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

Implementation and Clinical Adoption of Precision Oncology Workflows Across a Healthcare Network

BACKGROUND

Precision oncology relies on molecular diagnostics, and the value-proposition of modern healthcare networks promises a higher standard of care across partner sites. We present the results of a clinical pilot to standardize precision oncology workflows.

METHODS

Workflows are defined as the development, roll-out, and updating of disease-specific molecular order sets. We tracked the timeline, composition, and effort of consensus meetings to define the combination of molecular tests. To assess clinical impact, we examined order set adoption over a two-year period (before and after roll-out) across all gastrointestinal and hepatopancreatobiliary (GI) malignancies, and by provider location within the network.

RESULTS

Development of 12 disease center-specific order sets took ~9 months, and the average number of tests per indication changed from 2.9 to 2.8 (P = .74). After roll-out, we identified significant increases in requests for GI patients (17%; P < .001), compliance with testing recommendations (9%; P < .001), and the fraction of "abnormal" results (6%; P < .001). Of 1088 GI patients, only 3 received targeted agents based on findings derived from non-recommended orders (1 before and 2 after roll-out); indicating that our practice did not negatively affect patient treatments. Preliminary analysis showed 99% compliance by providers in network sites, confirming the adoption of the order sets across the network.

CONCLUSION

Our study details the effort of establishing precision oncology workflows, the adoption pattern, and the absence of harm from the reduction of non-recommended orders. Establishing a modifiable communication tool for molecular testing is an essential component to optimize patient care via precision oncology.

In vitro and in vivo drug screens of tumor cells identify novel therapies for high-risk child cancer

Biomarkers which better match anticancer drugs with cancer driver genes hold the promise of improved clinical responses and cure rates. We developed a precision medicine platform of rapid high-throughput drug screening (HTS) and patient-derived xenografting (PDX) of primary tumor tissue, and evaluated its potential for treatment identification among 56 consecutively enrolled high-risk pediatric cancer patients, compared with conventional molecular genomics and transcriptomics. Drug hits were seen in the majority of HTS and PDX screens, which identified therapeutic options for 10 patients for whom no targetable molecular lesions could be found. Screens also provided orthogonal proof of drug efficacy suggested by molecular analyses and negative results for some molecular findings. We identified treatment options across the whole testing platform for 70% of patients. Only molecular therapeutic recommendations were provided to treating oncologists and led to a change in therapy in 53% of patients, of whom 29% had clinical benefit. These data indicate that in vitro and in vivo drug screening of tumor cells could increase therapeutic options and improve clinical outcomes for high-risk pediatric cancer patients.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01214-y.

TRACEBACK: Testing of Historical Tubo-Ovarian Cancer Patients for Hereditary Risk Genes as a Cancer Prevention Strategy in Family Members

PURPOSE

Tubo-ovarian cancer (TOC) is a sentinel cancer for BRCA1 and BRCA2 pathogenic variants (PVs). Identification of a PV in the first member of a family at increased genetic risk (the proband) provides opportunities for cancer prevention in other at-risk family members. Although Australian testing rates are now high, PVs in patients with TOC whose diagnosis predated revised testing guidelines might have been missed. We assessed the feasibility of detecting PVs in this population to enable genetic risk reduction in relatives.

PATIENTS AND METHODS

In this pilot study, deceased probands were ascertained from research cohort studies, identification by a relative, and gynecologic oncology clinics. DNA was extracted from archival tissue or stored blood for panel sequencing of 10 risk-associated genes. Testing of deceased probands ascertained through clinic records was performed with a consent waiver.

RESULTS

We identified 85 PVs in 84 of 787 (11%) probands. Familial contacts of 39 of 60 (65%) deceased probands with an identified recipient (60 of 84; 71%) have received a written notification of results, with follow-up verbal contact made in 85% (33 of 39). A minority of families (n = 4) were already aware of the PV. For many (29 of 33; 88%), the genetic result provided new information and referral to a genetic service was accepted in most cases (66%; 19 of 29). Those who declined referral (4 of 29) were all male next of kin whose family member had died more than 10 years before.

CONCLUSION

We overcame ethical and logistic challenges to demonstrate that retrospective genetic testing to identify PVs in previously untested deceased probands with TOC is feasible. Understanding reasons for a family member's decision to accept or decline a referral will be important for guiding future TRACEBACK projects.

Genetic testing of deceased patients allows identification of at-risk families for cancer prevention

Knowledge bases and software support for variant interpretation in precision oncology

Precision oncology is a rapidly evolving interdisciplinary medical specialty. Comprehensive cancer panels are becoming increasingly available at pathology departments worldwide, creating the urgent need for scalable cancer variant annotation and molecularly informed treatment recommendations. A wealth of mainly academia-driven knowledge bases calls for software tools supporting the multi-step diagnostic process. We derive a comprehensive list of knowledge bases relevant for variant interpretation by a review of existing literature followed by a survey among medical experts from university hospitals in Germany. In addition, we review cancer variant interpretation tools, which integrate multiple knowledge bases. We categorize the knowledge bases along the diagnostic process in precision oncology and analyze programmatic access options as well as the integration of knowledge bases into software tools. The most commonly used knowledge bases provide good programmatic access options and have been integrated into a range of software tools. For the wider set of knowledge bases, access options vary across different parts of the diagnostic process. Programmatic access is limited for information regarding clinical classifications of variants and for therapy recommendations. The main issue for databases used for biological classification of pathogenic variants and pathway context information is the lack of standardized interfaces. There is no single cancer variant interpretation tool that integrates all identified knowledge bases. Specialized tools are available and need to be further developed for different steps in the diagnostic process.

HIV is associated with an increased risk of age-related clonal hematopoiesis among older adults

People with human immunodeficiency virus (HIV) have higher rates of certain comorbidities, particularly cardiovascular disease and cancer, than people without HIV^1-5. In view of observations that somatic mutations associated with age-related clonal hematopoiesis (CH) are linked to similar comorbidities in the general population^6-10, we hypothesized that CH may be more prevalent in people with HIV. To address this issue, we established a prospective cohort study, the ARCHIVE study (NCT04641013), in which 220 HIV-positive and 226 HIV-negative participants aged 55 years or older were recruited in Australia. Demographic characteristics, clinical data and peripheral blood were collected to assess the presence of CH mutations and to identify potential risk factors for and clinical sequelae of CH. In total, 135 CH mutations were identified in 100 (22.4%) of 446 participants. CH was more prevalent in HIV-positive participants than in HIV-negative participants (28.2% versus 16.8%, P = 0.004), overall and across all age groups; the adjusted odds ratio for having CH in those with HIV was 2.16 (95% confidence interval 1.34-3.48, P = 0.002). The most common genes mutated overall were DNMT3A (47.4%), TET2 (20.0%) and ASXL1 (13.3%). CH and HIV infection were independently associated with increases in blood parameters and biomarkers associated with inflammation. These data suggest a selective advantage for the emergence of CH in the context of chronic infection and inflammation related to HIV infection.

A new tool CovReport generates easy-to-understand sequencing coverage summary for diagnostic reports

In order to properly interpret the results of a diagnostic gene panel sequencing test, gene coverage needs to be taken into consideration. If coverage is too low, an additional re-sequencing test is needed to make sure that a pathogenic variant is not missed. To facilitate the interpretation of coverage data, we designed CovReport, a novel easy-to-use visualization tool. CovReport generates a concise coverage summary that allows one-glance assessment of the sequencing test performance. Both gene-level and exon-level coverage can be immediately appreciated and taken into consideration for further medical decisions. CovReport does not require complex installation and can thus be easily implemented in any diagnostic laboratory setting. A user-friendly interface generates a graphic summary of coverage that can be directly included in the diagnostic report. In addition to a stand-alone version, we also provide a command line version of CovReport that can be integrated into any bioinformatics pipeline. This flexible tool is now part of routine sequencing analysis at the Department of Medical Genetics at La Timone Hospital (Marseille, France). CovReport is available at http://jdotsoft.com/CovReport.php. It is implemented in Java and supported on Windows, Mac OS X and Linux.

Novel bioinformatics quality control metric for next-generation sequencing experiments in the clinical context

As the use of next-generation sequencing (NGS) for the Mendelian diseases diagnosis is expanding, the performance of this method has to be improved in order to achieve higher quality. Typically, performance measures are considered to be designed in the context of each application and, therefore, account for a spectrum of clinically relevant variants. We present EphaGen, a new computational methodology for bioinformatics quality control (QC). Given a single NGS dataset in BAM format and a pre-compiled VCF-file of targeted clinically relevant variants it associates this dataset with a single arbiter parameter. Intrinsically, EphaGen estimates the probability to miss any variant from the defined spectrum within a particular NGS dataset. Such performance measure virtually resembles the diagnostic sensitivity of given NGS dataset. Here we present case studies of the use of EphaGen in context of BRCA1/2 and CFTR sequencing in a series of 14 runs across 43 blood samples and 504 publically available NGS datasets. EphaGen is superior to conventional bioinformatics metrics such as coverage depth and coverage uniformity. We recommend using this software as a QC step in NGS studies in the clinical context. Availability: https://github.com/m4merg/EphaGen or https://hub.docker.com/r/m4merg/ephagen.

Mitogen-Activated Protein Kinase Pathway Inhibition for Redifferentiation of Radioiodine Refractory Differentiated Thyroid Cancer: An Evolving Protocol

Background: Some patients with metastatic differentiated thyroid cancer (DTC) lack iodine avidity and are therefore unsuitable for radioactive iodine (RAI) therapy. Limited experience suggests that single-agent selective mitogen-activated protein kinase (MAPK) pathway inhibitors can restore expression of the sodium-iodide symporter rendering RAI refractory (RAIR) DTC patients amenable to RAI therapy. The aim of this study was to assess the feasibility of mutation-guided MAPK-pathway blockade combined with thyroid hormone withdrawal (THW) for redifferentiation. Methods: This is a retrospective review of metastatic RAIR DTC and driver mutation in MAPK pathway, treated on a redifferentiation protocol. All patients had metastatic disease that had never been RAI-avid and/or imaging and biochemical progression despite treatment with RAI within the past 12 months. Patients with tumors harboring an NRAS mutation were treated with an MEK inhibitor (trametinib), and tumors with a BRAF^V600E mutation with combined BRAF and MEK inhibition (dabrafenib and trametinib; or vemurafenib and cobimetinib) for four weeks. Thyrotropin stimulation was performed by THW for four weeks. Restoration of RAI uptake was determined by ¹²⁴I positron emission tomography/computed tomography imaging. The response was assessed at least three months post-RAI. Results: From 2015 to 2017, six patients (age 45-70, four females) received redifferentiation therapy. Three patients had an NRAS mutation; two with follicular thyroid carcinoma (FTC) and one with a poorly differentiated thyroid carcinoma (PDTC); and three patients had a BRAF^V600E mutation and papillary thyroid carcinoma (PTC). One NRAS and all BRAF^V600E mutation cases demonstrated restoration of RAI uptake and proceeded to RAI therapy with a median follow-up of 16.6 months (range 13.5-42.3 months). The patient with an NRAS mutation and two of three patients with a BRAF^V600E demonstrated partial imaging response beyond a three-month follow-up. Grade 3 adverse events (acneiform rash) were observed in two patients with NRAS mutations. Conclusions: Mutation-guided MAPK pathway inhibition with MEK inhibitor or a combination of BRAF inhibitor and MEK inhibitor under concurrent THW is a feasible and a promising strategy to redifferentiate RAIR DTC, thereby rendering them suitable for RAI therapy with satisfactory retention following treatment.

Variant Call Format-Diagnostic Annotation and Reporting Tool: A Customizable Analysis Pipeline for Identification of Clinically Relevant Genetic Variants in Next-Generation Sequencing Data

In this article, we introduce the variant call format-diagnostic annotation and reporting tool (VCF-DART), a customized analysis pipeline tool for the rapid annotation of variants from exome or genome sequencing and the generation of reports for genetic diagnostics. VCF-DART uses custom gene lists to categorize variants into specific analysis tiers and to subcategorize them on the basis of standard parameters to facilitate the rapid interrogation of potentially pathogenic variants by human operators. The tool uses publicly available databases to identify a range of data to assist with variant classification and curation processes and includes robust logging of parameters and database versions to allow comparison of analyses performed at different times. VCF-DART-an online analysis pipeline for next-generation sequencing data-is a platform agnostic tool that leverages the use of publicly available databases to improve a laboratory's calling ability and reduce analysis times long-term. It also runs highly efficiently and scales from desk and laptop machines to servers. Overall, VCF-DART provides a simple, customizable, and entirely open-source method to identify genetic variants that may be of clinical importance in a variety of genetically important conditions.

VIST - a Variant-Information Search Tool for precision oncology

BACKGROUND

Diagnosis and treatment decisions in cancer increasingly depend on a detailed analysis of the mutational status of a patient's genome. This analysis relies on previously published information regarding the association of variations to disease progression and possible interventions. Clinicians to a large degree use biomedical search engines to obtain such information; however, the vast majority of scientific publications focus on basic science and have no direct clinical impact. We develop the Variant-Information Search Tool (VIST), a search engine designed for the targeted search of clinically relevant publications given an oncological mutation profile.

RESULTS

VIST indexes all PubMed abstracts and content from ClinicalTrials.gov. It applies advanced text mining to identify mentions of genes, variants and drugs and uses machine learning based scoring to judge the clinical relevance of indexed abstracts. Its functionality is available through a fast and intuitive web interface. We perform several evaluations, showing that VIST's ranking is superior to that of PubMed or a pure vector space model with regard to the clinical relevance of a document's content.

CONCLUSION

Different user groups search repositories of scientific publications with different intentions. This diversity is not adequately reflected in the standard search engines, often leading to poor performance in specialized settings. We develop a search engine for the specific case of finding documents that are clinically relevant in the course of cancer treatment. We believe that the architecture of our engine, heavily relying on machine learning algorithms, can also act as a blueprint for search engines in other, equally specific domains. VIST is freely available at https://vist.informatik.hu-berlin.de/.

[Detection and interpretation of somatic variants in molecular pathology]

BACKGROUND

Due to the increasing amount of data and sources of information, data evaluation is a crucial step in parallel sequencing.

OBJECTIVES

Illustration of pitfalls in evaluating the variant list of parallel sequencing and recommendations regarding software tools and databases.

METHODS

Description of filtering steps used, demonstration of criteria and recommendations for annotation by examples from everyday work, comparative analysis of databases with somatic variants, description of the installation of an individualized database.

RESULTS

Variant filtering is a multistep process using information from different databases. The plausibility of variant calling should be verified using the Integrative Genomics Viewer and variants should be described according to the Human Genome Variation Society (HGVS) recommendations. Different databases, which all show advantages and disadvantages, are available for variant interpretation. An individualized database can be built up with the open-source tool cBioPortal.

CONCLUSIONS

Different tools and databases might be used for the analysis of parallel sequencing data. The application depends on, amongst other things, the local situation and has to be extensively validated.

CNspector: a web-based tool for visualisation and clinical diagnosis of copy number variation from next generation sequencing

Next Generation Sequencing is now routinely used in the practice of diagnostic pathology to detect clinically relevant somatic and germline sequence variations in patient samples. However, clinical assessment of copy number variations (CNVs) and large-scale structural variations (SVs) is still challenging. While tools exist to estimate both, their results are typically presented separately in tables or static plots which can be difficult to read and are unable to show the context needed for clinical interpretation and reporting. We have addressed this problem with CNspector, a multi-scale interactive browser that shows CNVs in the context of other relevant genomic features to enable fast and effective clinical reporting. We illustrate the utility of CNspector at different genomic scales across a variety of sample types in a range of case studies. We show how CNspector can be used for diagnosis and reporting of exon-level deletions, focal gene-level amplifications, chromosome and chromosome arm level amplifications/deletions and in complex genomic rearrangements. CNspector is a web-based clinical variant browser tailored to the clinical application of next generation sequencing for CNV assessment. We have demonstrated the utility of this interactive software in typical applications across a range of tissue types and disease contexts encountered in the context of diagnostic pathology. CNspector is written in R and the source code is available for download under the GPL3 Licence from https://github.com/PapenfussLab/CNspector.

Exploring the feasibility and utility of exome-scale tumour sequencing in a clinical setting

BACKGROUND

Technology has progressed from single gene panel to large-scale genomic sequencing. This is raising expectations from clinicians and patients alike. The utility and performance of this technology in a clinical setting needs to be evaluated.

AIM

This pilot study investigated the feasibility of using exome-scale sequencing (ESS) to identify molecular drivers within cancers in real-time for Precision Oncology in the clinic.

METHODS

Between March 2014 and March 2015, the Victorian Comprehensive Cancer Centre Alliance explored the feasibility and utility of ESS in a pilot study. DNA extracted from the tumour specimens underwent both ESS and targeted 'hotspot' sequencing (TS). Blood was taken for germline analysis. A multi-disciplinary molecular tumour board determined the clinical relevance of identified mutations; in particular, whether they were 'actionable' and/or 'druggable'.

RESULTS

Of 23 patients screened, 15 (65%) met the tissue requirements for genomic analysis. TS and ESS were successful in all cases. ESS identified pathogenic somatic variants in 73% (11/15 cases) versus 53% (8/15 cases) using TS. Clinically focused ESS identified 63 variants, consisting of 30 somatic variants (including all 13 identified by TS) and 33 germline variants. Overall, there were 48 unique variants. ESS had a clinical impact in 53% (8/15 cases); 47% (7/15 cases) were referred to the familial cancer clinic, and 'druggable' targets were identified in 53% (8/15 cases).

CONCLUSION

ESS of tumour DNA impacted clinical decision-making in 53%, with 20% more pathogenic variants identified through ESS than TS. The identification of germline variants in 47% was an unexpected finding.

ChronQC: a quality control monitoring system for clinical next generation sequencing

Summary

ChronQC is a quality control (QC) tracking system for clinical implementation of next-generation sequencing (NGS). ChronQC generates time series plots for various QC metrics to allow comparison of current runs to historical runs. ChronQC has multiple features for tracking QC data including Westgard rules for clinical validity, laboratory-defined thresholds and historical observations within a specified time period. Users can record their notes and corrective actions directly onto the plots for long-term recordkeeping. ChronQC facilitates regular monitoring of clinical NGS to enable adherence to high quality clinical standards.

Availability and implementation

ChronQC is freely available on GitHub (https://github.com/nilesh-tawari/ChronQC), Docker (https://hub.docker.com/r/nileshtawari/chronqc/) and the Python Package Index. ChronQC is implemented in Python and runs on all common operating systems (Windows, Linux and Mac OS X).

Contact

tawari.nilesh@gmail.com or pauline.c.ng@gmail.com.

Supplementary information

Supplementary data are available at Bioinformatics online.

An integrated clinical and genomic information system for cancer precision medicine

BACKGROUND

Increasing affordability of next-generation sequencing (NGS) has created an opportunity for realizing genomically-informed personalized cancer therapy as a path to precision oncology. However, the complex nature of genomic information presents a huge challenge for clinicians in interpreting the patient's genomic alterations and selecting the optimum approved or investigational therapy. An elaborate and practical information system is urgently needed to support clinical decision as well as to test clinical hypotheses quickly.

RESULTS

Here, we present an integrated clinical and genomic information system (CGIS) based on NGS data analyses. Major components include modules for handling clinical data, NGS data processing, variant annotation and prioritization, drug-target-pathway analysis, and population cohort explorer. We built a comprehensive knowledgebase of genes, variants, drugs by collecting annotated information from public and in-house resources. Structured reports for molecular pathology are generated using standardized terminology in order to help clinicians interpret genomic variants and utilize them for targeted cancer therapy. We also implemented many features useful for testing hypotheses to develop prognostic markers from mutation and gene expression data.

CONCLUSIONS

Our CGIS software is an attempt to provide useful information for both clinicians and scientists who want to explore genomic information for precision oncology.

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.

Settling the score: variant prioritization and Mendelian disease

When investigating Mendelian disease using exome or genome sequencing, distinguishing disease-causing genetic variants from the multitude of candidate variants is a complex, multidimensional task. Many prioritization tools and online interpretation resources exist, and professional organizations have offered clinical guidelines for review and return of prioritization results. In this Review, we describe the strengths and weaknesses of widely used computational approaches, explain their roles in the diagnostic and discovery process and discuss how they can inform (and misinform) expert reviewers. We place variant prioritization in the wider context of gene prioritization, burden testing and genotype-phenotype association, and we discuss opportunities and challenges introduced by whole-genome sequencing.

Managing the genomic revolution in cancer diagnostics

Molecular tumor profiling is now a routine part of patient care, revealing targetable genomic alterations and molecularly distinct tumor subtypes with therapeutic and prognostic implications. The widespread adoption of next-generation sequencing technologies has greatly facilitated clinical implementation of genomic data and opened the door for high-throughput multigene-targeted sequencing. Herein, we discuss the variability of cancer genetic profiling currently offered by clinical laboratories, the challenges of applying rapidly evolving medical knowledge to individual patients, and the need for more standardized population-based molecular profiling.