Neutralizing Antibody Assay Development with High Drug and Target Tolerance to Support Clinical Development of an Anti-TFPI Therapeutic Monoclonal Antibody.

Immunogenicity is a major challenge for protein therapeutics which can potentially reduce drug efficacy and safety and is often being monitored by anti-drug antibody (ADA) and neutralizing antibody (NAb) assays. Circulating targets and residual drugs in matrices can have significant impacts on accuracy of results from ADA and NAb assays, and sufficient drug and target tolerance for these assays are necessary. Here, we report the development of a competitive ligand binding (CLB) NAb assay for an anti-TFPI (tissue factor pathway inhibitor) monoclonal antibody (PF-06741086) with high drug and target tolerance to support ongoing clinical studies.

Approaches to Resolve False Reporting in Neutralizing Antibody Assays Caused by Reagent Leaching from Affinity Capture Elution Solid Phase.

Insufficient drug tolerance presents a major challenge in the development of neutralizing antibody (NAb) assays for biotherapeutics. Sample pre-treatment using solid-phase extraction with acid dissociation (SPEAD) is widely reported to improve drug tolerance. In this paper, a case study is presented in which SPEAD was used in conjunction with a competitive ligand binding NAb assay format.

A global transcriptional network connecting noncoding mutations to changes in tumor gene expression.

Although cancer genomes are replete with noncoding mutations, the effects of these mutations remain poorly characterized. Here we perform an integrative analysis of 930 tumor whole genomes and matched transcriptomes, identifying a network of 193 noncoding loci in which mutations disrupt target gene expression. These 'somatic eQTLs' (expression quantitative trait loci) are frequently mutated in specific cancer tissues, and the majority can be validated in an independent cohort of 3,382 tumors.

Identifying DNase I hypersensitive sites as driver distal regulatory elements in breast cancer.

Efforts to identify driver mutations in cancer have largely focused on genes, whereas non-coding sequences remain relatively unexplored. Here we develop a statistical method based on characteristics known to influence local mutation rate and a series of enrichment filters in order to identify distal regulatory elements harboring putative driver mutations in breast cancer. We identify ten DNase I hypersensitive sites that are significantly mutated in breast cancers and associated with the aberrant expression of neighboring genes.

Large-Scale Profiling Reveals the Influence of Genetic Variation on Gene Expression in Human Induced Pluripotent Stem Cells.

In this study, we used whole-genome sequencing and gene expression profiling of 215 human induced pluripotent stem cell (iPSC) lines from different donors to identify genetic variants associated with RNA expression for 5,746 genes. We were able to predict causal variants for these expression quantitative trait loci (eQTLs) that disrupt transcription factor binding and validated a subset of them experimentally. We also identified copy-number variant (CNV) eQTLs, including some that appear to affect gene expression by altering the copy number of intergenic regulatory regions.

Syntax compensates for poor binding sites to encode tissue specificity of developmental enhancers.

Transcriptional enhancers are short segments of DNA that switch genes on and off in response to a variety of intrinsic and extrinsic signals. Despite the discovery of the first enhancer more than 30 y ago, the relationship between primary DNA sequence and enhancer activity remains obscure. In particular, the importance of "syntax" (the order, orientation, and spacing of binding sites) is unclear.

Suboptimization of developmental enhancers.

Transcriptional enhancers direct precise on-off patterns of gene expression during development. To explore the basis for this precision, we conducted a high-throughput analysis of the Otx-a enhancer, which mediates expression in the neural plate of Ciona embryos in response to fibroblast growth factor (FGF) signaling and a localized GATA determinant. We provide evidence that enhancer specificity depends on submaximal recognition motifs having reduced binding affinities ("suboptimization").

Regulatory Principles Governing Tissue Specificity of Developmental Enhancers.

Transcriptional enhancers are short segments of genomic DNA (50 bp to 1 kb in length) that can work over long distances (≥1 Mb) to regulate gene expression in specific cells and tissues. Genomic assays have identified on the order of 400,000 to one million putative enhancers in the human genome (e.g.