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• A blood atlas of COVID-19 defines hallmarks of disease severity and specificity

  Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete understanding of potentially druggable immune mediators of disease. To advance this, we present a comprehensive multi-omic blood atlas in patients with varying COVID-19 severity and compare with influenza, sepsis and healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity revealed cells, their inflammatory mediators and networks as potential therapeutic targets, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Tensor and matrix decomposition of the overall dataset revealed feature groupings linked with disease severity and specificity. Our systems-based integrative approach and blood atlas will inform future drug development, clinical trial design and personalised medicine approaches for COVID-19.

  Study EGAS00001005493

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

  Pheochromocytomas and paragangliomas (PCPG) are rare neuroendocrine tumors associated with autonomic nerves. We used single nuclei-RNA-seq (snRNA-seq) for analysis of 30 PCPG representing 13 known driver genes, plus two normal adrenal medullas to dissect cell composition, refine PCPG subtypes and compare PCPG and normal tissue expression. Incorporating bulk-tissue and snRNA-seq data we identified seven PCPG gene-expression subtypes with genotype and cell type associations. The tumor microenvironment reflected HIF pathway activation and neovascularization by detection of abundant tip-like endothelial cells and pericytes concordant with VEGFA expression in neoplastic cells with mutations in VHL, genes encoding SDH subunits and MAML3-fusions. Macrophages were abundant in PCPG with distinct tumor-associated features. Schwann-cell-like cells were also enriched in some subtypes. The transcriptional profile of neoplastic PCPG cells resembled normal chromaffin cells but early chromaffin and neuroblast cell markers were expressed in some subtypes including GPR139, a putative therapeutic target for a subset of pseudohypoxic PCPG.

  Study EGAS00001005861

• DLBCL NGS Genomic Datasets of non-China cohort from Phoenix Clinical Trial

  Study biopsies (n=773; 189 cases as China cohort and 584 cases as non-China cohort) underwent whole exome sequencing or targeted gene panel DNA sequencing and RNA sequencing, allowing the identification of somatic mutations. Tumors were assigned to DLBCL genetic subtypes as the MCD (n=110), BN2 (n=47) or N1 (n=28) using the LymphGen algorithm based on their somatically mutated genes. In younger patients (age≤60), ibrutinib plus R-CHOP was associated with a 100% event free survival (EFS) at 3-years in the MCD and N1 groups, whereas R-CHOP alone was associated with a 3-year EFS of 42.9% (p=0.01) and 50% (p=0.016) in the MCD and N1 groups, respectively. This analysis showed a benefit of ibrutinib with R-CHOP chemotherapy in particular genetic subtypes, providing mechanistic support for its survival benefit in younger patients with non-GCB DLBCL. The EGA collects RNA-Seq and NuGene targeted sequencing datasets of 584 cases for non-China cohort.

  Study EGAS00001005554

• Tumour gene expression signature in primary melanoma predicts long-term outcomes: A prospective multicentre study

  Adjuvant systemic therapies are now routinely used following resection of stage III melanoma, however accurate prognostic information is needed to better stratify patients. We used differential expression analyses of primary tumours from 204 RNA-sequenced melanomas within a large adjuvant trial, identifying a 121 metastasis-associated gene signature. This signature strongly associated with progression-free (HR=1.63, p=5.24x10-5) and overall survival (HR=1.61, p=1.67x10-4), and validated in 177 regional lymph nodes metastasis as well as two externally ascertained datasets. The machine learning classification models trained using the signature genes performed significantly better in predicting metastases than models trained with clinical covariates (pAUROC=0.02), or published prognostic signatures. The signature score negatively correlated with measures of immune cell infiltration (ρ=-0.75, p<2.2x10-16), with a higher score representing reduced lymphocyte infiltration and a higher 5-year risk of death in stage II melanoma. Our expression signature identifies melanoma patients at higher risk of metastases and warrants further evaluation in adjuvant clinical trials.

  Study EGAS00001004664

• Multi-focal genomic dissection of synchronous primary and metastatic tissue from de novo metastatic prostate cancer

  De novo metastatic prostate cancer is highly aggressive, but the paucity of routinely-collected tissue in this setting has hindered genomic stratification and jeopardizes precision oncology efforts. Here, we leveraged a rare study of surgical intervention in 43 de novo metastatic prostate cancers to assess somatic genotype across 607 synchronous primary and metastatic tissue foci plus circulating tumor DNA. Intra-prostate heterogeneity was pervasive and impacted clinically-relevant genes, resulting in frequent discordance between select primary-restricted foci and synchronous metastases. Additional complexity was driven in several instances by polyclonal metastatic seeding from the reservoir of phylogenetically-related primary populations. When simulating standard clinical practice relying on a single tissue focus, genomic heterogeneity plus highly variable per-sample tumor fraction caused false genotyping of dominant disease. However, in silico modeling demonstrated that analysis of multiple biopsy cores can rescue misassigned somatic genotypes. Our results define the relationship between synchronous treatment-naive primary and metastatic lesions in de novo metastatic prostate cancer and provide a framework for implementing genomics-guided patient management.

  Study EGAS00001006466

• Upper cortical layer-driven network impairment in schizophrenia

  Schizophrenia is one of the most wide-spread and complex mental disorders. To characterize the impact of schizophrenia, we performed single nucleus RNA sequencing (snRNA-seq) of >220,000 neurons from the dorsolateral prefrontal cortex of patients with schizophrenia and matched controls. Additionally, >115,000 neurons were analyzed topographically by immunohistochemistry. Compositional analysis of snRNA-seq data revealed a reduction in abundance of GABAergic neurons and a concomitant increase in principal neurons, most pronounced for upper cortical layer subtypes, which was substantiated by histological analysis. Many neuronal subtypes showed extensive transcriptomic changes, the most dramatic - in upper layer GABAergic neurons, including downregulation in energy metabolism and upregulation in neurotransmission. Transcription factor network analysis demonstrated a developmental origin of transcriptomic changes. Finally, Visium spatial transcriptomics further corroborated upper layer neuron vulnerability in schizophrenia. Overall, our results point towards general network impairment within upper cortical layers as a core substrate associated with schizophrenia symptomatology. Study is available on bioRxiv (https://doi.org/10.1101/2020.11.17.386458) and in upcoming publication.

  Study EGAS00001006495

• scRNASeq of human innate lymphoid cells from different compartments

  Group 1 innate lymphoid cells (ILCs) comprise a heterogeneous family of cytotoxic natural killer (NK) cells and ILC1s. We identifiy a population of “liver-type” ILC1s with transcriptional, phenotypic, and functional features distinct from those of conventional and liver-resident NK cells as well as from other previously described human ILC1 subsets. LT-ILC1s were CD49a+CD94+CD200R1+, expressed the transcription factor T-BET, do not express the activating receptor NKp80, or the transcription factor EOMES. Similar to NK cells, liver-type ILC1s produce IFN-γ, TNF-α, and GM-CSF; however, liver-type ILC1s also produce IL-2 and lack perforin and granzyme B. Liver- type ILC1s are expanded in cirrhotic liver tissues, and they can be produced from blood-derived ILC precursors in vitro in the presence of TGF-β1 and liver sinusoidal endothelial cells. Cells with similar signature and function can also be found in tonsil and intestinal tissues. Collectively, our study identifies and classifies a population of human cross-tissue ILC1s.

  Study EGAS00001006847

• Human NXPE1 mediates variation in sialic acid O-acetylation in Colon Tissue

  Sialylation, and its modifications, have important consequences for development, differentiation and immune system regulation in nearly all human tissues. An accounting of all the genes responsible for modifying sialic acids is incomplete, with only one pathway for O-acetylation being well-defined in humans. Using whole genome sequencing of normal human colorectal tissue we identify a haplotype on chromosome 11 that is associated with differences in mild periodic acid Schiff staining (mPAS), a marker of acetylation of sialic acids. Of the genes in this region, only SNPs from NXPE1 correlate perfectly in a validation data set. NXPE1 protein expression by IHC also correlates with mPAS staining patterns in homozygous, as well as heterozygous colon crypts that have undergone spontaneous gain of the mPAS phenotype. Manipulation of NXPE1 expression with CRISPR-Cas9 causes changes to modified sialic acid levels in both 2D cell line and 3D normal colon organoid models. These findings suggest NXPE1 may cause O-acetylation of sialic acids in colorectal tissue, potentially defining NXPE as a new family of sialic acid-modifying genes.

  Study EGAS00001007704

• Fetal origins of malignant germ cell tumours

  Germ cell tumours (GCTs) are a collection of benign and malignant neoplasms derived from primordial germ cells (PGCs). They are uniquely able to generate embryonic and extraembryonic tissues, which in malignant GCTs carries prognostic and therapeutic significance. The developmental pathways underpinning GCT initiation and histogenesis are incompletely understood. Here, we studied the phylogenetic and transcriptional diversity of 15 malignant gonadal GCTs and four normal testis biopsies by sequencing 131 whole genomes and 416 transcriptomes from 14 gonadal histologies, excised by laser capture microdissection. Our findings demonstrate that tumours were initiated by whole genome duplication likely in embryogenesis, within ~5-8 cell divisions post-PGC specification, followed by chromosome 12p gains associated with invasive disease. Of note, 12p imbalances were not only generated through GCT-typical isochromosomes, but also through non-isochromosomic configurations. Whilst tumours developed along homogenous phylogenetic pathways, they spawned manifold tissues independent of genetic subclonal diversification. A key feature of GCT tissues was the expression of fetal-specific genes. The transcriptional diversity notwithstanding, we found universal transcriptional elements correlated with hallmark 12p gains. Overall, our study reveals stereotyped phylogenies and transcriptomes underpinning the development of GCT that originate in fetal life and may lend themselves to therapeutic manipulation.

  Dataset EGAD00001007037

• The cellular immune and airway epithelial profile throughout childhood and in response to COVID-19 at multi-omic single cell level.

  Single-cell data gene expression data set (5’Chromium 10X) of healthy paediatric volunteers, and paediatric and adult COVID-19 patients. Gene expression was determined from samples of nasal, tracheal and bronchial brushings and blood (PBMCs). In addition to gene expression, PBMC’s were assayed by CITE-seq. A subset of samples have VDJ sequencing data for T cell receptors (TCR) and B cell receptors (BCR).

  Dataset EGAD00001007718