Orthogonal Comparison of Four Plasma NGS Tests With Tumor Suggests Technical Factors are a Major Source of Assay Discordance.

PURPOSE: Discordance between plasma and tumor variant calling has been attributed primarily to tumor heterogeneity, whereas technical variables remain largely unexplored. MATERIALS AND METHODS: To measure these variables, we tested four next-generation sequencing (NGS) gene panel assays for mutations in circulating tumor DNA (ctDNA) using replicate sets of 24 plasma samples and compared the results with matched tumor-normal tissue pairs. RESULTS: Our orthogonal approach identified false-negative (FN) and false-positive (FP) variants with high confidence and revealed substantial variability among the ctDNA assays, with a range of sensitivity (38% to 89%) and positive predictive value (36% to 80%). Most discordance in our cross-vendor study was observed below 1% variant allele frequency. FP variants displayed mutational biases and tended to be novel variants not found in somatic databases. Of the 56 unique variants called by all four ctDNA assays, 41 (68%) resulted from technical discordance. CONCLUSION: These findings suggest that most NGS assay discordance is a result of technical variations and, to a lesser extent, biologic factors such as clonal hematopoiesis of indeterminate potential and tumor heterogeneity.

Prioritisation of structural variant calls in cancer genomes.

Sensitivity of short read DNA-sequencing for gene fusion detection is improving, but is hampered by the significant amount of noise composed of uninteresting or false positive hits in the data. In this paper we describe a tiered prioritisation approach to extract high impact gene fusion events from existing structural variant calls. Using cell line and patient DNA sequence data we improve the annotation and interpretation of structural variant calls to best highlight likely cancer driving fusions. We also considerably improve on the automated visualisation of the high impact structural variants to highlight the effects of the variants on the resulting transcripts. The resulting framework greatly improves on readily detecting clinically actionable structural variants.

Defining actionable mutations for oncology therapeutic development.

Genomic profiling of tumours in patients in clinical trials enables rapid testing of multiple hypotheses to confirm which genomic events determine likely responder groups for targeted agents. A key challenge of this new capability is defining which specific genomic events should be classified as 'actionable' (that is, potentially responsive to a targeted therapy), especially when looking for early indications of patient subgroups likely to be responsive to new drugs. This Opinion article discusses some of the different approaches being taken in early clinical development to define actionable mutations, and describes our strategy to address this challenge in early-stage exploratory clinical trials.

Disambiguate: An open-source application for disambiguating two species in next generation sequencing data from grafted samples.

Grafting of cell lines and primary tumours is a crucial step in the drug development process between cell line studies and clinical trials. Disambiguate is a program for computationally separating the sequencing reads of two species derived from grafted samples. Disambiguate operates on DNA or RNA-seq alignments to the two species and separates the components at very high sensitivity and specificity as illustrated in artificially mixed human-mouse samples. This allows for maximum recovery of data from target tumours for more accurate variant calling and gene expression quantification. Given that no general use open source algorithm accessible to the bioinformatics community exists for the purposes of separating the two species data, the proposed Disambiguate tool presents a novel approach and improvement to performing sequence analysis of grafted samples. Both Python and C++ implementations are available and they are integrated into several open and closed source pipelines. Disambiguate is open source and is freely available at https://github.com/AstraZeneca-NGS/disambiguate.

Ecotype diversity and conversion in Photobacterium profundum strains.

Photobacterium profundum is a cosmopolitan marine bacterium capable of growth at low temperature and high hydrostatic pressure. Multiple strains of P. profundum have been isolated from different depths of the ocean and display remarkable differences in their physiological responses to pressure. The genome sequence of the deep-sea piezopsychrophilic strain Photobacterium profundum SS9 has provided some clues regarding the genetic features required for growth in the deep sea. The sequenced genome of Photobacterium profundum strain 3TCK, a non-piezophilic strain isolated from a shallow-water environment, is now available and its analysis expands the identification of unique genomic features that correlate to environmental differences and define the Hutchinsonian niche of each strain. These differences range from variations in gene content to specific gene sequences under positive selection. Genome plasticity between Photobacterium bathytypes was investigated when strain 3TCK-specific genes involved in photorepair were introduced to SS9, demonstrating that horizontal gene transfer can provide a mechanism for rapid colonisation of new environments.

Genome sequence of the marine photoheterotrophic bacterium Erythrobacter sp. strain NAP1.

Here we report the full genome sequence of marine phototrophic bacterium Erythrobacter sp. strain NAP1. The 3.3-Mb genome contains a full set of photosynthetic genes organized in one 38.9-kb cluster; however, it does not contain genes for CO(2) or N(2) fixation, thereby confirming that the organism is a photoheterotroph.