Improving gene regulatory network inference and assessment: The importance of using network structure.

Gene regulatory networks are graph models representing cellular transcription events. Networks are far from complete due to time and resource consumption for experimental validation and curation of the interactions. Previous assessments have shown the modest performance of the available network inference methods based on gene expression data. Here, we study several caveats on the inference of regulatory networks and methods assessment through the quality of the input data and gold standard, and the assessment approach with a focus on the global structure of the network. We used synthetic and biological data for the predictions and experimentally-validated biological networks as the gold standard (ground truth). Standard performance metrics and graph structural properties suggest that methods inferring co-expression networks should no longer be assessed equally with those inferring regulatory interactions. While methods inferring regulatory interactions perform better in global regulatory network inference than co-expression-based methods, the latter is better suited to infer function-specific regulons and co-regulation networks. When merging expression data, the size increase should outweigh the noise inclusion and graph structure should be considered when integrating the inferences. We conclude with guidelines to take advantage of inference methods and their assessment based on the applications and available expression datasets.

Preexisting Antibodies to an F(ab')2 Antibody Therapeutic and Novel Method for Immunogenicity Assessment.

Anti-therapeutic antibodies (ATAs) may impact drug exposure and activity and induce immune complex mediated toxicity; therefore the accurate measurement of ATA is important for the analysis of drug safety and efficacy. Preexisting ATAs to the hinge region of anti-Delta like ligand 4 (anti-DLL4) F(ab')2, a potential antitumor therapeutic, were detected in cynomolgus monkey serum, which presented a challenge in developing assays for detecting treatment induced ATA. A total ATA assay was developed using a bridging ELISA that detected both anti-CDR and anti-framework ATA including anti-hinge reactivity. A competition assay that could detect 500 ng/mL of anti-CDR ATA in the presence of preexisting ATA was also developed to determine ATA specific to the anti-DLL4 F(ab')2 CDR using anti-DLL4 F(ab')2 and a control F(ab')2. We used these assay methods in a cynomolgus monkey in vivo study to successfully evaluate total and anti-CDR ATA. The preexisting anti-hinge reactivity was also observed to a lesser extent in human serum, and a similar approach could be applied for specific immunogenicity assessment in clinical trials.