COVID-19 in patients with cancer: first report of the ESMO international, registry-based, cohort study (ESMO-CoCARE).

BACKGROUND: ESMO COVID-19 and CAncer REgistry (ESMO-CoCARE) is an international collaborative registry-based, cohort study gathering real-world data from Europe, Asia/Oceania and Africa on the natural history, management and outcomes of patients with cancer infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). PATIENTS AND METHODS: ESMO-CoCARE captures information on patients with solid/haematological malignancies, diagnosed with coronavirus disease 2019 (COVID-19). Data collected since June 2020 include demographics, comorbidities, laboratory measurements, cancer characteristics, COVID-19 clinical features, management and outcome. Parameters influencing COVID-19 severity/recovery were investigated as well as factors associated with overall survival (OS) upon SARS-CoV-2 infection. RESULTS: This analysis includes 1626 patients from 20 countries (87% from 24 European, 7% from 5 North African, 6% from 8 Asian/Oceanian centres), with COVID-19 diagnosis from January 2020 to May 2021. Median age was 64 years, with 52% of female, 57% of cancer stage III/IV and 65% receiving active cancer treatment. Nearly 64% patients required hospitalization due to COVID-19 diagnosis, with 11% receiving intensive care. In multivariable analysis, male sex, older age, Eastern Cooperative Oncology Group (ECOG) performance status ≥2, body mass index (BMI) <25 kg/m2, presence of comorbidities, symptomatic disease, as well as haematological malignancies, active/progressive cancer, neutrophil-to-lymphocyte ratio (NLR) ≥6 and OnCovid Inflammatory Score ≤40 were associated with COVID-19 severity (i.e. severe/moderate disease requiring hospitalization). About 98% of patients with mild COVID-19 recovered, as opposed to 71% with severe/moderate disease. Advanced cancer stage was an additional adverse prognostic factor for recovery. At data cut-off, and with median follow-up of 3 months, the COVID-19-related death rate was 24.5% (297/1212), with 380 deaths recorded in total. Almost all factors associated with COVID-19 severity, except for BMI and NLR, were also predictive of inferior OS, along with smoking and non-Asian ethnicity. CONCLUSIONS: Selected patient and cancer characteristics related to sex, ethnicity, poor fitness, comorbidities, inflammation and active malignancy predict for severe/moderate disease and adverse outcomes from COVID-19 in patients with cancer

3D anatomical and perfusion MRI for longitudinal evaluation of biomaterials for bone regeneration of femoral bone defect in rats

Magnetic Resonance Imaging (MRI) appears as a good surrogate to Computed Tomography (CT) scan as it does not involve radiation. In this context, a 3D anatomical and perfusion MR imaging protocol was developed to follow the evolution of bone regeneration and the neo-vascularization in femoral bone defects in rats. For this, three different biomaterials based on Pullulan-Dextran and containing either Fucoidan or HydroxyApatite or both were implanted. In vivo MRI, ex vivo micro-CT and histology were performed 1, 3 and 5 weeks after implantation. The high spatially resolved (156 × 182 × 195 µm) anatomical images showed a high contrast from the defects filled with biomaterials that decreased over time due to bone formation. The 3D Dynamic Contrast Enhanced (DCE) imaging with high temporal resolution (1 image/19 s) enabled to detect a modification in the Area-Under-The-Gadolinium-Curve over the weeks post implantation. The high sensitivity of MRI enabled to distinguish which biomaterial was the least efficient for bone regeneration, which was confirmed by micro-CT images and by a lower vessel density observed by histology. In conclusion, the methodology developed here highlights the efficiency of longitudinal MRI for tissue engineering as a routine small animal exam

An antibiotic produced by an insect-pathogenic bacterium suppresses host defenses through phenoloxidase inhibition

Photorhabdus is a virulent pathogen that kills its insect host by overcoming immune responses. The bacterium also secretes a range of antibiotics to suppress the growth of other invading microorganisms. Here we show that Photorhabdus produces a small-molecule antibiotic (E)-1,3-dihydroxy-2-(isopropyl)-5-(2-phenylethenyl)benzene (ST) that also acts as an inhibitor of phenoloxidase (PO) in the insect host Manduca sexta. The Photorhabdus gene stlA encodes an enzyme that produces cinnamic acid, a key precursor for production of ST, and a mutation in stlA results in loss of ST production and PO inhibitory activity, which are both restored by genetic complementation of the mutant and also by supplying cinnamic acid. ST is produced both in vitro and in vivo in sufficient quantities to account for PO inhibition and is the only detectable solvent-extractable inhibitor. A Photorhabdus stlA− mutant is significantly less virulent, proliferates slower within the host, and provokes the formation of significantly more melanotic nodules than wild-type bacteria. Virulence of the stlA− mutant is also rescued by supplying cinnamic acid. The proximate cause of the virulence effect, however, is the inhibition of PO, because the effect of the stlA− mutation on virulence is abolished in insects in which PO has been knocked down by RNA interference (RNAi). Thus, ST has a dual function both as a PO inhibitor to counter host immune reactions and also as an antibiotic to exclude microbial competitors from the insect cadaver

A definitive prognostication system for patients with thoracic malignancies diagnosed with COVID-19: an update from the TERAVOLT registry.

BackgroundPatients with thoracic malignancies are at increased risk for mortality from Coronavirus disease 2019 (COVID-19) and large number of intertwined prognostic variables have been identified so far.MethodsCapitalizing data from the TERAVOLT registry, a global study created with the aim of describing the impact of COVID-19 in patients with thoracic malignancies, we used a clustering approach, a fast-backward step-down selection procedure and a tree-based model to screen and optimize a broad panel of demographics, clinical COVID-19 and cancer characteristics.ResultsAs of April 15, 2021, 1491 consecutive evaluable patients from 18 countries were included in the analysis. With a mean observation period of 42 days, 361 events were reported with an all-cause case fatality rate of 24.2%. The clustering procedure screened approximately 73 covariates in 13 clusters. A further multivariable logistic regression for the association between clusters and death was performed, resulting in five clusters significantly associated with the outcome. The fast-backward step-down selection then identified seven major determinants of death ECOG-PS (OR 2.47 1.87-3.26), neutrophil count (OR 2.46 1.76-3.44), serum procalcitonin (OR 2.37 1.64-3.43), development of pneumonia (OR 1.95 1.48-2.58), c-reactive protein (CRP) (OR 1.90 1.43-2.51), tumor stage at COVID-19 diagnosis (OR 1.97 1.46-2.66) and age (OR 1.71 1.29-2.26). The ROC analysis for death of the selected model confirmed its diagnostic ability (AUC 0.78; 95%CI: 0.75 - 0.81). The nomogram was able to classify the COVID-19 mortality in an interval ranging from 8% to 90% and the tree-based model recognized ECOG-PS, neutrophil count and CRP as the major determinants of prognosis.ConclusionFrom 73 variables analyzed, seven major determinants of death have been identified. Poor ECOG-PS demonstrated the strongest association with poor outcome from COVID-19. With our analysis we provide clinicians with a definitive prognostication system to help determine the risk of mortality for patients with thoracic malignancies and COVID-19