Non-small cell lung cancer (NSCLC) has poor survival even with modern checkpoint inhibitor therapies. Personalised vaccines based on short peptide neoantigens containing tumour mutations are an attractive precision medicine strategy, but identifying therapeutically relevant neoantigens remains challenging, with existing methods yielding positive responses in only 6% of candidates tested. We developed an immunopeptidomics approach to improve neoantigen identification in 24 NSCLC patients (15 adenocarcinoma, 9 squamous cell carcinoma). We directly identified one neoantigen and using whole exome sequencing, transcriptomics and mass spectrometry-based immunopeptidomics, we filtered predicted neoantigens based on observed cohort HLA peptide presentation. This approach achieved positive functional responses in 5 of 6 patients tested (83% success rate) with 13% of putative neoantigens (9 out of 70) eliciting strong responses. Bayesian modelling of our initial rules-based neoantigen selection further revealed patient specific peptide presentation patterns and propensities. Our findings demonstrate that incorporating donor-specific HLA peptide presentation data substantially improves neoantigen identification success rates and immune response specificity, advancing personalised cancer vaccine development.

Background Mutation-derived neoantigens, typically identified in primary tumors, are emerging therapeutic targets for personalized cancer vaccines and adoptive T-cell therapies. However, clinical efficacy of neoantigen-directed therapies in patients with metastatic disease remains limited, partly due to inter-site genetic heterogeneity. We investigated whether ubiquitous neoantigens-derived from mutations shared across all tumor sites could provide more effective, durable targets, particularly in patients undergoing resection of metastatic lesions. Methods Whole-exome and RNA sequencing were performed on 14 tumor samples (primary and 13 synchronous nodal metastases) from a treatment-naive patient with pancreatic neuroendocrine tumor (PNET). Ubiquitous mutations were identified bioinformatically, and their immunogenicity assessed using in-vitro stimulation of autologous peripheral blood mononuclear cells followed by IFNγ ELISpot assay. Neoantigen-specific T-cell clonotypes were further identified by HLA-tetramer staining and single-cell RNA and TCR sequencing. Neoantigen-reactive clonotypes identified in peripheral blood were tracked across multiple metastatic sites using bulk TCRβ repertoire sequencing. Results Among 1,195 non-synonymous mutations detected, eight were shared across all 14 tumor sites. Of these, one encoded a neoantigen that elicited a reproducible IFNγ ELISpot response in peripheral blood, confirming its immunogenicity. Further, we identified the corresponding neoantigen-reactive TCR clonotypes in blood. Comparison with bulk TCRβ repertoires from eight metastatic sites showed that these clonotypes were present in every site analyzed, with evidence of local clonal expansion. Conclusion This study provides direct evidence that a single ubiquitous mutation-derived neoantigen can generate systemic T-cell responses and clonotype expansion across multiple metastatic sites in a TMB-low, TIL-low tumor. Our findings support incorporating mutation-sharing status across metastases as a key criterion for neoantigen selection in cancer vaccines and adoptive T-cell therapies. This approach could inform the design of neoantigen-directed immunotherapies in metastatic PNET and potentially other metastatic solid tumors.

Objectives:Chemical disinfectants are critical for infection control in healthcare environments and beyond, as exemplified by their vital role during the COVID-19 pandemic. Despite research repeatedly demonstrating that bacteria can develop adaptations that mitigate the efficacy of chemical disinfectants, the underlying molecular mechanisms remain poorly characterized. This study investigates the mechanisms that underpin resistance demonstrated by disinfectant-adapted Klebsiella pneumoniae NCTC 13443 samples. Methods:Resistant samples have previously undergone long-term in vitro adaptation via serial passage in increasing concentrations of common disinfectants benzalkonium chloride (BAC), didecydimethylammonium chloride (DDAC), polyhexamethylene biguanide (PHMB), chlorocresol or bronopol. A multi-omics approach was used to conduct in-depth molecular analyses of the adaptations that contribute to resistance. Results:K. pneumoniae adaptation to BAC, DDAC and PHMB was associated with the modification of lipid A causing the reduction of the net-negative charge of the outer surface, lowering the affinity of cationic disinfectants. This mechanism is also used for polymyxin and colistin resistance, highlighting a potential cross-resistance risk. Chlorocresol-adapted K. pneumoniae samples demonstrated increased expression of efflux pumps and expression changes linked to biofilm formation. Bronopol resistance was associated with promoting biofilm formation and increased thioredoxin expression to alleviate oxidative stress. Results indicate the potential role of N-ethylmaleimide reductase NemA in bronopol resistance via enzymatic degradation. Conclusions:These findings provide novel insights into how causative pathogens of healthcare-associated infections can adapt to and mitigate the effectiveness of common chemical disinfectants that are relied on globally every day as a critical infection control measure.

Abstract Single-cell RNA sequencing (scRNA-seq) has transformed our ability to analyse cellular heterogeneity, enabling detailed mapping of cellular progression. Trajectory inference tools construct trajectories from scRNA-seq data, facilitating the tracing of cellular progression through developmental pathways. PathPinpointR (PPR) is a lightweight and user-friendly R package developed to predict and compare the positions of scRNA-seq samples along reference biological trajectories, such as those created from large cell atlas projects. PPR utilises sets of switching-gene events from reference trajectories as indicators of cellular progression. By applying these positional indicators to query datasets, each cell can be accurately assigned a pseudo-time value, providing predictive insight into its position along a trajectory. This information can be used to stage cells within an established developmental process, or to evaluate how different patient samples compare when mapped onto reference disease or drug response trajectories. Availability PathPinpointR is available at https://github.com/moi-taiga/PathPinpointR . Contact o.j.l.rackham@soton.ac.uk

IntroductionNeurodegenerative disorders such as Alzheimer’s disease (AD) and Parkinson’s disease (PD) have been increasingly linked to alterations of the gut microbiota, although reported microbial signatures remain heterogeneous and often lack taxonomic resolution.MethodsIn the present study, we applied full-length 16S rRNA gene sequencing to characterize gut microbiota composition in 152 individuals, including patients with AD (n = 37), PD (n = 65), and age-matched healthy controls (n = 50), using a unified bioinformatic and statistical framework with adjustment for relevant demographic covariates.ResultsAlzheimer’s disease was associated with a modest but significant reduction in microbial richness and Shannon diversity compared with controls, whereas no alpha diversity differences were observed in PD. Beta diversity analyses revealed significant compositional differences across diagnostic groups, driven primarily by PD and modulated by sex but not age. Species-level differential abundance analysis identified a PD-associated microbial signature characterized by reduced abundances of short-chain fatty acid-producing bacteria, including Faecalibacterium prausnitzii, Agathobacter rectalis, Roseburia intestinalis, and Faecalicatena fissicatena, together with increased abundance of Ruminococcus sp. JE7A12. In contrast, AD exhibited minimal species-level changes, with only Bacteroidales bacterium CF showing reduced abundance compared with controls.DiscussionOverall, these findings indicate that Parkinson’s disease is characterized by a targeted disruption of beneficial butyrate-producing bacteria, whereas Alzheimer’s disease exhibits subtler and less consistent microbiome alterations. Our results underscore the importance of species-level resolution for identifying disease-associated microbial signatures.

Non-small cell lung cancer (NSCLC) is frequently diagnosed late and has poor survival. The two predominant subtypes of NSCLC, adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), are currently differentially diagnosed using immunohistochemical markers; however, they are increasingly recognized as very different cancer types suggestive of potential for new, more targeted therapies. There are extensive efforts to find more precise and noninvasive differential diagnostic tools. Here, we examined these two NSCLC subtypes for differences that may inform treatment and identify potential novel therapeutic pathways. We presented a comparative analysis of transcriptomic and proteomic expression in tumors from a cohort of 22 NSCLC patients: 8 LUSC and 14 LUAD. Comparing NSCLC subtypes, we found differential gene expression related to cell differentiation for LUSC and cellular structure and immune response regulation for LUAD. Differential protein expression between NSCLC subtypes was related to extracellular structure for LUSC and metabolic processes, including glucose metabolism for LUAD. This direct comparison was more informative about subtype-specific pathways than between each subtype and control (nontumor) tissues. Many of our observations between NSCLC subtypes support and inform existing observations and reveal differences that may aid research seeking to identify and validate novel subtype biomarkers or druggable targets.

BACKGROUND:Proteomic analysis of cerebrospinal fluid (CSF) has the potential to provide insight into the pathophysiology of aneurysmal subarachnoid hemorrhage (aSAH) and target trials to improve outcome. The aim of this study was to perform a definitive proteomic analysis of CSF following aSAH to identify proteins associated with neurological injury. METHODS:This was a retrospective proteomic analysis of CSF collected at neurosurgical centers in the United Kingdom between 2013 and 2023 either from external ventricular drain or lumbar puncture on day 7 after aSAH. Adults with confirmed aSAH were included. Exclusions were pregnancy, severe comorbidities, inability to follow-up, and those not expected to survive 24 hours. Proteomic analysis was performed using mass spectrometry to identify CSF proteins differentially expressed between patients with good (modified Rankin Scale score of 0-2) and poor (modified Rankin Scale score of 3-6) outcomes at 6 months following aSAH. Controlling for CSF albumin (a marker of blood-brain interface permeability and volume of hemorrhage), differentially expressed proteins were identified. Differential pathway activity was explored using protein interaction, gene set enrichment and TopMD analyses. RESULTS:A total of 152 patients were included (101 good and 51 poor outcome), and 4952 unique proteins were identified across all samples. The CSF proteomic profile differed between good and poor outcome individuals as evidenced by clustering of individuals by outcome using topological data analysis. Controlling for CSF albumin 16 intracellular and secreted proteins were differentially expressed between good and poor outcome patients. Two cellular pathways were identified to have differential activity by all 3 pathway analysis approaches: the phosphoinositide 3-kinase-Akt signaling pathway and glycolysis/gluconeogenesis. CONCLUSIONS:In this study, 16 proteins were differentially expressed between good and poor outcome aSAH patients. The proteomic evidence, both on an individual protein and pathway level highlights that inflammation and oxidative injury are associated with the pathophysiology of neurological injury following aSAH. These results support the exploration of treatments targeting these pathways to improve outcome after aSAH.

L1TD1 is a pluripotency factor required for embryonic stem cell self-renewal; its expression has also been detected in solid tumors, including embryonal tumors of the central nervous system (CNS). Previously, we showed that L1TD1 expression correlates with metastasis formation and shorter overall survival of medulloblastoma patients. Here, we used affinity purification coupled to mass spectrometry to map the L1TD1 interactome, and global proteomics to assess proteins differentially regulated by L1TD1 expression in patient-derived embryonal CNS tumor cell lines. We identified novel L1TD1 interactors and differentially expressed proteins related to cell proliferation, death and motility. Finally, we demonstrated that L1TD1-overexpressing tumor cells have distinct cell morphology with enhanced filopodial formation, higher cell motility, greater proliferation capability, and reduced sensitivity to cisplatin treatment.

Despite decades of research, survival from brain cancer has scarcely improved and is drastically lower than that of other cancers. Novel therapies, such as immunotherapy, hold great promise for treating brain tumours and are desperately needed. Zika virus (ZIKV) infects and kills aggressive cancer cells with stem-like properties (CSCs) from both paediatric and adult brain tumours. Whilst T cell recruitment into ZIKV-infected brain tumours is becoming well documented, the specific mechanisms through which they are activated are poorly understood. We address this by employing a combined global proteome and immunopeptidome mass spectrometry approach to describe, for the first time, human leukocyte antigen (HLA) presentation of ZIKV peptides on the surface of infected brain tumour cells. We first show that antigen processing and presentation by HLA class I (HLA-I) is the top enriched immune response pathway in the global proteome of aggressive paediatric USP7-ATRT brain tumour cells following ZIKV infection. We identify USP7-ATRT cells as a desirable immunopeptidome model as they express the globally common HLA-A allotype (A*02:01). We predict the majority of our 19 identified ZIKV peptides to strongly bind and be presented by HLA-A*02:01. We observe a trend between immunopeptide presentation and cellular ZIKV protein abundance, with nearly half of the peptides arising from the most abundant viral protein; non-structural protein 3 (NS3). We show the ZIKV NS3 helicase domain to be a particularly rich source of peptides. Finally, we verify that the 19 ZIKV peptides identified here are not predicted to mimic peptides of the human proteome. The ZIKV peptides we identify here are novel targets for immunotherapy, and our findings provide potential insight into the efficacious cytotoxic T cell response that oncolytic ZIKV virotherapy can induce against brain tumours.

Oesophageal adenocarcinoma (OAC) is the 7th most common cancer in the United Kingdom (UK) and remains a significant health challenge. This study presents a proteomic analysis of seven OAC donors complementing our previous neoantigen identification study of their human leukocyte antigen (HLA) immunopeptidomes. Our small UK cohort were selected from donors undergoing treatment for OAC. We used label-free mass spectrometry proteomics to compare OAC tumour tissue to matched normal adjacent tissue (NAT) to quantify expression of 3552 proteins. We identified differential expression of a number of proteins previously linked to OAC and other cancers including common markers of tumourigenesis and immunohistological markers, as well as enrichment of processes and pathways relating to RNA processing and the immune system. Our findings also offer insight into the role of the protein stability in the generation of an OAC neoantigen we previously identified. These results provide independent corroboration of existing oesophageal adenocarcinoma biomarker studies that may inform future diagnostic and therapeutic research.

Ubiquitin-specific protease 7 (USP7) is implicated in many cancers including colorectal cancer in which it regulates cellular pathways such as Wnt signaling and the P53-MDM2 pathway. With the discovery of small-molecule inhibitors, USP7 has also become a promising target for cancer therapy and therefore systematically identifying USP7 deubiquitinase interaction partners and substrates has become an important goal. In this study, we selected a colorectal cancer cell model that is highly dependent on USP7 and in which USP7 knockdown significantly inhibited colorectal cancer cell viability, colony formation, and cell-cell adhesion. We then used inducible knockdown of USP7 followed by LC-MS/MS to quantify USP7-dependent proteins. We identified the Ajuba LIM domain protein as an interacting partner of USP7 through co-IP, its substantially reduced protein levels in response to USP7 knockdown, and its sensitivity to the specific USP7 inhibitor FT671. The Ajuba protein has been shown to have oncogenic functions in colorectal and other tumors, including regulation of cell-cell adhesion. We show that both knockdown of USP7 or Ajuba results in a substantial reduction of cell-cell adhesion, with concomitant effects on other proteins associated with adherens junctions. Our findings underlie the role of USP7 in colorectal cancer through its protein interaction networks and show that the Ajuba protein is a component of USP7 protein networks present in colorectal cancer.

Objectives: Many reverse transcription polymerase chain reaction (RT-PCR) methods exist that can detect SARS-CoV-2 RNA in different matrices. RT-PCR is highly sensitive, although viral RNA may be detected long after active infection has taken place. SARS-CoV-2 proteins have shorter detection windows hence their detection might be more meaningful. Given salivary droplets represent a main source of transmission, we explored the detection of viral RNA and protein using four different detection platforms including SISCAPA peptide immunoaffinity liquid chromatography-mass spectrometry (SISCAPA-LC-MS) using polyclonal capture antibodies. Methods: The SISCAPA-LC MS method was compared to RT-PCR, RT-loop-mediated isothermal amplification (RT-LAMP), and a lateral flow rapid antigen test (RAT) for the detection of virus material in the drool saliva of 102 patients hospitalised after infection with SARS-CoV-2. Cycle thresholds (Ct) of RT-PCR (E gene) were compared to RT-LAMP time-to-positive (TTP) (NE and Orf1a genes), RAT optical densitometry measurements (test line/control line ratio) and to SISCAPA-LC-MS for measurements of viral protein. Results: SISCAPA-LC-MS showed low sensitivity (37.7 %) but high specificity (89.8 %). RAT showed lower sensitivity (24.5 %) and high specificity (100 %). RT-LAMP had high sensitivity (83.0 %) and specificity (100.0 %). At high initial viral RNA loads (<20 Ct), results obtained using SISCAPA-LC-MS correlated with RT-PCR (R-2 0.57, p-value 0.002). Conclusions: Detection of SARS-CoV-2 nucleoprotein in saliva was less frequent than the detection of viral RNA. The SISCAPA-LC-MS method allowed processing of multiple samples in <150 min and was scalable, enabling high throughput.

During the COVID-19 pandemic, development of diagnostic tests was vital to chart the course and to reduce the impact of the infection. Continued testing and surveillance of vaccine escape will continue for years to come which presents an opportunity to integrate such testing into clinical biochemistry laboratories that form part of integrated healthcare testing. Here we describe a protocol for a targeted mass spectrometry based proteomic assay (COVIDCAP) developed to detect SARS-CoV-2 peptides from oro-nasopharyngeal swabs (ONP) and saliva. This uses novel SISCAPA antibodies bound to magnetic beads and subsequent analysis of captured and purified SARS-CoV-2 nucleocapsid (NCAP) peptides. The method involves immediate deactivation of the sample using an ethanolic solution. This simultaneously inactivates the virus and denatures viral proteins at sampling in contrast to the approach for RT-PCR testing, with benefits for the assay as well as for downstream processing. A plate-based preparation of the samples involving acetone precipitation followed by a short tryptic digestion and subsequent immunocapture allows LC-MS detection and quantification of peptides from the NCAP protein, in a 3-minute inject-to-inject assay with an LOD of 20 attomoles from starting sample. For 576 ONP swab samples taken as exemplars here, the sensitivity and specificity of this analysis is shown to be 97.0% and 96.6% respectively.

Background: The anti-IgE monoclonal antibody omalizumab is widely used for severe asthma. This study aimed to identify biomarkers that predict clinical improvement during 1 year of omalizumab treatment. Methods: One-year open-label Study of Mechanisms of action of Omalizumab in Severe Asthma (SoMOSA) involving 216 patients with severe (Global Initiative for Asthma step 4/5) uncontrolled atopic asthma (at least two severe exacerbations in the previous year) taking high-dose inhaled corticosteroids and long-acting β-agonists with or without maintenance oral corticosteroids. It had two phases: 0-16 weeks, to assess early clinical improvement by Global Evaluation of Therapeutic Effectiveness (GETE); and 16-52 weeks, to assess late responses based on ⩾50% reduction in exacerbations or mOCS dose. All participants provided samples (exhaled breath, blood, sputum, urine) before and after 16 weeks of omalizumab treatment. Measurements and Main Results: A total of 191 patients completed phase 1; 63% had early improvement. Of 173 who completed phase 2, 69% had reduced exacerbations by ⩾50% and 57% (37 of 65) taking mOCSs had reduced their dose by ⩾50%. The primary outcomes 2,3-dinor-11-β-PGF2α, GETE score, and standard clinical biomarkers (blood and sputum eosinophils, exhaled nitric oxide, serum IgE) did not predict either clinical response. Five volatile organic compounds and five plasma lipid biomarkers strongly predicted the ⩾50% reduction in exacerbations (receiver operating characteristic areas under the curve of 0.780 and 0.922, respectively) and early responses (areas under the curve of 0.835 and 0.949, respectively). In an independent cohort, gas chromatography/mass spectrometry biomarkers differentiated between severe and mild asthma. Conclusions: This is the first discovery of omics biomarkers that predict improvement in asthma with biologic agent treatment. Prospective validation and development for clinical use is justified.

Precision medicine offers a promising avenue for better therapeutic responses to pandemics such as COVID-19. This study leverages independent patient cohorts in Florence and Liège gathered under the umbrella of the DRAGON consortium for the stratification of molecular phenotypes associated with COVID-19 using topological analysis of global blood gene expression. Whole blood from 173 patients was collected and RNA was sequenced on the Novaseq platform. Molecular phenotypes were defined through topological analysis of gene expression relative to the biological network using the TopMD algorithm. The two cohorts from Florence and Liège allowed for independent validation of the findings in this study. Clustering of the topological maps of differential pathway activation revealed three distinct molecular phenotypes of COVID-19 in the Florence patient cohort, which were also observed in the Liège cohort. Cluster 1 was characterised by high activation of pathways associated with ESC pluripotency, NRF2, and TGF-β receptor signalling. Cluster 2 displayed high activation of pathways including focal adhesion-PI3K-Akt-mTOR signalling and type I interferon induction and signalling, while Cluster 3 exhibited low IRF7-related pathway activation. TopMD was also used with the Drug-Gene Interaction Database (DGIdb), revealing pharmaceutical interventions targeting mechanisms across multiple phenotypes and individuals. The data illustrates the utility of molecular phenotyping from topological analysis of blood gene expression, and holds promise for informing personalised therapeutic strategies not only for COVID-19 but also for Disease X. Its potential transferability across multiple diseases highlights the value in pandemic response efforts, offering insights before large-scale clinical studies are initiated. ### Competing Interest Statement RPR is an employee at TopMD Precision Medicine Ltd. JPRS is a founding director, CEO, employee, and shareholder in TopMD Precision Medicine Ltd. FS is a founding director, CTO, employee, and shareholder in TopMD Precision Medicine Ltd. PS is a founding director, employee, and shareholder in TopMD Precision Medicine Ltd. BVE is CEO of Comunicare Solutions. TK is CTO of Comunicare Solutions. ### Funding Statement TopMD, the University of Southampton, Imperial College London, CDISC, Comunicare Solutions, and the University of Liverpool are members of the DRAGON consortium. The DRAGON project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 101005122. The JU receives support from the European Union's Horizon 2020 research and innovation program and EFPIA. This publication reflects the author's view. Neither IMI nor the European Union, EFPIA or the DRAGON consortium, are responsible for any use that may be made of the information contained therein. JAH, TP, RPR and CH were supported by the US Food and Drug Administration Medical Countermeasures Initiative (no 75F40120C00085) awarded to JAH and work was also supported by the MRC funded MR/Y004205/1: The G2P2 virology consortium. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. DB is funded by NIHR and MRC. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The protocol was approved by the ethics committee of the University Hospital of Liege (reference number 2021/89) and the ethics committee of the UNIFI (University of Florence) (#18085/OSS). Informed consent was obtained for every participant. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present work are contained in the manuscript

Non-small cell lung cancer (NSCLC) has poor survival even for those receiving modern checkpoint inhibitor therapies. Personalised vaccines based on short peptide neoantigens containing tumour mutations, presented to cytotoxic T-cells by human leukocyte antigen (HLA) molecules, are an attractive strategy. However, identifying therapeutically relevant neoantigens is challenging, with existing methods yielding positive responses in only 6% of candidates tested, and neoantigen-based vaccines in melanoma, glioblastoma and pancreatic cancer producing an immune responses in about 50% of patients. Here we report a proteogenomics approach to identify neoantigens in tumours from a cohort of 24 NSCLC patients: 15 adenocarcinoma, 9 squamous cell carcinoma. We characterised the mutational and HLA immunopeptide landscapes of NSCLC using whole exome sequencing, transcriptomics and mass spectrometry immunopeptidomics. We directly identified one neoantigen, and additional predicted neoantigens were generated using an existing in silico neoantigen prediction workflow. Using the immunopeptidomes to filter for candidate predicted neoantigens we identified positive functional assay responses for 5 out of the 6 patients we tested, with an overall success rate of 13%, inclusive of the directly observed neoantigen. Finally, for one patient using scRNAseq we identified a CD8+ effector T-cell clonotype expanded only in response to the putative class I HLA neoantigen. These results represent an improvement in both the quantity of neoantigens identified and the specificity of immune responses to neoantigens, utilising knowledge of the HLA peptides presented on a tumour. Thus immunopeptidomics has the potential to improve the efficacy of neoantigen based personalised cancer vaccine workflows.

BACKGROUND:COVID-19 has put a huge strain on the healthcare systems worldwide, requiring unprecedented intensive care resources. There is still an unmet clinical need for easily available biomarkers capable of predicting the risk for severe disease. The main goal of this prospective multicenter study was to identify biomarkers that could predict ICU admission and in-hospital mortality. METHODS:We prospectively recruited COVID-19 PCR positive patients in two hospitals, in Belgium and Italy. Blood samples were collected at hospital admission and 20 potential biomarkers were measured with the Luminex technology. Logistic regression models were performed to identify the biomarkers that, alone or together, were associated with patient disease severity. RESULTS:Our study demonstrates that elevated levels of circulating inflammatory cytokines were associated with disease severity in COVID-19 hospitalized patients. CXCL10, IL-4, IL-6 and MCP-1 values were predictive of ICU admission. Elevated levels of IL-6 and MCP-1 were also associated with in hospital death in COVID-19 hospitalized patients. CONCLUSION:Altogether, elevated and correlated inflammatory cytokines in the blood of COVID-19 patients at hospital admission are predictive of disease severity and suggest a dysregulated inflammation induced by SARS-CoV-2 infection.

Background Paediatric neuroblastoma and brain tumours account for a third of all childhood cancer-related mortality. High-risk neuroblastoma is highly aggressive and survival is poor despite intensive multi-modal therapies with significant toxicity. Novel therapies are desperately needed. The Zika virus (ZIKV) can access the nervous system and there is growing interest in employing ZIKV as a potential therapy against paediatric nervous system tumours, including neuroblastoma. Methods Here, we perform extensive data mining, integration and re-analysis of ZIKV infection datasets to highlight molecular mechanisms that may govern the oncolytic response in neuroblastoma cells. We collate infection data of multiple neuroblastoma cell lines by different ZIKV strains from a body of published literature to inform the susceptibility of neuroblastoma to the ZIKV oncolytic response. Integrating published transcriptomics, interaction proteomics, dependency factor and compound datasets we propose the involvement of multiple host systems during ZIKV infection. Results Through data mining of published literature, we observed most paediatric neuroblastoma cell lines to be highly susceptible to ZIKV infection and propose the PRVABC59 ZIKV strain to be the most promising candidate for neuroblastoma oncolytic virotherapy. ZIKV induces TNF signalling, lipid metabolism, the Unfolded Protein Response (UPR), and downregulates cell cycle and DNA replication processes. ZIKV infection is dependent on sterol regulatory element binding protein (SREBP)-regulated lipid metabolism and three protein complexes; V-ATPase, ER Membrane Protein Complex (EMC) and mammalian translocon. We propose ZIKV non-structural protein 4B (NS4B) as a likely mediator of ZIKVs interaction with IRE1-mediated UPR, lipid metabolism and mammalian translocon. Conclusions Our work provides a significant understanding of ZIKV infection in neuroblastoma cells, which will facilitate the progression of ZIKV-based oncolytic virotherapy through pre-clinical research and clinical trials.

Matrix stiffening by lysyl oxidase-like 2 (LOXL2)-mediated collagen cross-linking is proposed as a core feedforward mechanism that promotes fibrogenesis. Failure in clinical trials of simtuzumab (the humanized version of AB0023, a monoclonal antibody against human LOXL2) suggested that targeting LOXL2 may not have disease relevance; however, target engagement was not directly evaluated. We compare the spatial transcriptome of active human lung fibrogenesis sites with different human cell culture models to identify a disease-relevant model. Within the selected model, we then evaluate AB0023, identifying that it does not inhibit collagen cross-linking or reduce tissue stiffness, nor does it inhibit LOXL2 catalytic activity. In contrast, it does potently inhibit angiogenesis consistent with an alternative, non-enzymatic mechanism of action. Thus, AB0023 is anti-angiogenic but does not inhibit LOXL2 catalytic activity, collagen cross-linking, or tissue stiffening. These findings have implications for the interpretation of the lack of efficacy of simtuzumab in clinical trials of fibrotic diseases.