IDH/MGMT-driven molecular classification of low-grade glioma is a strong predictor for long-term survival

BACKGROUND Low-grade gliomas (LGGs) are rare brain neoplasms, with survival spanning up to a few decades. Thus, accurate evaluations on how biomarkers impact survival among patients with LGG require long-term studies on samples prospectively collected over a long period. METHODS The 210 adult LGGs collected in our databank were screened for IDH1 and IDH2 mutations (IDHmut), MGMT gene promoter methylation (MGMTmet), 1p/19q loss of heterozygosity (1p19qloh), and nuclear TP53 immunopositivity (TP53pos). Multivariate survival analyses with multiple imputation of missing data were performed using either histopathology or molecular markers. Both models were compared using Akaike's information criterion (AIC). The molecular model was reduced by stepwise model selection to filter out the most critical predictors. A third model was generated to assess for various marker combinations. RESULTS Molecular parameters were better survival predictors than histology (ΔAIC = 12.5, P< .001). Forty-five percent of studied patients died. MGMTmet was positively associated with IDHmut (P< .001). In the molecular model with marker combinations, IDHmut/MGMTmet combined status had a favorable impact on overall survival, compared with IDHwt (hazard ratio [HR] = 0.33, P< .01), and even more so the triple combination, IDHmut/MGMTmet/1p19qloh (HR = 0.18, P< .001). Furthermore, IDHmut/MGMTmet/TP53pos triple combination was a significant risk factor for malignant transformation (HR = 2.75, P< .05). CONCLUSION By integrating networks of activated molecular glioma pathways, the model based on genotype better predicts prognosis than histology and, therefore, provides a more reliable tool for standardizing future treatment strategies.

OMA and OPA—Software-Supported Mass Spectra Analysis of Native and Modified Nucleic Acids

The platform-independent software package consisting of the oligonucleotide mass assembler (OMA) and the oligonucleotide peak analyzer (OPA) was created to support the analysis of oligonucleotide mass spectra. It calculates all theoretically possible fragments of a given input sequence and annotates it to an experimental spectrum, thus, saving a large amount of manual processing time. The software performs analysis of precursor and product ion spectra of oligonucleotides and their analogues comprising user-defined modifications of the backbone, the nucleobases, or the sugar moiety, as well as adducts with metal ions or drugs. The ability to expand the library of building blocks and to implement individual structural variations makes it extremely useful for supporting the analysis of therapeutically active compounds. The functionality of the software tool is demonstrated on the examples of a platinated doublestranded oligonucleotide and a modified RNA sequence. Experiments also reveal the unique dissociation behavior of platinated higher-order DNA structures.

MQN-Mapplet: Visualization of Chemical Space with Interactive Maps of DrugBank, ChEMBL, PubChem, GDB-11, and GDB-13

The MQN-mapplet is a Java application giving access to the structure of small molecules in large databases via color-coded maps of their chemical space. These maps are projections from a 42-dimensional property space defined by 42 integer value descriptors called molecular quantum numbers (MQN), which count different categories of atoms, bonds, polar groups, and topological features and categorize molecules by size, rigidity, and polarity. Despite its simplicity, MQN-space is relevant to biological activities. The MQN-mapplet allows localization of any molecule on the color-coded images, visualization of the molecules, and identification of analogs as neighbors on the MQN-map or in the original 42-dimensional MQN-space. No query molecule is necessary to start the exploration, which may be particularly attractive for nonchemists. To our knowledge, this type of interactive exploration tool is unprecedented for very large databases such as PubChem and GDB-13 (almost one billion molecules). The application is freely available for download at www.gdb.unibe.ch.

Stereoselective synthesis and structure determination of a bicyclo[3.3.2]decapeptide

By analogy to the structural diversity of covalent bond networks between atoms within organic molecules, one can design topologically diverse peptides from mathematical graphs by assigning amino acids to graph nodes and peptide bonds to graph edges. The key is to use diamino acids or amino diacids as equivalents of trivalent graph nodes, which enables a variety of graph topologies beyond the standard linear and monocyclic graphs in natural peptides. Here the bicyclic decapeptide A1FGk2VFPE1AG2 (1b) was prepared and crystallized to assign its bridge stereochemistry. The bridge configuration appears as planned by the chirality of the branching amino acids. Bicyclization furthermore depends on the presence of matched chiralities in the branching amino acids. The stereoselective formation of the second bridge opens the way for the synthesis of a large family of bicyclic peptides as promising new scaffolds for drug design.

Transesophageal echocardiography in cryptogenic stroke and patent foramen ovale: analysis of putative high-risk features from the risk of paradoxical embolism database

BACKGROUND Patent foramen ovale (PFO) is associated with cryptogenic stroke (CS), although the pathogenicity of a discovered PFO in the setting of CS is typically unclear. Transesophageal echocardiography features such as PFO size, associated hypermobile septum, and presence of a right-to-left shunt at rest have all been proposed as markers of risk. The association of these transesophageal echocardiography features with other markers of pathogenicity has not been examined. METHODS AND RESULTS We used a recently derived score based on clinical and neuroimaging features to stratify patients with PFO and CS by the probability that their stroke is PFO-attributable. We examined whether high-risk transesophageal echocardiography features are seen more frequently in patients more likely to have had a PFO-attributable stroke (n=637) compared with those less likely to have a PFO-attributable stroke (n=657). Large physiologic shunt size was not more frequently seen among those with probable PFO-attributable strokes (odds ratio [OR], 0.92; P=0.53). The presence of neither a hypermobile septum nor a right-to-left shunt at rest was detected more often in those with a probable PFO-attributable stroke (OR, 0.80; P=0.45; OR, 1.15; P=0.11, respectively). CONCLUSIONS We found no evidence that the proposed transesophageal echocardiography risk markers of large PFO size, hypermobile septum, and presence of right-to-left shunt at rest are associated with clinical features suggesting that a CS is PFO-attributable. Additional tools to describe PFOs may be useful in helping to determine whether an observed PFO is incidental or pathogenically related to CS.