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• COVID-19 severity correlates with airway epithelium–immune cell interactions identified by single-cell analysis

  To investigate the immune response and mechanisms associated with severe COVID-19, we performed single-cell RNA-seq on nasopharyngeal and bronchial samples from 19 clinically well-characterized patients with moderate or critical disease and from 5 healthy controls. We identified airway epithelial cell types and states vulnerable to SARS-CoV-2 infection. In COVID-19 patients, epithelial cells showed an average threefold increase in expression of the SARS-CoV-2 entry receptor ACE2, which correlated with interferon signals by immune cells. Compared with moderate cases, critical cases exhibited stronger interactions between epithelial and immune cells, as indicated by ligand–receptor expression profiles, and activated immune cells , including inflammatory macrophages expressing CCL2, CCL3, CCL20, CXCL1, CXCL3, CXCL10, IL8, IL1B and TNF . The transcriptional differences in critical cases compared with moderate cases likely contribute to clinical observations of heightened inflammatory tissue damage, lung injury and respiratory failure. Our data suggest that pharmacologic inhibition of the CCR1 and/or CCR5 pathways may suppress immune hyperactivation in critical COVID-19.

  Dataset EGAD00001006339

• Genomic characterisation of MGUS

  The hematological malignancy multiple myeloma (MM), also called Kahler's disease or plasma cell (PC) myeloma, is characterized by a clonal expansion of PCs originating in the bone marrow (BM). The expansion of these cells leads to an overproduction of antibodies and results in typical symptoms such as anemia, renal failure and bone lesions. All cases of MM are preceded by the asymptomatic, non-malignant pre-stage monoclonal gammopathy of undetermined significance (MGUS). Of all MGUS patients, only 1% per year will progress to MM. Despite efforts to elucidate the molecular mechanisms underlying the MGUS-to-MM progression, its pathogenesis still remains largely unknown. Additionally, the genetic profiles of MGUS patients have only been limitedly investigated due to the only incidental finding of MGUS, the difficulties in BM sampling and isolating a sufficient number of aberrant PCs from the BM aspirates of MGUS patients. Consequently, reliable biomarkers to individually predict which MGUS patients will progress to MM and which will not, are lacking. Therefore, it is highly required to study the molecular pathogenesis of MGUS and the role of genetic events in relation to the malignant transformation to MM.

  Dataset EGAD00001006363

• A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity

  Abstract: Cancer cells display highly heterogeneous and plastic states in glioblastoma, an incurable brain tumour. However, how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generated a deep single cell and spatial multi-omic atlas of human glioblastoma that pairs transcriptomic, epigenomic and genomic profiling of 12 tumours across multiple regions. We identify that glioblastoma heterogeneity is driven by spatially-patterned transitions of cancer cells from developmental-like states towards those defined by a glial injury response and hypoxia. This cancer cell trajectory regionalizes tumours into distinct tissue niches and manifests in a conserved manner across tumours as well as genetically distinct tumour subclones. Moreover, using a new deep learning framework to jointly map cancer cell states and clones in situ, we show that tumour subclones are finely spatially intermixed through glioblastoma tissue niches. Finally, we show that this cancer cell trajectory is intimately linked to myeloid heterogeneity and unfolds across regionalised myeloid signalling environments. Our findings define a stereotyped trajectory of cancer cells in glioblastoma and unify glioblastoma tumour heterogeneity into a tractable cellular and tissue framework.

  Dataset EGAD00001015516

• RAG mediated recombination is the predominant driver of oncogenic rearrangement in ETV6-RUNX1 Acute Lymphoblastic Leukemia (Rearrangement_sequencing_data)

  The ETV6-RUNX1 fusion gene, found in 25% of childhood acute lymphoblastic leukemia (ALL), is acquired in utero but requires additional somatic mutations for overt leukemia. We used exome and low-coverage whole-genome sequencing to characterize the critical secondary events associated with leukemic transformation. RAG-mediated deletions emerge as the dominant mutational process, accounting for at least 43% of genomic rearrangements and characterized by the presence of recombination signal sequence motifs near the breakpoints; incorporation of non-templated sequence at the junction and a ten-fold enrichment at promoters and enhancers of genes actively transcribed in early B-lineage development. Single-cell tracking shows that this mechanism is not restricted to one founder cell but is rather active throughout leukemic evolution. Integration of point mutation and rearrangement data identifies recurrent inactivation of ATF7IP and MGA as two new tumor suppressor genes.Thus, a remarkably parsimonious mutational process transforms ETV6-RUNX1 lymphoblasts, striking promoters and enhancers of the genes that normally control B-cell differentiation.

  Dataset EGAD00001000635

• Dataset for the Pearl study

  Biomarkers to identify patients without benefit from adding everolimus to endocrine treatment in metastatic breast cancer (MBC) are needed. We report the results of the Pearl trial conducted in five Belgian centers assessing 18F-FDG-PET/CT non-response (n=45) and ctDNA detection (n=46) after 14 days of exemestane-everolimus (EXE-EVE) to identify MBC patients who will not benefit. Metabolic non-response rate was 66.6%. Median PFS in non-responding patients (using as cut-off 25% for SUVmax decrease) was 3.1 months compared to 6.0 months in those showing response (HR: 0.77, 95% CI: 0.40-1.50, p=0.44). Difference was significant when using a “post-hoc” cut-off of 15% (PFS 2.2 months vs 6.4 months). ctDNA detection at D14 was associated with PFS: 2.1 months vs 5.0 months (HR-2.5, 95% CI: 1.3-5.0, p=0.012). Detection of ctDNA and/or the absence of 18F-FDG-PET/CT response after 14 days of EXE-EVE identifies patients with a low probability of benefiting from treatment. Independent validation is needed.

  Dataset EGAD00001007979

• T-cell reconstitution after reduced dose ATLG induction in kidney transplant patients

  We analyzed the T-cell receptor (TCR) repertoires from ten kidney transplant recipients. Five out of the ten kidney transplant recipients received ATLG while the other five recipients received basiliximab as induction therapy. TCR repertoires of CD4+ and CD8+ positive T-cells were assessed prior to transplantation and within the first month after transplantation as well as at three- and 12-months post-transplant. In addition, the pre-formed alloreactive TCR repertoire for each kidney transplant recipient was identified using mixed lymphocyte reaction and donor reactive T-cells were subjected to TCR beta sequencing. This dataset comprises a total of 106 samples. NGS TCR beta libraries of all samples were sequenced on an Illumina NextSeq 500 and raw sequencing data (in the form of fastq files) as well assembled clonotypes and their counts (in the form of clonotype tables) are provided.

  Dataset EGAD00001008478

• Upper cortical layer-driven network impairment in schizophrenia - 10x genomics v3 snRNA-seq and Visium spatial transcriptomics datasets

  This dataset contains 10x Genomics v3 3’ single nuclei RNA sequencing (24 human schizophrenia and control samples) and 10x Genomics Visium spatial transcriptomics (14 human schizophrenia and control samples) datasets. Files are in .bam format, output of the cellranger v3.1.0 (https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/3.1/using/count) for snRNA-seq and spaceranger v1.1.0 (https://support.10xgenomics.com/spatial-gene-expression/software/pipelines/1.1/using/count) for Visium samples. Reads were mapped against Release 97 of human genome from Ensembl (http://ftp.ensembl.org/pub/release-97/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna.primary_assembly.fa.gz http://ftp.ensembl.org/pub/release-97/gtf/homo_sapiens/Homo_sapiens.GRCh38.97.gtf.gz). More details on sample processing are available in the biorXiv pre-print (https://doi.org/10.1101/2020.11.17.386458) and upcoming publication in Science Advances. BAM files can be converted to fastq files using bamtofastq tool (https://support.10xgenomics.com/docs/bamtofastq) with downstream remapping using tools and genomes of choice.

  Dataset EGAD00001009173

• Germline TP53 mutations undergo copy number gain years prior to tumor diagnosis

  Whole-genome sequence (WGS) analysis of tumors from 22 TP53 mutation carriers. We observed somatic mutations affecting Wnt, PI3K/AKT signaling, epigenetic modifiers and homologous recombination genes as well as mutational signatures associated with prior chemotherapy. We identified near-ubiquitous early loss of heterozygosity of TP53, with gain of the mutant allele. This occurred earlier in these tumors compared to tumors with somatic TP53 mutations, suggesting the timing of this mark may distinguish germline from somatic TP53 mutations. Phylogenetic trees of tumor evolution, reconstructed from bulk and multi-region WGS, revealed that LFS tumors exhibit comparatively limited heterogeneity. Overall, our study delineates early copy number gains of mutant TP53 as a characteristic mutational process in LFS tumorigenesis, likely arising very early in life or in utero.years prior to tumor diagnosis.

  Dataset EGAD00001009280

• RNA-seq study of a Princess Margaret Cancer Centre human acute myeloid leukemia patient cohort

  The PMCC AML RNAseq dataset consists of 81 AML patient samples (clinical data in Supplemental Table 11 of manuscript), processed in two batches. These patient samples are able to engraft in the NSG (NOD.Cg PrkdcscidIl2rgtm1Wjl /SzJ) mouse model. Five patients (90543, 598, 90240, 110484, 100500) were included in both batches. Viaably frozen material from the Leukemia Tissue Bank at Princess Margaret Cancer Centre/ University Health Network were thawed by dropwise addition of X-VIVO + 50% fetal calf serum supplemented with DNase (100μg/mL final concentration, Roche). RNA was extracted from bulk peripheral blood mononuclear cells (PBMC) using the RNeasy Micro Kit (Qiagen Inc.). A paired-end 76 base-pair flow-cell lane Illumina High seq 2000 yielded an average of 240 million sequence reads aligning to genome per sample at the Genome Sciences Centre, BC Cancer Agency for cohort 1. Cohort 2 was subjected to 125 bp, paired-end RNA-sequencing on the Illumina HiSeq 2500 with an average of 50 million reads/sample at the Centre for Applied Genomics, Sick Kids Hospital.

  Dataset EGAD00001006576

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006641