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• Heterogeneous metabolic signatures are linked to cancer cell differentiation in colorectal cancer

  Colorectal cancer (CRC) is characterized by functional intratumor heterogeneity that shares many similarites with the hierarchical organization of the normal intestinal epithelium. In order to relate transcriptional subtypes to functional tumor cell heterogeneity we applied scRNA-seq to 12 patient-derived CRC spheroid cultures. We identified shared expression programs that relate to intestinal lineages and revealed metabolic signatures that are linked to cancer cell differentiation. In addition, we validated and complemented sequencing results by quantitative microscopy using live-dyes and multiplexed RNA fluorescence in situ hybridization, thereby revealing metabolic compartmentalization and potential cell-cell interactions. Finally, we demonstrate functional differences between metabolically distinct lineage subtypes that might have strong implications for future treatment strategies of CRC.

  Dataset EGAD00001005524

• Single-nuclei gene-expression analysis of pheochromocytoma and paraganglioma links tumor subtypes with tumor microenvironment

  This dataset contains raw sequencing reads in FASTQ format from single-nuclei (30 samples) and bulk tissue (40 samples) transcriptome sequencing of pheochromocytoma and paraganglioma tissue specimens. Additionally, data from single-nuclei sequencing of two normal adrenal medulla specimens is included.

  Dataset EGAD00001008403

• Single-cell RNA-seq of peripheral blood mononuclear cells in classic Hodgkin lymphoma

  Abstract: Classic Hodgkin lymphoma (cHL) is a largely MHC class I-negative tumor with recurrent 9p24.1/ PD-L1/ PD-L2 copy gains and the highest reported response rates to PD-1 blockade. We utilized scRNA sequencing to characterize the peripheral immune response to PD-1 blockade and more broadly define non-CD8+ dependent mechanisms of immune evasion in cHL. Peripheral blood mononuclear cells were obtained from 20 patients with relapsed/refractory (R/R) cHL treated with PD-1 blockade (nivolumab) on the CheckMate 205 clinical trial (paired samples from cycle 1 day 1 [C1D1] and cycle 4 day 1 [C4D1]), 11 patients with newly diagnosed, previously untreated cHL and 13 healthy donors.

  Dataset EGAD00001011360

• COVID-19 Multiomics Atlas

  We provide a single-nuclei RNA-sequencing (snRNA-seq) dataset derived from four COVID-19 patients, generated using the 10x Chromium Next GEM Single Cell v3.1 kit. For our study, these were integrated with snRNA-seq data with 12 publicly available sc/snRNA-seq datasets, comprising organ donor lung samples (n=89) and COVID-19 lung tissue samples (n=51). Additionally, we provide a spatial transcriptomic dataset characterizing different histopathological stages of diffuse alveolar damage, across a cohort of 33 COVID-19 patients. This was generated using the Nanostring Whole Transcriptome Assay (WTA) with regions of interest (ROIs) sized 400 µm² each. This integrated multi-omics analysis of snRNA-seq, histology, and spatial transcriptomics data, is available for exploration and download via our web portal: https://covid19-multiomicatlas.cellgeni.sanger.ac.uk/.

  Dataset EGAD00001015404

• An integrated single-cell reference atlas of the human endometrium

  This dataset includes both the anchor scRNA-seq and snRNA-seq datasets used to build the Human Endometrial Cell Atlas (HECA). HECA provides a comprehensive definition of endometrial cell types and states throughout the menstrual cycle in donor with and without endometriosis. It identifies consensus cell types across datasets generated by teams worldwide, as well as previously unreported cell types, all of which are validated and mapped in situ using spatial transcriptomics. Processed data is available from ArrayExpress with accession number E-MTAB-14039. See Marečková, M., Garcia-Alonso, L., Moullet, M. et al. An integrated single-cell reference atlas of the human endometrium. Nat Genet 56, 1925–1937 (2024) https://doi.org/10.1038/s41588-024-01873-w for more information.

  Dataset EGAD00001015446

• Single-cell RNA sequencing of human kidney transplant nephrectomies with chronic rejection or non-alloimmune graft injury

  This dataset contains raw single-cell RNA sequencing (scRNA-seq) data for five new kidney allograft nephrectomy samples used to construct the described in the following study: https://www.biorxiv.org/content/10.1101/2022.10.28.514222v2.full. The full description of processing is described in the manuscript. Briefly, samples were digested into a single cell suspension and run according to the 10X Genomics Chromium 5’ single cell kit (v2). Sequencing was performed using an Illumina Novaseq instrument. Samples were designated as TXN2 (EGAN00002519570, mycotic pseudoaneurysm, control dataset), TXN3 (EGAN00002235628, renal vein thrombus, control dataset), TXN5 (EGAN00002519573, chronic transplant rejection), TXN6 (EGAN00002519572, chronic pyelonephritis and renal artery stenosis, non-alloimmune graft injury dataset), TXN7 (EGAN00002519576, recurrent focal segmental glomerulosclerosis, non-alloimmune graft injury dataset).

  Dataset EGAD00001015631

• Targeted sequencing of 72 prostate cancer driver in 712 plasma cell free DNA samples

  Dataset contains targeted sequencing data of 712 plasma cell free DNA samples and 428 white blood cell samples collected from 428 men with metastatic prostate cancer. Target capture was performed using a hydridization-based custom Roche SeqCap EZ Choice kit, designed to capture all exons of 72 prostate cancer driver genes. Cell free DNA was extracted from 10 mL blood samples. Libraries were sequenced using Illumina HiSeq 2500 or Illumina MiSeq instruments to a median coverage of 750x. 62% of samples had ctDNA fraction above 2% of total cfDNA. Note that "Dataset type" is erroneously listed as "Amplicon sequencing", because "Captured-based targeted sequencing" or "Hybridization-based targeted sequencing" were not available options in EGA at the time of submission.

  Dataset EGAD00001004208

• Pilot experiment on functional genomics in osteoarthritis_RNA

  The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). In this pilot we will assess the feasibility of the approach in the relevant tissue. We will obtain diseased and non-diseased tissue (cartilage and endochondral bone) following TJR, coupled with a blood sample, from 12 patients. We will characterise the 12 pairs of diseased and non-diseased tissue samples in terms of transcription (RNASeq) The pilot will help assess the feasibility of isolating sufficient levels of starting material for the different approaches, and will instigate the development of analytical approaches to synthesising the resulting data.

  Dataset EGAD00001001331

• Whole Genome Sequencing of Liver Cancers

  Genomic alterations driving tumorigenesis result from the interaction of environmental exposures and endogeneous cellular processes. With a diversity of risk factors including viral infection, carcinogenic exposures and metabolic diseases, liver cancer is an ideal model to study these interactions. Whole genome sequencing of liver tumors identified 10 mutational signatures showing distinct relationships with environmental exposures, replication and transcription. Transcription-coupled damage was specifically associated with the liver-specific signature 16 and alcohol intake. Flood of indels were identified in very highly expressed hepato-specific genes, likely resulting from replication-transcription collisions. Reconstruction of sub-clonal architecture revealed mutational signature evolution during tumor development exemplified by the vanishing of aflatoxin-B1 signature in African migrants. These findings shed new light on the natural history of liver cancers.

  Dataset EGAD00001003281

• Identification of rare variants associated with cardiovascular traits in Cilento isolates

  The aim of this project is to identify rare genetic variants of large effect implicated in complex diseases by focusing on the study of cardiovascular diseases and related quantitative traits in a well characterized isolated population in Cilento area, Italy. The reference panel has been selected carefully in order to maximize the imputation coverage and quality on the all population samples. The selected individuals should meet three criteria: selected individuals should be chip-genotyped and closely related to the maximum number of chip-genotyped individuals so as to maximize imputation coverage; relatedness between selected individuals should be minimal, so as to minimize redundancy in genetic information of the reference panel. We perform exome sequencing on samples from 250 individuals from the Campora and Gioi-Cardile populations.

  Dataset EGAD00001002195