Homologous Recombination Repair Deficiency: An Overview for Pathologists.

The repair of DNA double-stranded breaks relies on the homologous recombination repair pathway and is critical to cell function. However, this pathway can be lost in some cancers such as breast, ovarian, endometrial, pancreatic, and prostate cancers. Cancer cells with homologous recombination deficiency (HRD) are sensitive to targeted inhibition of poly-ADP ribose polymerase (PARP), a key component of alternative backup DNA repair pathways. Identifying patients with cancer with HRD biomarkers allows the identification of patients likely to benefit from PARP inhibitor therapies. In this study, we describe the causes of HRD, the underlying molecular changes resulting from HRD that form the basis of different molecular HRD assays, and discuss the issues around their clinical use. This overview is directed toward practicing pathologists wishing to be informed of this new predictive biomarker, as PARP inhibitors are increasingly used in standard care settings.

Shariant platform: Enabling evidence sharing across Australian clinical genetic-testing laboratories to support variant interpretation.

Sharing genomic variant interpretations across laboratories promotes consistency in variant assertions. A landscape analysis of Australian clinical genetic-testing laboratories in 2017 identified that, despite the national-accreditation-body recommendations encouraging laboratories to submit genotypic data to clinical databases, fewer than 300 variants had been shared to the ClinVar public database. Consultations with Australian laboratories identified resource constraints limiting routine application of manual processes, consent issues, and differences in interpretation systems as barriers to sharing. This information was used to define key needs and solutions required to enable national sharing of variant interpretations. The Shariant platform, using both the GRCh37 and GRCh38 genome builds, was developed to enable ongoing sharing of variant interpretations and associated evidence between Australian clinical genetic-testing laboratories. Where possible, two-way automated sharing was implemented so that disruption to laboratory workflows would be minimized. Terms of use were developed through consultation and currently restrict access to Australian clinical genetic-testing laboratories. Shariant was designed to store and compare structured evidence, to promote and record resolution of inter-laboratory classification discrepancies, and to streamline the submission of variant assertions to ClinVar. As of December 2021, more than 14,000 largely prospectively curated variant records from 11 participating laboratories have been shared. Discrepant classifications have been identified for 11% (28/260) of variants submitted by more than one laboratory. We have demonstrated that co-design with clinical laboratories is vital to developing and implementing a national variant-interpretation sharing effort. This approach has improved inter-laboratory concordance and enabled opportunities to standardize interpretation practices.

Findings from precision oncology in the clinic: rare, novel variants are a significant contributor to scaling molecular diagnostics.

BACKGROUND: Next generation sequencing for oncology patient management is now routine in clinical pathology laboratories. Although wet lab, sequencing and pipeline tasks are largely automated, the analysis of variants for clinical reporting remains largely a manual task. The increasing volume of sequencing data and the limited availability of genetic experts to analyse and report on variants in the data is a key scalability limit for molecular diagnostics. METHOD: To determine the impact and size of the issue, we examined the longitudinally compiled genetic variants from 48,036 cancer patients over a six year period in a large cancer hospital from ten targeted cancer panel tests in germline, solid tumour and haematology contexts using hybridization capture and amplicon assays. This testing generated 24,168,398 sequenced variants of which 23,255 (8214 unique) were clinically reported. RESULTS: Of the reported variants, 17,240 (74.1%) were identified in more than one assay which allowed curated variant data to be reused in later reports. The remainder, 6015 (25.9%) were not subsequently seen in later assays and did not provide any reuse benefit. The number of new variants requiring curation has significantly increased over time from 1.72 to 3.73 variants per sample (292 curated variants per month). Analysis of the 23,255 variants reported, showed 28.6% (n = 2356) were not present in common public variant resources and therefore required de novo curation. These in-house only variants were enriched for indels, tumour suppressor genes and from solid tumour assays. CONCLUSION: This analysis highlights the significant percentage of variants not present within common public variant resources and the level of non-recurrent variants that consequently require greater curation effort. Many of these variants are unique to a single patient and unlikely to appear in other patients reflecting the personalised nature of cancer genomics. This study depicts the real-world situation for pathology laboratories faced with curating increasing numbers of low-recurrence variants while needing to expedite the process of manual variant curation. In the absence of suitably accurate automated methods, new approaches are needed to scale oncology diagnostics for future genetic testing volumes.

Tumour mutational burden: an overview for pathologists.

Cancer immunotherapy holds great promise and has shown durable responses in many patients; however, these responses are not uniform in all patients or all tumour streams. There is an ongoing clinical need for objective diagnostic biomarkers to identify patients that will respond to immunotherapies. Tumour mutational burden (TMB) is a diagnostic biomarker that can stratify cancer patients for response to immune checkpoint inhibitor therapies. It is commonly defined as the average number of somatic mutations per megabase in a tumour exome. Here we describe the TMB biomarker, how it is determined, its underlying molecular basis, the relationship to neoantigens and the issues around its clinical use. This overview is directed toward practising pathologists wishing to be informed of this predictive biomarker.

Canary: an atomic pipeline for clinical amplicon assays.

BACKGROUND: High throughput sequencing requires bioinformatics pipelines to process large volumes of data into meaningful variants that can be translated into a clinical report. These pipelines often suffer from a number of shortcomings: they lack robustness and have many components written in multiple languages, each with a variety of resource requirements. Pipeline components must be linked together with a workflow system to achieve the processing of FASTQ files through to a VCF file of variants. Crafting these pipelines requires considerable bioinformatics and IT skills beyond the reach of many clinical laboratories. RESULTS: Here we present Canary, a single program that can be run on a laptop, which takes FASTQ files from amplicon assays through to an annotated VCF file ready for clinical analysis. Canary can be installed and run with a single command using Docker containerization or run as a single JAR file on a wide range of platforms. Although it is a single utility, Canary performs all the functions present in more complex and unwieldy pipelines. All variants identified by Canary are 3' shifted and represented in their most parsimonious form to provide a consistent nomenclature, irrespective of sequencing variation. Further, proximate in-phase variants are represented as a single HGVS 'delins' variant. This allows for correct nomenclature and consequences to be ascribed to complex multi-nucleotide polymorphisms (MNPs), which are otherwise difficult to represent and interpret. Variants can also be annotated with hundreds of attributes sourced from MyVariant.info to give up to date details on pathogenicity, population statistics and in-silico predictors. CONCLUSIONS: Canary has been used at the Peter MacCallum Cancer Centre in Melbourne for the last 2 years for the processing of clinical sequencing data. By encapsulating clinical features in a single, easily installed executable, Canary makes sequencing more accessible to all pathology laboratories. Canary is available for download as source or a Docker image at https://github.com/PapenfussLab/Canary under a GPL-3.0 License.

PathOS: a decision support system for reporting high throughput sequencing of cancers in clinical diagnostic laboratories.

BACKGROUND: The increasing affordability of DNA sequencing has allowed it to be widely deployed in pathology laboratories. However, this has exposed many issues with the analysis and reporting of variants for clinical diagnostic use. Implementing a high-throughput sequencing (NGS) clinical reporting system requires a diverse combination of capabilities, statistical methods to identify variants, global variant databases, a validated bioinformatics pipeline, an auditable laboratory workflow, reproducible clinical assays and quality control monitoring throughout. These capabilities must be packaged in software that integrates the disparate components into a useable system. RESULTS: To meet these needs, we developed a web-based application, PathOS, which takes variant data from a patient sample through to a clinical report. PathOS has been used operationally in the Peter MacCallum Cancer Centre for two years for the analysis, curation and reporting of genetic tests for cancer patients, as well as the curation of large-scale research studies. PathOS has also been deployed in cloud environments allowing multiple institutions to use separate, secure and customisable instances of the system. Increasingly, the bottleneck of variant curation is limiting the adoption of clinical sequencing for molecular diagnostics. PathOS is focused on providing clinical variant curators and pathology laboratories with a decision support system needed for personalised medicine. While the genesis of PathOS has been within cancer molecular diagnostics, the system is applicable to NGS clinical reporting generally. CONCLUSIONS: The widespread availability of genomic sequencers has highlighted the limited availability of software to support clinical decision-making in molecular pathology. PathOS is a system that has been developed and refined in a hospital laboratory context to meet the needs of clinical diagnostics. The software is available as a set of Docker images and source code at https://github.com/PapenfussLab/PathOS .

Complete genome sequence of the frog pathogen Mycobacterium ulcerans ecovar Liflandii.

In 2004, a previously undiscovered mycobacterium resembling Mycobacterium ulcerans (the agent of Buruli ulcer) was reported in an outbreak of a lethal mycobacteriosis in a laboratory colony of the African clawed frog Xenopus tropicalis. This mycobacterium makes mycolactone and is one of several strains of M. ulcerans-like mycolactone-producing mycobacteria recovered from ectotherms around the world. Here, we describe the complete 6,399,543-bp genome of this frog pathogen (previously unofficially named "Mycobacterium liflandii"), and we show that it has undergone an intermediate degree of reductive evolution between the M. ulcerans Agy99 strain and the fish pathogen Mycobacterium marinum M strain. Like M. ulcerans Agy99, it has the pMUM mycolactone plasmid, over 200 chromosomal copies of the insertion sequence IS2404, and a high proportion of pseudogenes. However, M. liflandii has a larger genome that is closer in length, sequence, and architecture to M. marinum M than to M. ulcerans Agy99, suggesting that the M. ulcerans Agy99 strain has undergone accelerated evolution. Scrutiny of the genes specifically lost suggests that M. liflandii is a tryptophan, tyrosine, and phenylalanine auxotroph. A once-extensive M. marinum-like secondary metabolome has also been diminished through reductive evolution. Our analysis shows that M. liflandii, like M. ulcerans Agy99, has the characteristics of a niche-adapted mycobacterium but also has several distinctive features in important metabolic pathways that suggest that it is responding to different environmental pressures, supporting earlier proposals that it could be considered an M. ulcerans ecotype, hence the name M. ulcerans ecovar Liflandii.

On the origin of Mycobacterium ulcerans, the causative agent of Buruli ulcer.

BACKGROUND: Mycobacterium ulcerans is an unusual bacterial pathogen with elusive origins. While closely related to the aquatic dwelling M. marinum, M. ulcerans has evolved the ability to produce the immunosuppressive polyketide toxin mycolactone and cause the neglected tropical disease Buruli ulcer. Other mycolactone-producing mycobacteria (MPM) have been identified in fish and frogs and given distinct species designations (M. pseudoshottsii, M. shinshuense, M. liflandii and M. marinum), however the evolution of M. ulcerans and its relationship to other MPM has not been defined. Here we report the comparative analysis of whole genome sequences from 30 MPM and five M. marinum. RESULTS: A high-resolution phylogeny based on genome-wide single nucleotide polymorphisms (SNPs) showed that M. ulcerans and all other MPM represent a single clonal group that evolved from a common M. marinum progenitor. The emergence of the MPM was driven by the acquisition of the pMUM plasmid encoding genes for the biosynthesis of mycolactones. This change was accompanied by the loss of at least 185 genes, with a significant overrepresentation of genes associated with cell wall functions. Cell wall associated genes also showed evidence of substantial adaptive selection, suggesting cell wall remodeling has been critical for the survival of MPM. Fine-grain analysis of the MPM complex revealed at least three distinct lineages, one of which comprised a highly clonal group, responsible for Buruli ulcer in Africa and Australia. This indicates relatively recent transfer of M. ulcerans between these continents, which represent the vast majority of the global Buruli ulcer burden. Our data provide SNPs and gene sequences that can differentiate M. ulcerans lineages, suitable for use in the diagnosis and surveillance of Buruli ulcer. CONCLUSIONS: M. ulcerans and all mycolactone-producing mycobacteria are specialized variants of a common Mycobacterium marinum progenitor that have adapted to live in restricted environments. Examination of genes lost or retained and now under selective pressure suggests these environments might be aerobic, and extracellular, where slow growth, production of an immune suppressor, cell wall remodeling, loss or modification of cell wall antigens, and biofilm-forming ability provide a survival advantage. These insights will guide our efforts to find the elusive reservoir(s) of M. ulcerans and to understand transmission of Buruli ulcer.