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Introduction Tumor mutational burden (TMB) has emerged as a clinically relevant biomarker that may be associated with immune checkpoint inhibitor efficacy. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Objective Here we describe the in-depth evaluation of bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples from a phase III clinical trial. Methods In the CheckMate 026 clinical trial, TMB was retrospectively assessed in 312 patients with non-small-cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or standard-of-care chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne® CDx assay. Results TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90). Conclusions Parameter variation can impact TMB calculations, highlighting the need for standardization. Encouragingly, differences between assays could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms, and centers is achievable.

Purpose Hearing loss (HL) is the most common sensory disorder in children. Prompt molecular diagnosis may guide screening and management; especially in syndromic cases when HL is the single presenting feature. Exome sequencing (ES)is an appealing diagnostic tool for HL as the genetic causes are highly heterogeneous. Methods ES was performed on a prospective cohort of 43 probands with HL. Sequence data were analyzed for primary and secondary findings. Capture and coverage analysis was performed for genes and variants associated with HL. Results The diagnostic rate using ES was 37.2% compared to 15.8% with clinical HL panel. Secondary findings were discovered in three patients. For 247 genes associated with HL, 94.7% of the exons were targeted for capture and 81.7% of these exons were covered at 20× or greater. Further analysis of 454 randomly selected HL-associated variants showed 89% were targeted for capture and 75% were covered at a read depth of at least 20×. Conclusion ES has an improved yield to clinical testing and may capture diagnoses not initially considered due to subtle clinical phenotypes. Technical challenges were identified, including inadequate capture and coverage of HL genes. Additional considerations of ES include secondary findings, cost, and turnaround time.

PURPOSE: As massively parallel sequencing is increasingly being used for clinical decision-making, it has become critical to understand parameters that affect sequencing quality and to establish methods for measuring and reporting clinical sequencing standards. In this report, we propose a definition for reduced coverage regions and have established a set of standards for variant calling in clinical sequencing applications. METHODS: To enable sequencing centers to assess the regions of poor sequencing quality in their own data, we optimized and used a tool (ExCid) to identify reduced coverage loci within genes or regions of particular interest. We used this framework to examine sequencing data from 500 patients generated in ten projects from sequencing centers in the NHGRI/NCI Clinical Sequencing Exploratory Research (CSER) Consortium. RESULTS: This approach identified reduced coverage regions in clinically relevant genes, including known clinically relevant loci that were uniquely missed at individual centers, in multiple centers, and in all centers. CONCLUSIONS: This report provides a process roadmap for clinical sequencing centers looking to perform similar analyses on their data.

Background/Aims: In a family with congenital hyperinsulinism (HI), first described in the 1950s by McQuarrie, we examined the genetic locus and clinical phenotype of a novel form of dominant HI. Methods: We surveyed 25 affected individuals, 7 of whom participated in tests of insulin dysregulation (24-hour fasting, oral glucose and protein tolerance tests). To identify the disease locus and potential disease-associated mutations we performed linkage analysis, whole transcriptome sequencing, whole genome sequencing, gene capture, and next generation sequencing. Results: Most affecteds were diagnosed with HI before age one and 40% presented with a seizure. All affecteds responded well to diazoxide. Affecteds failed to adequately suppress insulin secretion following oral glucose tolerance test or prolonged fasting; none had protein-sensitive hypoglycemia. Linkage analysis mapped the HI locus to Chr10q21-22, a region containing 48 genes. Three novel noncoding variants were found in hexokinase 1 (HK1) and one missense variant in the coding region of DNA2. Conclusion: Dominant, diazoxide-responsive HI in this family maps to a novel locus on Chr10q21-22. HK1 is the more attractive disease gene candidate since a mutation interfering with the normal suppression of HK1 expression in beta-cells could readily explain the hypoglycemia phenotype of this pedigree.

Understanding the relationship between chemical structure and function is a ubiquitous problem within the fields of chemistry and biology. Simulation approaches attack the problem utilizing physics to understand a given process at the particle level. Unfortunately, these approaches are often too expensive for many problems of interest. Informatics approaches attack the problem with empirical analysis of descriptions of chemical structure. The issue in these methods is how to describe molecules in a manner that facilitates accurate and general calculation of molecular properties. Here, we present a novel approach that utilizes aspects of simulation and informatics in order to formulate structure-property relationships. We show how supervised learning can be utilized to overcome the sampling problem in simulation approaches. Likewise, we show how learning can be achieved based on molecular descriptions that are rooted in the physics of dynamic intermolecular forces. We apply the approach to three problems including the analysis of corticosteroid binding globulin ligand binding affinity, identification of formylpeptide receptor ligands, and identification of resveratrol analogues capable of inhibiting activation of transcription factor nuclear factor kappaB.

Background Conditions associated with sudden cardiac arrest/death (SCA/D) in youth often have a genetic etiology. While SCA/D is uncommon, a pro-active family screening approach may identify these inherited structural and electrical abnormalities prior to symptomatic events and allow appropriate surveillance and treatment. This study investigated the diagnostic utility of exome sequencing (ES) by evaluating the capture and coverage of genes related to SCA/D. Methods Samples from 102 individuals (13 with known molecular etiologies for SCA/D, 30 individuals without known molecular etiologies for SCA/D and 59 with other conditions) were analyzed following exome capture and sequencing at an average read depth of 100X. Reads were mapped to human genome GRCh37 using Novoalign, and post-processing and analysis was done using Picard and GATK. A total of 103 genes (2,190 exons) related to SCA/D were used as a primary filter. An additional 100 random variants within the targeted genes associated with SCA/D were also selected and evaluated for depth of sequencing and coverage. Although the primary objective was to evaluate the adequacy of depth of sequencing and coverage of targeted SCA/D genes and not for primary diagnosis, all patients who had SCA/D (known or unknown molecular etiologies) were evaluated with the project’s variant analysis pipeline to determine if the molecular etiologies could be successfully identified. Results The majority of exons (97.6 %) were captured and fully covered on average at minimum of 20x sequencing depth. The proportion of unique genomic positions reported within poorly covered exons remained small (4 %). Exonic regions with less coverage reflect the need to enrich these areas to improve coverage. Despite limitations in coverage, we identified 100 % of cases with a prior known molecular etiology for SCA/D, and analysis of an additional 30 individuals with SCA/D but no known molecular etiology revealed a diagnostic answer in 5/30 (17 %). We also demonstrated 95 % of 100 randomly selected reported variants within our targeted genes would have been picked up on ES based on our coverage analysis. Conclusions ES is a helpful clinical diagnostic tool for SCA/D given its potential to successfully identify a molecular diagnosis, but clinicians should be aware of limitations of available platforms from technical and diagnostic perspectives. Electronic supplementary material The online version of this article (doi:10.1186/s40246-015-0038-y) contains supplementary material, which is available to authorized users.

Background The ability to capture and sequence large contiguous DNA fragments represents a significant advancement towards the comprehensive characterization of complex genomic regions. While emerging sequencing platforms are capable of producing several kilobases-long reads, the fragment sizes generated by current DNA target enrichment technologies remain a limiting factor, producing DNA fragments generally shorter than 1 kbp. The DNA enrichment methodology described herein, Region-Specific Extraction (RSE), produces DNA segments in excess of 20 kbp in length. Coupling this enrichment method to appropriate sequencing platforms will significantly enhance the ability to generate complete and accurate sequence characterization of any genomic region without the need for reference-based assembly. Results RSE is a long-range DNA target capture methodology that relies on the specific hybridization of short (20-25 base) oligonucleotide primers to selected sequence motifs within the DNA target region. These capture primers are then enzymatically extended on the 3’-end, incorporating biotinylated nucleotides into the DNA. Streptavidin-coated beads are subsequently used to pull-down the original, long DNA template molecules via the newly synthesized, biotinylated DNA that is bound to them. We demonstrate the accuracy, simplicity and utility of the RSE method by capturing and sequencing a 4 Mbp stretch of the major histocompatibility complex (MHC). Our results show an average depth of coverage of 164X for the entire MHC. This depth of coverage contributes significantly to a 99.94 % total coverage of the targeted region and to an accuracy that is over 99.99 %. Conclusions RSE represents a cost-effective target enrichment method capable of producing sequencing templates in excess of 20 kbp in length. The utility of our method has been proven to generate superior coverage across the MHC as compared to other commercially available methodologies, with the added advantage of producing longer sequencing templates amenable to DNA sequencing on recently developed platforms. Although our demonstration of the method does not utilize these DNA sequencing platforms directly, our results indicate that the capture of long DNA fragments produce superior coverage of the targeted region. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2836-6) contains supplementary material, which is available to authorized users.