A Phase I Open-Label Clinical Trial Evaluating the Therapeutic Vaccine hVEGF26–104/RFASE in Patients with Advanced Solid Malignancies

Lessons Learned

• The novel therapeutic vaccine hVEGF_26–104/RFASE was found to be safe and well tolerated in patients with cancer.
• hVEGF_26–104/RFASE failed to induce seroconversion against native hVEGF₁₆₅ and, accordingly, neither a decrease in circulating vascular endothelial growth factor (VEGF) levels nor clinical benefit was observed.
• Remarkably, hVEGF_26–104/RFASE induced VEGF₁₆₅-neutralizing antibodies in a nonhuman primate model. The absence of seroconversion in human calls for caution in the interpretation of efficacy of human vaccines in nonhuman primates.

     

Abnormal glucose tolerance in a pediatric cystic fibrosis cohort: Trends in clinical outcomes and associated factors in the preceding years

Background and aimsDeterioration of anthropometric and lung function parameters was shown to precede the onset of cystic fibrosis-related diabetes (CFRD) in adults. In children, studies have been conducted in small cohorts with relatively short observation period. Study objectives were to document the longitudinal trends of anthropometric, pulmonary, nutritional and metabolic parameters from cystic fibrosis (CF) diagnosis to the ascertainment of abnormal glucose tolerance and identify parameters associated with the incidence of such abnormalities in a pediatric CF cohort.Methods and resultsRetrospective cohort study of 281 children with CF. Longitudinal trends of anthropometric, lung function, nutritional and metabolic data were generated from CF diagnosis to the ascertainment of abnormal glucose tolerance defined as the presence of either impaired glucose tolerance (IGT), unconfirmed CFRD or CFRD. Cox models and Kaplan–Meier curves were used to identify factors associated with developing abnormal glucose tolerance.Forty-five percent of cohort had normal glucose tolerance (NGT), 27% IGT, 10% unconfirmed CFRD and 18% CFRD. Children who developed CFRD displayed lower height z-scores from a very early age. Conversely, HbA1c levels began to rise closer to CFRD ascertainment. Height z-scores (HR: 0.45; CI 95% [0.29–0.69]) and HbA1c (HR: 2.43; CI 95% [1.86–3.18]) in years preceding ascertainment were associated with the risk of developing CFRD.ConclusionChildren who developed CFRD display distinctive trends for height z-scores from a very early age, whereas HbA1c appears as a marker of established glucose metabolism derangements.     

Characterization of hepatitis B virus infection and viral DNA integration in non-Hodgkin lymphoma

Hepatitis B virus (HBV) infection has been reported to be associated with non-Hodgkin lymphoma (NHL). However, the evidence is limited to the seroepidemiological study. There is a lack of evidence showing the HBV infection and integration in NHL cells. Here, we reported that in the Shanghai area, the positive rates of serum HBsAg (OR: 3.11; 95% CI: 2.20-4.41) and HBeAg (OR: 3.99; 95% CI: 1.73-9.91) were significantly higher in patients with NHL. HBsAg, HBcAg and HBV DNA were detected in 34.4%, 45.2% and 47.0% of the NHL tissues, respectively. Furthermore, by using a high-throughput viral integration detection approach (HIVID), integrated HBV DNA was identified from 50% (6/12) HBV-related NHL tissues. There were a total of 313 HBV integration sites isolated from the NHL tissues, among which four protein-coding genes (FAT2, SETX, ITGA10 and CD63) were interrupted by HBV DNA in their exons. Seven HBV preferential target genes (ANKS1B, HDAC4, EGFLAM, MAN1C1, XKR6, ZBTB38 and CCDC91) showed significantly altered expression levels in NHL, suggesting a potential role of these genes in NHL development. Taken together, HBV integration is a common phenomenon in NHL. This finding opens up a new direction of research into the mechanistic link between HBV infection and NHL.     

Graph Convolutional Network Based on Manifold Similarity Learning

In the area of large-scale graph data representation and semi-supervised learning, deep graph-based convolutional neural networks have been widely applied. However, typical graph convolutional network (GCN) aggregates information of neighbor nodes based on binary neighborhood similarity (adjacency matrix). It treats all neighbor nodes of one node equally, which does not suppress the influence of dissimilar neighbor nodes. In this paper, we investigate GCN based on similarity matrix instead of adjacency matrix of graph nodes. Gaussian heat kernel similarity in Euclidean space is first adopted, which is named EGCN. Then biologically inspired manifold similarity is trained in reproducing kernel Hilbert space (RKHS), based on which a manifold GCN (named MGCN) is proposed for graph data representation and semi-supervised learning with four different kernel types. The proposed method is evaluated with extensive experiments on four benchmark document citation network datasets. The objective function of manifold similarity learning converges very quickly on different datasets using various kernel functions. Compared with state-of-the-art methods, our method is very competitive in terms of graph node recognition accuracy. In particular, the recognition rates of MGCN (Gaussian kernel) and MGCN (Polynomial Kernel) outperform that of typical GCN about 3.8% on Cora dataset, 3.5% on Citeseer dataset, 1.3% on Pubmed dataset and 4% on Cora_ML dataset, respectively. Although the proposed MGCN is relatively simple and easy to implement, it can discover local manifold structure by manifold similarity learning and suppress the influence of dissimilar neighbor nodes, which shows the effectiveness of the proposed MGCN.

     

Complications and reoperations after surgery for 647 patients with spine metastatic disease

Background Context

Postoperative morbidity may offset the potential benefits of surgical treatment for spine metastatic disease; hence, risk factors for postoperative complications and reoperations should be taken into considerations during surgical decision-making. In addition, it remains unknown whether complications and reoperations shorten these patients' survival.