-end sequencing sample preparation protocol provided by Illumina41. Enrichment of exonic sequences was then performed for each library using either the Sure Select Human All Exon 50 Mb or All Exon+UTRs v4 kits following the manufacturer’s instructions (Agilent Technologies). Exon-enriched DNA was pulled down by magnetic beads coated with streptavidin (Invitrogen), followed by washing, elution and 18 additional cycles of amplification of the captured library. Enriched libraries were sequenced (2 × 76 bp) in one lane of an Illumina GAIIx sequencer or in two lanes of a HiSeq2000 when using pools of eight samples.

  Dataset EGAD00001001464

• Axes of Biological Variation in Diffuse Large B-Cell Lymphoma

  To explore the DLBCL molecular and genetic environment, we conducted genome-wide NGS sequencing on 103 DLBCL biopsy samples (named as Cornell-NCI cohort) with NGS platforms, including bulk WES, etc. The raw fastq files of the bulk WES were deposited on the EGA for user access. To obtain other genomic data from the study, please see the data links described in the paper.

  Study EGAS50000001227

• Bladder Cancer Organoids as a Functional System to Model Different Disease Stages and Therapy Response

  The study 'Bladder Cancer Organoids as a Functional System to Model Different Disease Stages and Therapy Response' reports the genomic characterization at the single allele level upon Whole Exome Sequencing of Bladder Cancer (BLCa) Patient Tumor (PT) samples obtained from 18 patients and corresponding Patient Derived Organoids (PDOs), implementing the SPICE pipeline (Ciani Y et al). Our cohort included 21 PTs and 22 PDOs. In this study, we generated a unique biobank resource of BLCa organoids that encompasses a broad spectrum of disease stages. We demonstrated that PDOs retain cancer heterogeneity and mutational burden. Furthermore, we observed that BLCa PDO can have different morphologies which may reflect tumor-specific features. Indeed, a solid morphology may be associated with more advanced tumors, as supported by the high PDO genomic burden and high primary tumor stage. Moreover, with our drug screening pipeline, we demonstrated the clinical relevance and feasibility of using a BLCa PDO-based drug assay for comparing the standard of care (SOC) drugs with compounds not currently in use for BLCa. Response to SOC was highly heterogeneous with approximately 50% of non-muscle invasive bladder cancer and 33% of muscle invasive bladder cancer PDOs showing no or minimal response. The most effective targeted therapy was lapatinib. We used an integrative analysis of drug response profiles with matched PDO genomic analysis to determine enrichment thresholds for candidate markers of therapy resistance and sensitivity. Importantly, by assessing the clinical history of longitudinally sampled cases, the clonal evolution of the disease could be determined and matched with PDO drug response profiles.

  Study phs003149