Diagnostic classification of childhood cancer using multiscale transcriptomics

The causes of pediatric cancers’ distinctiveness compared to adult-onset tumors of the same type are not completely clear and not fully explained by their genomes. In this study, we used an optimized multilevel RNA clustering approach to derive molecular definitions for most childhood cancers. Applying this method to 13,313 transcriptomes, we constructed a pediatric cancer atlas to explore age-associated changes. Tumor entities were sometimes unexpectedly grouped due to common lineages, drivers or stemness profiles. Some established entities were divided into subgroups that predicted outcome better than current diagnostic approaches. These definitions account for inter-tumoral and intra-tumoral heterogeneity and have the potential of enabling reproducible, quantifiable diagnostics. As a whole, childhood tumors had more transcriptional diversity than adult tumors, maintaining greater expression flexibility. To apply these insights, we designed an ensemble convolutional neural network classifier. We show that this tool was able to match or clarify the diagnosis for 85% of childhood tumors in a prospective cohort. If further validated, this framework could be extended to derive molecular definitions for all cancer types

Electrocardiogram-based mortality prediction in patients with COVID-19 using machine learning

Background and purpose: The electrocardiogram (ECG) is frequently obtained in the work-up of COVID-19 patients. So far, no study has evaluated whether ECG-based machine learning models have added value to predict in-hospital mortality specifically in COVID-19 patients. / Methods: Using data from the CAPACITY-COVID registry, we studied 882 patients admitted with COVID-19 across seven hospitals in the Netherlands. Raw format 12-lead ECGs recorded within 72 h of admission were studied. With data from five hospitals (n = 634), three models were developed: (a) a logistic regression baseline model using age and sex, (b) a least absolute shrinkage and selection operator (LASSO) model using age, sex and human annotated ECG features, and (c) a pre-trained deep neural network (DNN) using age, sex and the raw ECG waveforms. Data from two hospitals (n = 248) was used for external validation. / Results: Performances for models a, b and c were comparable with an area under the receiver operating curve of 0.73 (95% confidence interval [CI] 0.65–0.79), 0.76 (95% CI 0.68–0.82) and 0.77 (95% CI 0.70–0.83) respectively. Predictors of mortality in the LASSO model were age, low QRS voltage, ST depression, premature atrial complexes, sex, increased ventricular rate, and right bundle branch block. / Conclusion: This study shows that the ECG-based prediction models could be helpful for the initial risk stratification of patients diagnosed with COVID-19, and that several ECG abnormalities are associated with in-hospital all-cause mortality of COVID-19 patients. Moreover, this proof-of-principle study shows that the use of pre-trained DNNs for ECG analysis does not underperform compared with time-consuming manual annotation of ECG features

Functional characteristics of coronary vasomotor function following intramyocardial gene therapy with naked DNA encoding for vascular endothelial growth factor 165

Vascular endothelial growth factor (VEGF) is a potent angiogenic factor. VEGF gene therapy improves perfusion of ischemic myocardium in experimental models and possibly in patients with end-stage coronary artery disease. In addition to its proliferative and migratory effect on endothelial cells, it also activates and up-regulates endothelial nitric oxide synthase (eNOS). Therefore, the authors investigated coronary endothelium-dependent vasodilatation in patients before and after VEGF gene therapy. The effect of intracoronary acetylcholine infusion on coronary diameter was assessed at baseline and after 3 months follow-up in patients with end-stage coronary artery disease treated with VEGF gene and in controls scheduled for elective percutaneous transluminal coronary angioplasty (PTCA) (acetylcholine test at diagnostic angiography and before a subsequently scheduled PTCA). Five out of six VEGF patients experienced a reduction in anginal complaints. Angiographic evidence for improved collateral filling was evident in two out of six patients. The vasoconstrictive response to acetylcholine was partly converted into dilatation. In contrast, the acetylcholine response in control patients remained vasoconstrictive. In conclusion, VEGF gene therapy has an important beneficial effect on the functional characteristics of the myocardial vascular network. Therefore, this therapy can potentially play an important role in all stages of the atherosclerotic process

Safety evaluation of routine intracoronary acetylcholine infusion in patients undergoing a first diagnostic coronary angiogram

Background: Recent findings imply prognostic significance of intracoronary acetylcholine infusion for endothelial function testing. We evaluated whether routine use of this test in coronary angiography patients is safe. Methods: Patients undergoing a first diagnostic coronary angiography were selected to receive intracoronary acetylcholine for endothelial function evaluation. The relation between adverse reactions during infusion and risk factors was analyzed with a logistic regression model. Included in the multiple logistic regression model were the variables with a univariate P value <0.20. Results: Adverse reactions occurred in 16% (49/299) of the patients. This included two life-threatening events caused by occlusive spasm and flow limitation in the left coronary artery. Other adverse events were chest pain (n = 38), AV block or sinus bradycardia (n = 10), dyspnea (n = 3). Adverse reactions were more likely to occur in patients younger than 60 years of age (relative risk, 5.6 [2.2-14.3]). Conclusion: Intracoronary acetylcholine infusion is safe, but may lead to serious adverse reactions. Care should be taken especially in patients younger than 60 years of age. Routine use of acetylcholine infusion can thus only be justified if it has important prognostic significance. This has to be proven further in large prospective studies