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• Single-cell RNA sequencing of human skin tumors (BCC, SCC and Melanoma)

  Cancer-associated fibroblasts (CAFs) play a key role in cancer progression and treatment outcome. Here, we elucidate the yet unresolved intra-tumoral CAF variety in three skin cancer types at molecular and spatial single-cell resolution in a large cohort. We show that two out of three CAF subtypes contribute to tumor immune surveillance with distinct mechanisms. Matrix CAFs (mCAFs) ensheath tumor nests and synthesize extracellular-matrix to prevent T cell invasion. Immunomodulatory CAFs (iCAFs), which express proinflammatory and immunomodulatory factors, are only detected in high abundance in aggressive tumors. Strikingly, iCAFs but not tumor cells are (apart from immune cells) the exclusive cell type producing chemokines and, thus, play a key role in immune cell recruitment and activation. Mechanistically, we show that cancer cells transform adjacent healthy fibroblasts into cytokine-expressing iCAFs, which subsequently recruit immune cells and modulate the immune response. In conclusion, targeting CAF variants holds promise for improved efficacy of immunotherapy.

  Study EGAS50000000365

• Comprehensive spatial landscape and plasticity of immunosuppressive fibroblasts in breast cancer

  Although immunosuppressive and pro-metastatic functions of FAP+ Cancer-Associated Fibroblasts (CAF) are well-established, their plasticity and spatial distribution remain poorly understood. Here, we analyze trajectory inference, deconvolute spatial transcriptomics at single-cell level and perform functional assays to generate an integrative high-resolution map of breast cancer (BC), focusing particularly on the different subpopulations within inflammatory and myofibroblastic (iCAF/myCAF) FAP+ CAF. We identify 10 spatially-organized FAP+ CAF-related cellular niches, called EcoCellTypes, which are precisely localized within tumors. Consistent with their spatial organization, we identify DPP4- and YAP1-dependent mechanisms, by which cancer cells drive the transition of the detoxification-associated inflammatory FAP+ CAF cluster (Detox-iCAF) towards immunosuppressive extracellular matrix (ECM)-producing myofibroblasts (ECM-myCAF). In turn, ECM-myCAF polarize TREM2+ macrophages and regulatory NK cells to induce immunosuppressive EcoCellTypes. FAP+ CAF subpopulations accumulate differently depending on the invasive BC status and predict invasive recurrence of ductal carcinoma in situ (DCIS), which could help in identifying low-risk DCIS patients eligible for therapeutic de-escalation.

  Study EGAS50000000220

• Genomic Variant Dataset of 5,309 Jeju Residents: Integrated WGS and SNP Array Analysis

  This dataset comprises genomic data from the Jeju Genome Project (JGP). WGS libraries were prepared using TruSeq Nano DNA kits and sequenced on Illumina NovaSeq 6000, with variants called via the DRAGEN Germline pipeline (v4.0.3). Genotyping was performed using the customized Axiom_JPMI v1 Chip on the Affymetrix GeneTitan platform. Raw data were processed using APT (v2.11.4), followed by phasing with Eagle (v2.4.1) and imputation via Minimac3 (v2.0.1) using a JGP-specific reference panel to optimize accuracy for the Jeju population.

  Dataset EGAD50000002451

• 4 subjects, 12 brain regions, UKBEC

  Brain samples for this dataset were provided by the Medical Research Council Sudden Death Brain and Tissue Bank (Edinburgh, UK). All four individuals sampled were of European descent, neurologically normal during life and confirmed to be neuropathologically normal by a consultant neuropathologist using histology performed on sections prepared from paraffin-embedded tissue blocks. Twelve regions of the central nervous system were sampled from each individual. The regions studied were: cerebellar cortex, frontal cortex, temporal cortex, occipital cortex, hippocampus, the inferior olivary nucleus (sub-dissected from the medulla), putamen, substantia nigra, thalamus, hypothalamus, intralobular white matter and cervical spinal cord.

  Dataset EGAD00001001274

• Transcriptomics of Liver and PBMCs in Alcohol-Associated Liver Disease

  This study was designed to characterize the transcriptome of alcohol-associated hepatitis using RNA sequencing (RNA-seq) technology for both liver tissue biopsies and peripheral blood mononuclear cells (PBMCs) extracted from blood samples, in order to identify expressed genes that are markers of the disease. To distinguish genes that differentiate alcohol-associated hepatitis from other inflammatory liver diseases, we compared the RNA-seq data generated from participants with alcohol-associated hepatitis, alcohol-associated cirrhosis, chronic hepatitis C infection, non-alcohol-associated fatty liver disease, and healthy controls. We utilized computational approaches to demonstrate that gene expression data generated from either liver tissue or blood samples can be used to identify a small set of gene biomarkers to distinguish between these liver diseases. The raw RNA-seq data will be available through dbGaP.

  Study phs003112

• SCIMAP ACTUAL D0, D3, D6, D8, D14, D49

  The first experiment with multimodal sequencing in the SCI-MAP project. Here, human induced pluripotent stem cells underwent differentiation to chondrocytes for 21 days following an established protocol. Nuclei were isolated and sequenced in two modalities simultaneously; RNA and ATAC.

  Dataset EGAD50000002520

• sQTL summary statistics

  This dataset contains the sQTL summary statistics (nominal pass, significant sQTLs). sQTL mapping was performed with QTLtools. This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity.

  Dataset EGAD00001005042

• Oxford Nanopore Technologies (ONT) long-read sequencing in a paired diagnostic and post- therapy medulloblastoma

  Oxford Nanopore Technologies (ONT) long-read sequencing in a paired diagnostic and post- therapy medulloblastoma (2 samples). One sequencing was done on GridION, the other one on a P2 Solo. In both cases the SQK LSK-109 Kit was used for preparation.

  Dataset EGAD00001009490

• MARS-seq dataset of five obese human subjects and a lean human subject

  Biopsies from visceral adipose tissue from the omental depot (OAT) were obtained from five obese individuals and one lean donor with participant informed consent obtained after the nature and possible consequences of the studies were explained under protocols approved by the Institutional Review Boards of the Perelman School of Medicine at the University of Pennsylvania, the Children’s Hospital of Philadelphia, or the Tel Aviv Sourasky Medical Center. The obese donors underwent bariatric surgery, the lean donor underwent cholecystectomy. OAT samples were placed in 1 mL of DMEM, and finely minced under sterile conditions before digestion in 50 mL of DMEM with 3 mg/1 mL collagenase IV (Gibco). Samples were incubated at 37°C in a rotating oven for 20-60 min. Adipocyte and stromal vascular fractions (SVF) were separated by centrifugation, and red blood cells (RBCs) were removed from the SVF by histopaque gradient (Sigma). Single-cell RNA-sequencing libraries were prepared using the MARS-seq pipeline, and sequenced on the MiSeq 500 or HiSeq 2500 Sequencing System (Illumina).

  Dataset EGAD00001005100

• Myeloid cell programming in patients with non-medullary thyroid carcinoma

  This dataset contains single-cell RNA sequencing data from patients with thyroid cancer (n=7), multinodal Goiter (n=3) and healthy individuals (n=5). Mononuclear cells were taken from both the peripheral blood and the bone marrow compartments. We used a pooled single-cell design where multiple individuals were pooled in a single sample for sequencing (NextSeq 500-V2) and later demultiplexed using their genotype data. Associated metadata contains information on the phenotypes per individual, the pooling design and the linkage between the supplied files and sequenced pools. Due to limitations from EGA in uploading single-cell data, the raw fastq files were processed as follows: (i) I1/I2/R1/R2 fast files were concatenated over the different lanes. (ii) Concatenated I1 and I2 files were interleaved, as were the concatenated R1 and R2 files to generate two fastq files per pool containing all the information. To interleave the fastq files, the BBmap tool bbmap/reformat.sh was used, which can also be used to de-interleave the files.

  Dataset EGAD00001008108