Racial Disparities in Cancer Guideline-Concordant Treatment Using Surveillance, Epidemiology, and End Results Data for Patients With NSCLC.

Introduction: Despite efforts to achieve health care equality, racial/ethnic disparities persist in lung cancer survival in the United States, with non-Hispanic Black patients experiencing higher mortality compared with non-Hispanic Whites. Previous research often focused on single treatments, overlooking the broad range of options available. We aimed to highlight disparities in survival and receipt of comprehensive lung cancer treatment by developing a guideline-concordant initial treatment (GCIT) indicator based on disease stage and recommended treatment.

A generalized Kirkwood implicit solvent for the polarizable AMOEBA protein model.

Computational simulation of biomolecules can provide important insights into protein design, protein-ligand binding interactions, and ab initio biomolecular folding, among other applications. Accurate treatment of the solvent environment is essential in such applications, but the use of explicit solvents can add considerable cost. Implicit treatment of solvent effects using a dielectric continuum model is an attractive alternative to explicit solvation since it is able to describe solvation effects without the inclusion of solvent degrees of freedom.

Assessing variants of uncertain significance implicated in hearing loss using a comprehensive deafness proteome.

Hearing loss is the leading sensory deficit, affecting ~ 5% of the population. It exhibits remarkable heterogeneity across 223 genes with 6328 pathogenic missense variants, making deafness-specific expertise a prerequisite for ascribing phenotypic consequences to genetic variants. Deafness-implicated variants are curated in the Deafness Variation Database (DVD) after classification by a genetic hearing loss expert panel and thorough informatics pipeline.

Assessing Variants of Uncertain Significance Implicated in Hearing Loss Using a Comprehensive Deafness Proteome.

Hearing loss is the leading sensory deficit, affecting ~ 5% of the population. It exhibits remarkable heterogeneity across 223 genes with 6,328 pathogenic missense variants, making deafness-specific expertise a prerequisite for ascribing phenotypic consequences to genetic variants. Deafness-implicated variants are curated in the Deafness Variation Database (DVD) after classification by a genetic hearing loss expert panel and thorough informatics pipeline.

AudioGene: refining the natural history of KCNQ4, GSDME, WFS1, and COCH-associated hearing loss.

Autosomal dominant non-syndromic hearing loss (ADNSHL) displays gene-specific progression of hearing loss, which is amenable to sequential audioprofiling. We sought to refine the natural history of ADNSHL by examining audiometric data in 5-year increments. 2175 audiograms were included from four genetic causes of ADNSHL-KCNQ4 (DFNA2), GSDME (DFNA5), WFS1 (DFNA6/14/38), and COCH (DFNA9).

Implicit Solvents for the Polarizable Atomic Multipole AMOEBA Force Field.

Computational protein design, ab initio protein/RNA folding, and protein-ligand screening can be too computationally demanding for explicit treatment of solvent. For these applications, implicit solvent offers a compelling alternative, which we describe here for the polarizable atomic multipole AMOEBA force field based on three treatments of continuum electrostatics: numerical solutions to the nonlinear and linearized versions of the Poisson-Boltzmann equation (PBE), the domain-decomposition conductor-like screening model (ddCOSMO) approximation to the PBE, and the analytic generalized Kirkwood (GK) approximation. The continuum electrostatics models are combined with a nonpolar estimator based on novel cavitation and dispersion terms.

A comparative analysis of genetic hearing loss phenotypes in European/American and Japanese populations.

We present detailed comparative analyses to assess population-level differences in patterns of genetic deafness between European/American and Japanese cohorts with non-syndromic hearing loss. One thousand eighty-three audiometric test results (921 European/American and 162 Japanese) from members of 168 families (48 European/American and 120 Japanese) with non-syndromic hearing loss secondary to pathogenic variants in one of three genes (KCNQ4, TECTA, WFS1) were studied. Audioprofile characteristics, specific mutation types, and protein domains were considered in the comparative analyses.

Structural Insights into Hearing Loss Genetics from Polarizable Protein Repacking.

Hearing loss is associated with ∼8100 mutations in 152 genes, and within the coding regions of these genes are over 60,000 missense variants. The majority of these variants are classified as "variants of uncertain significance" to reflect our inability to ascribe a phenotypic effect to the observed amino acid change. A promising source of pathogenicity information is biophysical simulation, although input protein structures often contain defects because of limitations in experimental data and/or only distant homology to a template.

Machine learning with the TCGA-HNSC dataset: improving usability by addressing inconsistency, sparsity, and high-dimensionality.

Background: In the era of precision oncology and publicly available datasets, the amount of information available for each patient case has dramatically increased. From clinical variables and PET-CT radiomics measures to DNA-variant and RNA expression profiles, such a wide variety of data presents a multitude of challenges. Large clinical datasets are subject to sparsely and/or inconsistently populated fields.

Audioprofile Surfaces: The 21st Century Audiogram.

Objective: To present audiometric data in 3 dimensions by considering age as an addition dimension.

Methods: Audioprofile surfaces (APSs) were fitted to a set of audiograms by plotting each measurement of an audiogram as an independent point in 3 dimensions with the x, y, and z axes representing frequency, hearing loss in dB, and age, respectively.

Results: Using the Java-based APS viewer as a standalone application, APSs were pre-computed for 34 loci.

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays.

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives.

Utilizing ethnic-specific differences in minor allele frequency to recategorize reported pathogenic deafness variants.

Ethnic-specific differences in minor allele frequency impact variant categorization for genetic screening of nonsyndromic hearing loss (NSHL) and other genetic disorders. We sought to evaluate all previously reported pathogenic NSHL variants in the context of a large number of controls from ethnically distinct populations sequenced with orthogonal massively parallel sequencing methods. We used HGMD, ClinVar, and dbSNP to generate a comprehensive list of reported pathogenic NSHL variants and re-evaluated these variants in the context of 8,595 individuals from 12 populations and 6 ethnically distinct major human evolutionary phylogenetic groups from three sources (Exome Variant Server, 1000 Genomes project, and a control set of individuals created for this study, the OtoDB).

Cordova: web-based management of genetic variation data.

Unlabelled: Cordova is an out-of-the-box solution for building and maintaining an online database of genetic variations integrated with pathogenicity prediction results from popular algorithms. Our primary motivation for developing this system is to aid researchers and clinician-scientists in determining the clinical significance of genetic variations. To achieve this goal, Cordova provides an interface to review and manually or computationally curate genetic variation data as well as share it for clinical diagnostics and the advancement of research.

Advancing genetic testing for deafness with genomic technology.

Background: Non-syndromic hearing loss (NSHL) is the most common sensory impairment in humans. Until recently its extreme genetic heterogeneity precluded comprehensive genetic testing. Using a platform that couples targeted genomic enrichment (TGE) and massively parallel sequencing (MPS) to sequence all exons of all genes implicated in NSHL, we tested 100 persons with presumed genetic NSHL and in so doing established sequencing requirements for maximum sensitivity and defined MPS quality score metrics that obviate Sanger validation of variants.

Computational identification of operon-like transcriptional loci in eukaryotes.

Operons are primarily a bacterial phenomenon, not commonly observed in eukaryotes. However, new research indicates that operons are found in higher organisms as well. There are instances of operons found in C.

A genome-wide association study for primary open angle glaucoma and macular degeneration reveals novel Loci.

Glaucoma and age-related macular degeneration (AMD) are the two leading causes of visual loss in the United States. We utilized a novel study design to perform a genome-wide association for both primary open angle glaucoma (POAG) and AMD. This study design utilized a two-stage process for hypothesis generation and validation, in which each disease cohort was utilized as a control for the other.

Prioritization of retinal disease genes: an integrative approach.

The discovery of novel disease-associated variations in genes is often a daunting task in highly heterogeneous disease classes. We seek a generalizable algorithm that integrates multiple publicly available genomic data sources in a machine-learning model for the prioritization of candidates identified in patients with retinal disease. To approach this problem, we generate a set of feature vectors from publicly available microarray, RNA-seq, and ChIP-seq datasets of biological relevance to retinal disease, to observe patterns in gene expression specificity among tissues of the body and the eye, in addition to photoreceptor-specific signals by the CRX transcription factor.

Exon-level expression profiling of ocular tissues.

The normal gene expression profiles of the tissues in the eye are a valuable resource for considering genes likely to be involved with disease processes. We profiled gene expression in ten ocular tissues from human donor eyes using Affymetrix Human Exon 1.0 ST arrays.

AudioGene: predicting hearing loss genotypes from phenotypes to guide genetic screening.

Autosomal dominant nonsyndromic hearing loss (ADNSHL) is a common and often progressive sensory deficit. ADNSHL displays a high degree of genetic heterogeneity and varying rates of progression. Accurate, comprehensive, and cost-effective genetic testing facilitates genetic counseling and provides valuable prognostic information to affected individuals.

Prediction of cochlear implant performance by genetic mutation: the spiral ganglion hypothesis.

Background: Up to 7% of patients with severe-to-profound deafness do not benefit from cochlear implantation. Given the high surgical implantation and clinical management cost of cochlear implantation (>$1 million lifetime cost), prospective identification of the worst performers would reduce unnecessary procedures and healthcare costs. Because cochlear implants bypass the membranous labyrinth but rely on the spiral ganglion for functionality, we hypothesize that cochlear implant (CI) performance is dictated in part by the anatomic location of the cochlear pathology that underlies the hearing loss.

Coex-Rank: An approach incorporating co-expression information for combined analysis of microarray data.

Microarrays have been widely used to study differential gene expression at the genomic level. They can also provide genome-wide co-expression information. Biologically related datasets from independent studies are publicly available, which requires robust combined approaches for integration and validation.

Informatics methods to enable sharing of quantitative imaging research data.

Introduction: The National Cancer Institute Quantitative Research Network (QIN) is a collaborative research network whose goal is to share data, algorithms and research tools to accelerate quantitative imaging research. A challenge is the variability in tools and analysis platforms used in quantitative imaging. Our goal was to understand the extent of this variation and to develop an approach to enable sharing data and to promote reuse of quantitative imaging data in the community.

Swarm rat chondrosarcoma cells as an in vivo model: lung colonization and effects of tissue environment on tumor growth.

Swarm rat chondrosarcoma cells have been used extensively for biochemical studies of extra-cellular matrix metabolism in cartilage. However, these cells also possess tumor-like behavior in vivo and are useful in investigation of chondrosarcoma biology. the current study was designed to develop a metastatic model using swarm rat chondrosarcoma cells, and to assess the effect of tissue-environment on tumor behavior in vivo.