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

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Abstract

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.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0427-z) contains supplementary material, which is available to authorized users.

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Most cited references 26

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Impact of mutant p53 functional properties on TP53 mutation patterns and tumor phenotype: lessons from recent developments in the IARC TP53 database.

Audrey Petitjean, Ewy Mathe, Shunsuke Kato … (2007)

The tumor suppressor gene TP53 is frequently mutated in human cancers. More than 75% of all mutations are missense substitutions that have been extensively analyzed in various yeast and human cell assays. The International Agency for Research on Cancer (IARC) TP53 database (www-p53.iarc.fr) compiles all genetic variations that have been reported in TP53. Here, we present recent database developments that include new annotations on the functional properties of mutant proteins, and we perform a systematic analysis of the database to determine the functional properties that contribute to the occurrence of mutational "hotspots" in different cancer types and to the phenotype of tumors. This analysis showed that loss of transactivation capacity is a key factor for the selection of missense mutations, and that difference in mutation frequencies is closely related to nucleotide substitution rates along TP53 coding sequence. An interesting new finding is that in patients with an inherited missense mutation, the age at onset of tumors was related to the functional severity of the mutation, mutations with total loss of transactivation activity being associated with earlier cancer onset compared to mutations that retain partial transactivation capacity. Furthermore, 80% of the most common mutants show a capacity to exert dominant-negative effect (DNE) over wild-type p53, compared to only 45% of the less frequent mutants studied, suggesting that DNE may play a role in shaping mutation patterns. These results provide new insights into the factors that shape mutation patterns and influence mutation phenotype, which may have clinical interest.

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Whole-exome sequencing and clinical interpretation of FFPE tumor samples to guide precision cancer medicine

Eliezer Allen, Nikhil Wagle, Petar Stojanov … (2014)

Translating whole exome sequencing (WES) for prospective clinical use may impact the care of cancer patients; however, multiple innovations are necessary for clinical implementation. These include: (1) rapid and robust WES from formalin-fixed paraffin embedded (FFPE) tumor tissue, (2) analytical output similar to data from frozen samples, and (3) clinical interpretation of WES data for prospective use. Here, we describe a prospective clinical WES platform for archival FFPE tumor samples. The platform employs computational methods for effective clinical analysis and interpretation of WES data. When applied retrospectively to 511 exomes, the interpretative framework revealed a “long tail” of somatic alterations in clinically important genes. Prospective application of this approach identified clinically relevant alterations in 15/16 patients. In one patient, previously undetected findings guided clinical trial enrollment leading to an objective clinical response. Overall, this methodology may inform the widespread implementation of precision cancer medicine.

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Realizing the promise of cancer predisposition genes.

Nazneen Rahman (2014)

Genes in which germline mutations confer highly or moderately increased risks of cancer are called cancer predisposition genes. More than 100 of these genes have been identified, providing important scientific insights in many areas, particularly the mechanisms of cancer causation. Moreover, clinical utilization of cancer predisposition genes has had a substantial impact on diagnosis, optimized management and prevention of cancer. The recent transformative advances in DNA sequencing hold the promise of many more cancer predisposition gene discoveries, and greater and broader clinical applications. However, there is also considerable potential for incorrect inferences and inappropriate clinical applications. Realizing the promise of cancer predisposition genes for science and medicine will thus require careful navigation.

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Author and article information

Contributors

Kenneth D. Doig: ken.doig@petermac.org

Journal

Journal ID (nlm-ta): Genome Med

Journal ID (iso-abbrev): Genome Med

Title: Genome Medicine

Publisher: BioMed Central (London )

ISSN (Electronic): 1756-994X

Publication date (Electronic): 24 April 2017

Publication date PMC-release: 24 April 2017

Publication date Collection: 2017

Volume: 9

Electronic Location Identifier: 38

Affiliations

[1 ]ISNI 0000000403978434, GRID grid.1055.1, Research Division, , Peter MacCallum Cancer Centre, ; East Melbourne, VIC Australia

[2 ]ISNI 0000000403978434, GRID grid.1055.1, Department of Pathology, , Peter MacCallum Cancer Centre, ; East Melbourne, VIC Australia

[3 ]ISNI 0000 0001 2179 088X, GRID grid.1008.9, Sir Peter MacCallum Department of Oncology, , University of Melbourne, ; Melbourne, VIC Australia

[4 ]ISNI 0000 0001 2179 088X, GRID grid.1008.9, Department of Pathology, , University of Melbourne, ; Melbourne, VIC Australia

[5 ]ISNI 0000 0001 2179 088X, GRID grid.1008.9, Department of Medical Biology, , University of Melbourne, ; Melbourne, VIC Australia

[6 ]GRID grid.1042.7, Bioinformatics Division, , The Walter and Eliza Hall Institute of Medical Research, ; Parkville, VIC Australia

[7 ]ISNI 0000 0004 4902 0432, GRID grid.1005.4, , Children’s Cancer Institute, University of New South Wales, ; Sydney, NSW Australia

[8 ]ISNI 0000000403978434, GRID grid.1055.1, , Peter MacCallum Cancer Centre, ; 305 Grattan Street, Parkville, VIC 3000 Australia

Article

Publisher ID: 427

DOI: 10.1186/s13073-017-0427-z

PMC ID: 5404673

PubMed ID: 28438193

SO-VID: 0f35295f-8b25-45a9-a831-2473344c6257

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 22 August 2016

Date accepted : 7 April 2017

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;

Award ID: 1054618

Award Recipient : Anthony T. Papenfuss

Funded by: Laby Foundation

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ScienceOpen disciplines: Molecular medicine

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

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Abstract

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Electronic supplementary material

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Most cited references 26

Impact of mutant p53 functional properties on TP53 mutation patterns and tumor phenotype: lessons from recent developments in the IARC TP53 database.

Whole-exome sequencing and clinical interpretation of FFPE tumor samples to guide precision cancer medicine

Realizing the promise of cancer predisposition genes.

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