Uveal Melanoma Patients Have a Distinct Metabolic Phenotype in Peripheral Blood

Uveal melanomas (UM) are detected earlier. Consequently, tumors are smaller, allowing for novel eye-preserving treatments. This reduces tumor tissue available for genomic profiling. Additionally, these small tumors can be hard to differentiate from nevi, creating the need for minimally invasive detection and prognostication. Metabolites show promise as minimally invasive detection by resembling the biological phenotype. In this pilot study, we determined metabolite patterns in the peripheral blood of UM patients (n = 113) and controls (n = 46) using untargeted metabolomics. Using a random forest classifier (RFC) and leave-one-out cross-validation, we confirmed discriminatory metabolite patterns in UM patients compared to controls with an area under the curve of the receiver operating characteristic of 0.99 in both positive and negative ion modes. The RFC and leave-one-out cross-validation did not reveal discriminatory metabolite patterns in high-risk versus low-risk of metastasizing in UM patients. Ten-time repeated analyses of the RFC and LOOCV using 50% randomly distributed samples showed similar results for UM patients versus controls and prognostic groups. Pathway analysis using annotated metabolites indicated dysregulation of several processes associated with malignancies. Consequently, minimally invasive metabolomics could potentially allow for screening as it distinguishes metabolite patterns that are putatively associated with oncogenic processes in the peripheral blood plasma of UM patients from controls at the time of diagnosis.</p

Untargeted metabolomics-based screening method for inborn errors of metabolism using semi-automatic sample preparation with an UHPLC-orbitrap-MS platform

Routine diagnostic screening of inborn errors of metabolism (IEM) is currently performed by different targeted analyses of known biomarkers. This approach is time-consuming, targets a limited number of biomarkers and will not identify new biomarkers. Untargeted metabolomics generates a global metabolic phenotype and has the potential to overcome these issues. We describe a novel, single platform, untargeted metabolomics method for screening IEM, combining semi-automatic sample preparation with pentafluorophenylpropyl phase (PFPP)-based UHPLC-Orbitrap-MS. We evaluated analytical performance and diagnostic capability of the method by analysing plasma samples of 260 controls and 53 patients with 33 distinct IEM. Analytical reproducibility was excellent, with peak area variation coefficients below 20% for the majority of the metabolites. We illustrate that PFPP-based chromatography enhances identification of isomeric compounds. Ranked z-score plots of metabolites annotated in IEM samples were reviewed by two laboratory specialists experienced in biochemical genetics, resulting in the correct diagnosis in 90% of cases. Thus, our untargeted metabolomics platform is robust and differentiates metabolite patterns of different IEMs from those of controls. We envision that the current approach to diagnose IEM, using numerous tests, will eventually be replaced by untargeted metabolomics methods, which also have the potential to discover novel biomarkers and assist in interpretation of genetic data

Using out-of-batch reference populations to improve untargeted metabolomics for screening inborn errors of metabolism

Untargeted metabolomics is an emerging technology in the laboratory diagnosis of inborn errors of metabolism (IEM). Analysis of a large number of reference samples is crucial for correcting variations in metabolite concentrations that result from factors, such as diet, age, and gender in order to judge whether metabolite levels are abnormal. However, a large number of reference samples requires the use of out-of-batch samples, which is hampered by the semi-quantitati

Improved annotation of conjugated bile acid hydrolase superfamily members in Gram-positive bacteria.

Item does not contain fulltextMost Gram-positive bacteria inhabiting the gastrointestinal tract are capable of hydrolysing bile salts. Bile salt hydrolysis is thought to play an important role in various biological processes in the host. Therefore, correct annotation of bacterial bile salt hydrolases (Bsh) in public databases (EC 3.5.1.24) is of importance, especially for lactobacilli, which are considered to play a major role in bile salt hydrolysis in vivo. In the present study, all enzymes listed in public databases that belong to the Bsh family and the closely related penicillin V acylase (Pva; EC 3.5.1.11) family were compared with the sequences annotated as Bsh in Lactobacillus plantarum WCFS1, as an example. In Gram-positive bacteria, a clear distinction was made between the two families using sequence alignment, phylogenetic clustering, and protein homology modelling. Biochemical and structural data on experimentally verified Bsh and Pva enzymes were used for validation of function prediction. Hidden Markov models were constructed from the sequence alignments to enable a more accurate prediction of Bsh-encoding genes, and their distinction from those encoding members of the Pva family. Many Pva-related sequences appeared to be annotated incorrectly as Bsh in public databases. This refinement in the annotation of Bsh family members influences the prediction of the function of bsh-like genes in species of the genus Lactobacillus, and it is discussed in detail

ImmunoPET with Anti-Mesothelin Antibody in Patients with Pancreatic and Ovarian Cancer before Anti-Mesothelin Antibody-Drug Conjugate Treatment

PURPOSE: Mesothelin (MSLN) is frequently overexpressed in pancreatic and ovarian cancers, making it a potential drug target. We performed an 89Zr-PET imaging study with MMOT0530A, a MSLN antibody, in conjunction with a phase I study with the antibody-drug conjugate DMOT4039A, containing MMOT0530A bound to MMAE. The aim was to study antibody tumor uptake, whole body distribution and relation between uptake, response to treatment and MSLN expression. EXPERIMENTAL DESIGN: Before DMOT4039A treatment, patients received 37 MBq 89Zr-MMOT0530A followed by PET/CT imaging 2, 4, and 7 days post injection (pi). Tracer uptake was expressed as standardized uptake value (SUV). MSLN expression was determined with immunohistochemistry (IHC) on archival tumor tissue. RESULTS: Eleven patients were included, seven with pancreatic and four with ovarian cancer. IHC MSLN expression varied from absent to strong. Suitable tracer antibody dose was 10 mg MMOT0530A and optimal imaging time was 4 and 7 days pi. Tumor tracer uptake occurred in 37 lesions with mean SUVmax of 13.1 (± 7.5) on PET 4 days pi, with 11.5 (± 7.5) in (N=17) pancreatic and 14.5 (± 8.7) in (N=20) ovarian cancer lesions. Within patients, a mean 2.4-fold (± 1.10) difference in uptake between tumor lesions existed. Uptake in blood, liver, kidneys, spleen and intestine reflected normal antibody distribution. Tracer tumor uptake was correlated to immunohistochemistry. Best response to DMOT4039A was partial response in one patient. CONCLUSIONS: With 89Zr-MMOT0530A-PET pancreatic and ovarian cancer lesions as well as antibody biodistribution could be visualized. This technique can potentially guide individualized antibody-based treatment

Web-accessible application for identifying pathogenic transcripts with RNA-seq: Increased sensitivity in diagnosis of neurodevelopmental disorders

For neurodevelopmental disorders (NDDs), a molecular diagnosis is key for management, predicting outcome, and counseling. Often, routine DNA-based tests fail to establish a genetic diagnosis in NDDs. Transcriptome analysis (RNA sequencing [RNA-seq]) promises to improve the diagnostic yield but has not been applied to NDDs in routine diagnostics. Here, we explored the diagnostic potential of RNA-seq in 96 individuals including 67 undiagnosed subjects with NDDs. We performed RNA-seq on single individuals' cultured skin fibroblasts, with and without cycloheximide treatment, and used modified OUTRIDER Z scores to detect gene expression outliers and mis-splicing by exonic and intronic outliers. Analysis was performed by a user-friendly web application, and candidate pathogenic transcriptional events were confirmed by secondary assays. We identified intragenic deletions, monoallelic expression, and pseudoexonic insertions but also synonymous and non-synonymous variants with deleterious effects on transcription, increasing the diagnostic yield for NDDs by 13%. We found that cycloheximide treatment and exonic/intronic Z score analysis increased detection and resolution of aberrant splicing. Importantly, in one individual mis-splicing was found in a candidate gene nearly matching the individual's specific phenotype. However, pathogenic splicing occurred in another neuronal-expressed gene and provided a molecular diagnosis, stressing the need to customize RNA-seq. Lastly, our web browser application allowed custom analysis settings that facilitate diagnostic application and ranked pathogenic transcripts as top candidates. Our results demonstrate that RNA-seq is a complementary method in the genomic diagnosis of NDDs and, by providing accessible analysis with improved sensitivity, our transcriptome analysis approach facilitates wider implementation of RNA-seq in routine genome diagnostics

Carbohydrate Availability Regulates Virulence Gene Expression in Streptococcus suis

Contains fulltext : 127539.pdf (publisher's version ) (Open Access)Streptococcus suis is a major bacterial pathogen of young pigs causing worldwide economic problems for the pig industry. S. suis is also an emerging pathogen of humans. Colonization of porcine oropharynx by S. suis is considered to be a high risk factor for invasive disease. In the oropharyngeal cavity, where glucose is rapidly absorbed but dietary alpha-glucans persist, there is a profound effect of carbohydrate availability on the expression of virulence genes. Nineteen predicted or confirmed S. suis virulence genes that promote adhesion to and invasion of epithelial cells were expressed at higher levels when S. suis was supplied with the alpha-glucan starch/pullulan compared to glucose as the single carbon source. Additionally the production of suilysin, a toxin that damages epithelial cells, was increased more than ten-fold when glucose levels were low and S. suis was growing on pullulan. Based on biochemical, bioinformatics and in vitro and in vivo gene expression studies, we developed a biological model that postulates the effect of carbon catabolite repression on expression of virulence genes in the mucosa, organs and blood. This research increases our understanding of S. suis virulence mechanisms and has important implications for the design of future control strategies including the development of anti-infective strategies by modulating animal feed composition