Genotype-phenotype associations among panel-based TP53+ subjects.

Purpose: Panel testing has led to the identification of TP53 pathogenic/likely pathogenic (P/LP) variant carriers (TP53+) who exhibit a broad range of phenotypes. We sought to evaluate and compare genotype-phenotype associations among TP53+ panel-ascertained subjects.

Methods: Between 2012 and 2017, 317 TP53+ subjects (279 females and 38 males) identified through panel testing at one testing laboratory were found to have evaluable clinical histories and molecular results.

A Bayesian framework for efficient and accurate variant prediction.

There is a growing need to develop variant prediction tools capable of assessing a wide spectrum of evidence. We present a Bayesian framework that involves aggregating pathogenicity data across multiple in silico scores on a gene-by-gene basis and multiple evidence statistics in both quantitative and qualitative forms, and performs 5-tiered variant classification based on the resulting probability credible interval. When evaluated in 1,161 missense variants, our gene-specific in silico model-based meta-predictor yielded an area under the curve (AUC) of 96.

Promoter Variants Are Not Associated With Common Cancers: Implications for Multigene Panel Testing.

Purpose: mutations are associated with breast, colon, endometrial, kidney, and thyroid cancers. Most promoter alterations, however, are characterized as variants of unknown significance, and their contribution to cancer risk is unclear.

Materials And Methods: Personal and family histories of 88,333 patients undergoing analysis as part of multigene panel testing (MGPT) were retrospectively reviewed.

Discovery and information-theoretic characterization of transcription factor binding sites that act cooperatively.

Transcription factor binding to the surface of DNA regulatory regions is one of the primary causes of regulating gene expression levels. A probabilistic approach to model protein-DNA interactions at the sequence level is through position weight matrices (PWMs) that estimate the joint probability of a DNA binding site sequence by assuming positional independence within the DNA sequence. Here we construct conditional PWMs that depend on the motif signatures in the flanking DNA sequence, by conditioning known binding site loci on the presence or absence of additional binding sites in the flanking sequence of each site's locus.

Conformational sampling of peptides in cellular environments.

Biological systems provide a complex environment that can be understood in terms of its dielectric properties. High concentrations of macromolecules and cosolvents effectively reduce the dielectric constant of cellular environments, thereby affecting the conformational sampling of biomolecules. To examine this effect in more detail, the conformational preference of alanine dipeptide, poly-alanine, and melittin in different dielectric environments is studied with computer simulations based on recently developed generalized Born methodology.