Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters.

Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.

Cohesin and CTCF do not assemble TADs in Xenopus sperm and male pronuclei.

Paternal genomes are compacted during spermiogenesis and decompacted following fertilization. These processes are fundamental for inheritance but incompletely understood. We analyzed these processes in the frog Xenopus laevis, whose sperm can be assembled into functional pronuclei in egg extracts in vitro. In such extracts, cohesin extrudes DNA into loops, but in vivo cohesin only assembles topologically associating domains (TADs) at the mid-blastula transition (MBT). Why cohesin assembles TADs only at this stage is unknown. We first analyzed genome architecture in frog sperm and compared it to human and mouse. Our results indicate that sperm genome organization is conserved between frogs and humans and occurs without formation of TADs. TADs can be detected in mouse sperm samples, as reported, but these structures might originate from somatic chromatin contaminations. We therefore discuss the possibility that the absence of TADs might be a general feature of vertebrate sperm. To analyze sperm genome remodeling upon fertilization, we reconstituted male pronuclei in Xenopus egg extracts. In pronuclei, chromatin compartmentalization increases, but cohesin does not accumulate at CTCF sites and assemble TADs. However, if pronuclei are formed in the presence of exogenous CTCF, CTCF binds to its consensus sites, and cohesin accumulates at these and forms short-range chromatin loops, which are preferentially anchored at CTCF's N terminus. These results indicate that TADs are only assembled at MBT because before this stage CTCF sites are not occupied and cohesin only forms short-range chromatin loops.

Parental-to-embryo switch of chromosome organization in early embryogenesis.

Paternal and maternal epigenomes undergo marked changes after fertilization1. Recent epigenomic studies have revealed the unusual chromatin landscapes that are present in oocytes, sperm and early preimplantation embryos, including atypical patterns of histone modifications2-4 and differences in chromosome organization and accessibility, both in gametes5-8 and after fertilization5,8-10. However, these studies have led to very different conclusions: the global absence of local topological-associated domains (TADs) in gametes and their appearance in the embryo8,9 versus the pre-existence of TADs and loops in the zygote5,11. The questions of whether parental structures can be inherited in the newly formed embryo and how these structures might relate to allele-specific gene regulation remain open. Here we map genomic interactions for each parental genome (including the X chromosome), using an optimized single-cell high-throughput chromosome conformation capture (HiC) protocol12,13, during preimplantation in the mouse. We integrate chromosome organization with allelic expression states and chromatin marks, and reveal that higher-order chromatin structure after fertilization coincides with an allele-specific enrichment of methylation of histone H3 at lysine 27. These early parental-specific domains correlate with gene repression and participate in parentally biased gene expression-including in recently described, transiently imprinted loci14. We also find TADs that arise in a non-parental-specific manner during a second wave of genome assembly. These de novo domains are associated with active chromatin. Finally, we obtain insights into the relationship between TADs and gene expression by investigating structural changes to the paternal X chromosome before and during X chromosome inactivation in preimplantation female embryos15. We find that TADs are lost as genes become silenced on the paternal X chromosome but linger in regions that escape X chromosome inactivation. These findings demonstrate the complex dynamics of three-dimensional genome organization and gene expression during early development.

CTCF regulates hepatitis B virus cccDNA chromatin topology.

Hepatitis B Virus (HBV) is a small DNA virus that replicates via an episomal covalently closed circular DNA (cccDNA) that serves as the transcriptional template for viral mRNAs. The host protein, CCCTC-binding factor (CTCF), is a key regulator of cellular transcription by maintaining epigenetic boundaries, nucleosome phasing, stabilisation of long-range chromatin loops and directing alternative exon splicing. We previously reported that CTCF binds two conserved motifs within Enhancer I of the HBV genome and represses viral transcription, however, the underlying mechanisms were not identified. We show that CTCF depletion in cells harbouring cccDNA-like HBV molecules and in de novo infected cells resulted in an increase in spliced transcripts, which was most notable in the abundant SP1 spliced transcript. In contrast, depletion of CTCF in cell lines with integrated HBV DNA had no effect on the abundance of viral transcripts and in line with this observation there was limited evidence for CTCF binding to viral integrants, suggesting that CTCF-regulation of HBV transcription is specific to episomal cccDNA. Analysis of HBV chromatin topology by Assay for Transposase Accessible Chromatin Sequencing (ATAC-Seq) revealed an accessible region spanning Enhancers I and II and the basal core promoter (BCP). Mutating the CTCF binding sites within Enhancer I resulted in a dramatic rearrangement of chromatin accessibility where the open chromatin region was no longer detected, indicating loss of the phased nucleosome up- and down-stream of the HBV enhancer/BCP. These data demonstrate that CTCF functions to regulate HBV chromatin conformation and nucleosomal positioning in episomal maintained cccDNA, which has important consequences for HBV transcription regulation.

Short- and long-range cis interactions between integrated HPV genomes and cellular chromatin dysregulate host gene expression in early cervical carcinogenesis.

Development of cervical cancer is directly associated with integration of human papillomavirus (HPV) genomes into host chromosomes and subsequent modulation of HPV oncogene expression, which correlates with multi-layered epigenetic changes at the integrated HPV genomes. However, the process of integration itself and dysregulation of host gene expression at sites of integration in our model of HPV16 integrant clone natural selection has remained enigmatic. We now show, using a state-of-the-art 'HPV integrated site capture' (HISC) technique, that integration likely occurs through microhomology-mediated repair (MHMR) mechanisms via either a direct process, resulting in host sequence deletion (in our case, partially homozygously) or via a 'looping' mechanism by which flanking host regions become amplified. Furthermore, using our 'HPV16-specific Region Capture Hi-C' technique, we have determined that chromatin interactions between the integrated virus genome and host chromosomes, both at short- (<500 kbp) and long-range (>500 kbp), appear to drive local host gene dysregulation through the disruption of host:host interactions within (but not exceeding) host structures known as topologically associating domains (TADs). This mechanism of HPV-induced host gene expression modulation indicates that integration of virus genomes near to or within a 'cancer-causing gene' is not essential to influence their expression and that these modifications to genome interactions could have a major role in selection of HPV integrants at the early stage of cervical neoplastic progression.

Cell-cycle dynamics of chromosomal organization at single-cell resolution.

Chromosomes in proliferating metazoan cells undergo marked structural metamorphoses every cell cycle, alternating between highly condensed mitotic structures that facilitate chromosome segregation, and decondensed interphase structures that accommodate transcription, gene silencing and DNA replication. Here we use single-cell Hi-C (high-resolution chromosome conformation capture) analysis to study chromosome conformations in thousands of individual cells, and discover a continuum of cis-interaction profiles that finely position individual cells along the cell cycle. We show that chromosomal compartments, topological-associated domains (TADs), contact insulation and long-range loops, all defined by bulk Hi-C maps, are governed by distinct cell-cycle dynamics. In particular, DNA replication correlates with a build-up of compartments and a reduction in TAD insulation, while loops are generally stable from G1 to S and G2 phase. Whole-genome three-dimensional structural models reveal a radial architecture of chromosomal compartments with distinct epigenomic signatures. Our single-cell data therefore allow re-interpretation of chromosome conformation maps through the prism of the cell cycle.

Application of T-cell receptor repertoire as a novel monitor in dynamic tracking and assessment: A cohort-study based on RA patients.

T-cell receptor repertoire (TCRR) sequencing has been widely applied in many fields as a novel tool. This study explored characteristics of TCRR in detail with a cohort of 598 rheumatoid arthritis (RA) patients before and after anti-rheumatic treatments. We highlighted the abnormal TCRR distribution in RA characterized by decreased diversity and increased proportion of hyperexpanded clones (HECs), which was potentially attributed to skewed usage of global V/J segments but not a few certain ones. Enriched motifs analysis in RA community demonstrated the huge heterogeneity of CDR3 sequences, so that individual factors are strongly recommended to be taken into consideration when it comes to clinical application of TCRR. Disease-modifying antirheumatic drugs (DMARDs) can regulate immune system through recovery of TCRR richness to relieve symptoms. Remarkably, sensitive gene profile and advantageous gene profile were identified in this study as new biomarkers for different DMARDs regimens.

Key findings from the UKCCMP cohort of 877 patients with haematological malignancy and COVID-19: disease control as an important factor relative to recent chemotherapy or anti-CD20 therapy.

Patients with haematological malignancies have a high risk of severe infection and death from SARS-CoV-2. In this prospective observational study, we investigated the impact of cancer type, disease activity, and treatment in 877 unvaccinated UK patients with SARS-CoV-2 infection and active haematological cancer. The primary end-point was all-cause mortality. In a multivariate analysis adjusted for age, sex and comorbidities, the highest mortality was in patients with acute leukaemia [odds ratio (OR) = 1·73, 95% confidence interval (CI) 1·1-2·72, P = 0·017] and myeloma (OR 1·3, 95% CI 0·96-1·76, P = 0·08). Having uncontrolled cancer (newly diagnosed awaiting treatment as well as relapsed or progressive disease) was associated with increased mortality risk (OR = 2·45, 95% CI 1·09-5·5, P = 0·03), as was receiving second or beyond line of treatment (OR = 1·7, 95% CI 1·08-2·67, P = 0·023). We found no association between recent cytotoxic chemotherapy or anti-CD19/anti-CD20 treatment and increased risk of death within the limitations of the cohort size. Therefore, disease control is an important factor predicting mortality in the context of SARS-CoV-2 infection alongside the possible risks of therapies such as cytotoxic treatment or anti-CD19/anti-CD20 treatments.

Severity of COVID-19 in children with cancer: Report from the United Kingdom Paediatric Coronavirus Cancer Monitoring Project.

BACKGROUND: Children with cancer are frequently immunocompromised. While children are generally thought to be at less risk of severe SARS-CoV-2 infection than adults, comprehensive population-based evidence for the risk in children with cancer is unavailable. We aimed to produce evidence of the incidence and outcomes from SARS-CoV-2 in children with cancer attending all hospitals treating this population across the UK. METHODS: Retrospective and prospective observational study of all children in the UK under 16 diagnosed with cancer through data collection from all hospitals providing cancer care to this population. Eligible patients tested positive for SARS-CoV-2 on reverse transcription polymerase chain reaction (RT-PCR). The primary end-point was death, discharge or end of active care for COVID-19 for those remaining in hospital. RESULTS: Between 12 March 2020 and 31 July 2020, 54 cases were identified: 15 (28%) were asymptomatic, 34 (63%) had mild infections and 5 (10%) moderate, severe or critical infections. No patients died and only three patients required intensive care support due to COVID-19. Estimated incidence of hospital identified SARS-CoV-2 infection in children with cancer under 16 was 3%. CONCLUSIONS: Children with cancer with SARS-CoV-2 infection do not appear at increased risk of severe infection compared to the general paediatric population. This is reassuring and supports the continued delivery of standard treatment.

Topologically associating domains and chromatin loops depend on cohesin and are regulated by CTCF, WAPL, and PDS5 proteins.

Mammalian genomes are spatially organized into compartments, topologically associating domains (TADs), and loops to facilitate gene regulation and other chromosomal functions. How compartments, TADs, and loops are generated is unknown. It has been proposed that cohesin forms TADs and loops by extruding chromatin loops until it encounters CTCF, but direct evidence for this hypothesis is missing. Here, we show that cohesin suppresses compartments but is required for TADs and loops, that CTCF defines their boundaries, and that the cohesin unloading factor WAPL and its PDS5 binding partners control the length of loops. In the absence of WAPL and PDS5 proteins, cohesin forms extended loops, presumably by passing CTCF sites, accumulates in axial chromosomal positions (vermicelli), and condenses chromosomes. Unexpectedly, PDS5 proteins are also required for boundary function. These results show that cohesin has an essential genome-wide function in mediating long-range chromatin interactions and support the hypothesis that cohesin creates these by loop extrusion, until it is delayed by CTCF in a manner dependent on PDS5 proteins, or until it is released from DNA by WAPL.

COVID-19 mortality in patients with cancer on chemotherapy or other anticancer treatments: a prospective cohort study.

BACKGROUND: Individuals with cancer, particularly those who are receiving systemic anticancer treatments, have been postulated to be at increased risk of mortality from COVID-19. This conjecture has considerable effect on the treatment of patients with cancer and data from large, multicentre studies to support this assumption are scarce because of the contingencies of the pandemic. We aimed to describe the clinical and demographic characteristics and COVID-19 outcomes in patients with cancer. METHODS: In this prospective observational study, all patients with active cancer and presenting to our network of cancer centres were eligible for enrolment into the UK Coronavirus Cancer Monitoring Project (UKCCMP). The UKCCMP is the first COVID-19 clinical registry that enables near real-time reports to frontline doctors about the effects of COVID-19 on patients with cancer. Eligible patients tested positive for severe acute respiratory syndrome coronavirus 2 on RT-PCR assay from a nose or throat swab. We excluded patients with a radiological or clinical diagnosis of COVID-19, without a positive RT-PCR test. The primary endpoint was all-cause mortality, or discharge from hospital, as assessed by the reporting sites during the patient hospital admission. FINDINGS: From March 18, to April 26, 2020, we analysed 800 patients with a diagnosis of cancer and symptomatic COVID-19. 412 (52%) patients had a mild COVID-19 disease course. 226 (28%) patients died and risk of death was significantly associated with advancing patient age (odds ratio 9·42 [95% CI 6·56-10·02]; p<0·0001), being male (1·67 [1·19-2·34]; p=0·003), and the presence of other comorbidities such as hypertension (1·95 [1·36-2·80]; p<0·001) and cardiovascular disease (2·32 [1·47-3·64]). 281 (35%) patients had received cytotoxic chemotherapy within 4 weeks before testing positive for COVID-19. After adjusting for age, gender, and comorbidities, chemotherapy in the past 4 weeks had no significant effect on mortality from COVID-19 disease, when compared with patients with cancer who had not received recent chemotherapy (1·18 [0·81-1·72]; p=0·380). We found no significant effect on mortality for patients with immunotherapy, hormonal therapy, targeted therapy, radiotherapy use within the past 4 weeks. INTERPRETATION: Mortality from COVID-19 in cancer patients appears to be principally driven by age, gender, and comorbidities. We are not able to identify evidence that cancer patients on cytotoxic chemotherapy or other anticancer treatment are at an increased risk of mortality from COVID-19 disease compared with those not on active treatment. FUNDING: University of Birmingham, University of Oxford.

COVID-19 prevalence and mortality in patients with cancer and the effect of primary tumour subtype and patient demographics: a prospective cohort study.

BACKGROUND: Patients with cancer are purported to have poor COVID-19 outcomes. However, cancer is a heterogeneous group of diseases, encompassing a spectrum of tumour subtypes. The aim of this study was to investigate COVID-19 risk according to tumour subtype and patient demographics in patients with cancer in the UK. METHODS: We compared adult patients with cancer enrolled in the UK Coronavirus Cancer Monitoring Project (UKCCMP) cohort between March 18 and May 8, 2020, with a parallel non-COVID-19 UK cancer control population from the UK Office for National Statistics (2017 data). The primary outcome of the study was the effect of primary tumour subtype, age, and sex and on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prevalence and the case-fatality rate during hospital admission. We analysed the effect of tumour subtype and patient demographics (age and sex) on prevalence and mortality from COVID-19 using univariable and multivariable models. FINDINGS: 319 (30·6%) of 1044 patients in the UKCCMP cohort died, 295 (92·5%) of whom had a cause of death recorded as due to COVID-19. The all-cause case-fatality rate in patients with cancer after SARS-CoV-2 infection was significantly associated with increasing age, rising from 0·10 in patients aged 40-49 years to 0·48 in those aged 80 years and older. Patients with haematological malignancies (leukaemia, lymphoma, and myeloma) had a more severe COVID-19 trajectory compared with patients with solid organ tumours (odds ratio [OR] 1·57, 95% CI 1·15-2·15; p<0·0043). Compared with the rest of the UKCCMP cohort, patients with leukaemia showed a significantly increased case-fatality rate (2·25, 1·13-4·57; p=0·023). After correction for age and sex, patients with haematological malignancies who had recent chemotherapy had an increased risk of death during COVID-19-associated hospital admission (OR 2·09, 95% CI 1·09-4·08; p=0·028). INTERPRETATION: Patients with cancer with different tumour types have differing susceptibility to SARS-CoV-2 infection and COVID-19 phenotypes. We generated individualised risk tables for patients with cancer, considering age, sex, and tumour subtype. Our results could be useful to assist physicians in informed risk-benefit discussions to explain COVID-19 risk and enable an evidenced-based approach to national social isolation policies. FUNDING: University of Birmingham and University of Oxford.

Functional movements of the GABA type A receptor.

We have performed a parallel tempering crankshaft motion Monte Carlo simulation on a model of the GABA type A receptor with the aim of exploring a wide variety of local conformational space. We develop a novel method to analyse the protein movements in terms of a correlation tensor and use this to explore the gating process, that is, how agonist binding could cause ion channel opening. We find that simulated binding impulses to varying clusters of GABA binding site residues produce channel opening, and that equivalent impulses to single GABA sites produce partial opening.

Predicting protein ß-sheet contacts using a maximum entropy-based correlated mutation measure.

MOTIVATION: The problem of ab initio protein folding is one of the most difficult in modern computational biology. The prediction of residue contacts within a protein provides a more tractable immediate step. Recently introduced maximum entropy-based correlated mutation measures (CMMs), such as direct information, have been successful in predicting residue contacts. However, most correlated mutation studies focus on proteins that have large good-quality multiple sequence alignments (MSA) because the power of correlated mutation analysis falls as the size of the MSA decreases. However, even with small autogenerated MSAs, maximum entropy-based CMMs contain information. To make use of this information, in this article, we focus not on general residue contacts but contacts between residues in ß-sheets. The strong constraints and prior knowledge associated with ß-contacts are ideally suited for prediction using a method that incorporates an often noisy CMM. RESULTS: Using contrastive divergence, a statistical machine learning technique, we have calculated a maximum entropy-based CMM. We have integrated this measure with a new probabilistic model for ß-contact prediction, which is used to predict both residue- and strand-level contacts. Using our model on a standard non-redundant dataset, we significantly outperform a 2D recurrent neural network architecture, achieving a 5% improvement in true positives at the 5% false-positive rate at the residue level. At the strand level, our approach is competitive with the state-of-the-art single methods achieving precision of 61.0% and recall of 55.4%, while not requiring residue solvent accessibility as an input. AVAILABILITY: http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software/

Efficiently Differentiating Agonists and Competitive Antagonists for Weak Allosteric Protein-Ligand Interactions with Linear Response Theory.

What makes an agonist and a competitive antagonist? In this work, we aim to answer this question by performing parallel tempering Monte Carlo simulations on the serotonin type 3A (5-HT3A) receptor. We use linear response theory to predict conformational changes in the 5-HT3A receptor active site after weak perturbations are applied to its allosteric binding sites. A covariance tensor is built from conformational sampling of its apo state, and a harmonic approximation allows us to substitute the calculation of ligand-induced forces with the binding site's displacement vector. Remarkably, our study demonstrates the feasibility of effectively discerning between agonists and competitive antagonists for multiple ligands, requiring computationally expensive calculations only once per protein.

Engineering amino acid uptake or catabolism promotes CAR T-cell adaption to the tumor environment.

Cancer cells take up amino acids from the extracellular space to drive cell proliferation and viability. Similar mechanisms are applied by immune cells, resulting in the competition between conventional T cells, or indeed chimeric antigen receptor (CAR) T cells and tumor cells, for the limited availability of amino acids within the environment. We demonstrate that T cells can be re-engineered to express SLC7A5 or SLC7A11 transmembrane amino acid transporters alongside CARs. Transporter modifications increase CAR T-cell proliferation under low tryptophan or cystine conditions with no loss of CAR cytotoxicity or increased exhaustion. Transcriptomic and phenotypic analysis reveals that downstream, SLC7A5/SLC7A11-modified CAR T cells upregulate intracellular arginase expression and activity. In turn, we engineer and phenotype a further generation of CAR T cells that express functional arginase 1/arginase 2 enzymes and have enhanced CAR T-cell proliferation and antitumor activity. Thus, CAR T cells can be adapted to the amino acid metabolic microenvironment of cancer, a hitherto recognized but unaddressed barrier for successful CAR T-cell therapy.

Intra- and interchromosomal contact mapping reveals the Igh locus has extensive conformational heterogeneity and interacts with B-lineage genes.

To produce a diverse antibody repertoire, immunoglobulin heavy-chain (Igh) loci undergo large-scale alterations in structure to facilitate juxtaposition and recombination of spatially separated variable (VH), diversity (DH), and joining (JH) genes. These chromosomal alterations are poorly understood. Uncovering their patterns shows how chromosome dynamics underpins antibody diversity. Using tiled Capture Hi-C, we produce a comprehensive map of chromatin interactions throughout the 2.8-Mb Igh locus in progenitor B cells. We find that the Igh locus folds into semi-rigid subdomains and undergoes flexible looping of the VH genes to its 3' end, reconciling two views of locus organization. Deconvolution of single Igh locus conformations using polymer simulations identifies thousands of different structures. This heterogeneity may underpin the diversity of V(D)J recombination events. All three immunoglobulin loci also participate in a highly specific, developmentally regulated network of interchromosomal interactions with genes encoding B cell-lineage factors. This suggests a model of interchromosomal coordination of B cell development.

Exploring the energy landscapes of protein folding simulations with Bayesian computation.

Nested sampling is a Bayesian sampling technique developed to explore probability distributions localized in an exponentially small area of the parameter space. The algorithm provides both posterior samples and an estimate of the evidence (marginal likelihood) of the model. The nested sampling algorithm also provides an efficient way to calculate free energies and the expectation value of thermodynamic observables at any temperature, through a simple post processing of the output. Previous applications of the algorithm have yielded large efficiency gains over other sampling techniques, including parallel tempering. In this article, we describe a parallel implementation of the nested sampling algorithm and its application to the problem of protein folding in a Go-like force field of empirical potentials that were designed to stabilize secondary structure elements in room-temperature simulations. We demonstrate the method by conducting folding simulations on a number of small proteins that are commonly used for testing protein-folding procedures. A topological analysis of the posterior samples is performed to produce energy landscape charts, which give a high-level description of the potential energy surface for the protein folding simulations. These charts provide qualitative insights into both the folding process and the nature of the model and force field used.

QM/MM simulation of liquid water with an adaptive quantum region.

The simulation of complex chemical systems often requires a multi-level description, in which a region of special interest is treated using a computationally expensive quantum mechanical (QM) model while its environment is described by a faster, simpler molecular mechanical (MM) model. Furthermore, studying dynamic effects in solvated systems or bio-molecules requires a variable definition of the two regions, so that atoms or molecules can be dynamically re-assigned between the QM and MM descriptions during the course of the simulation. Such reassignments pose a problem for traditional QM/MM schemes by exacerbating the errors that stem from switching the model at the boundary. Here we show that stable, long adaptive simulations can be carried out using density functional theory with the BLYP exchange-correlation functional for the QM model and a flexible TIP3P force field for the MM model without requiring adjustments of either. Using a primary benchmark system of pure water, we investigate the convergence of the liquid structure with the size of the QM region, and demonstrate that by using a sufficiently large QM region (with radius 6 Å) it is possible to obtain radial and angular distributions that, in the QM region, match the results of fully quantum mechanical calculations with periodic boundary conditions, and, after a smooth transition, also agree with fully MM calculations in the MM region. The key ingredient is the accurate evaluation of forces in the QM subsystem which we achieve by including an extended buffer region in the QM calculations. We also show that our buffered-force QM/MM scheme is transferable by simulating the solvated Cl(-) ion.

COVID-19 in children with haematological malignancies.

BACKGROUND: Children with cancer are not at increased risk of severe SARS-CoV-2 infection; however, adults with haematological malignancies have increased risk of severe infections compared with non-haematological malignancies. METHODS: We compared patients with haematological and non-haematological malignancies enrolled in the UK Paediatric Coronavirus Cancer Monitoring Project between 12 March 2020 and 16 February 2021. Children who received stem cell transplantation were excluded. RESULTS: Only 2/62 patients with haematological malignancy had severe/critical infections, with an OR of 0.5 for patients with haematological compared with non-haematological malignancies. INTERPRETATION: Children with haematological malignancies are at no greater risk of severe SARS-CoV-2 infection than those with non-haematological malignancies.