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Searching for the needle in the haystack: the application of a literature searching tool to retrieve information to allow optimum classification of MMR variants
  • Varun Kaushik,
  • Finlay Macrae,
  • John Paul Plazzer
Varun Kaushik
The Royal Melbourne Hospital

Corresponding Author:[email protected]

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Finlay Macrae
The Royal Melbourne Hospital
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John Paul Plazzer
The Royal Melbourne Hospital
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Background: Pathogenic variants in the mismatch repair (MMR) genes are the drivers of Lynch Syndrome; optimal variant interpretation is required for the management of suspected and confirmed cases. Given the onerous nature of extracting information related to genetic variants, literature searching tools which harness artificial intelligence may aid in retrieving information to allow optimum variant classification. Methods: In this study, we described the nature of discordance in a sample of 80 variants from a list of variants requiring updating by InSiGHT for ClinGen by comparing their existing InSiGHT classifications on ClinVar. Variants were searched for using a traditional method (Google Scholar) and literature searching tool (Mastermind Genomenon) independently. Descriptive statistics were used to compare: the number of articles before and after screening for relevance and the number of relevant articles unique to either method. Results: 916 articles were returned by both methods. Mastermind averaged four relevant articles per search, Google Scholar, three. Of relevant Mastermind articles, 193/308 (62.7%) were unique to it, compared to 87/202, (43.0%) for Google Scholar. All 6/80 (20%) variants with pathogenic or likely pathogenic InSiGHT classifications have newer VUS assertions on ClinVar. Conclusion: Mastermind on average returned a more relevant literature search. Google Scholar still found unique information, suggesting that Mastermind could play a complementary role.
28 Sep 2020Submitted to Advanced Genetics
28 Sep 2020Submission Checks Completed
28 Sep 2020Assigned to Editor
05 Oct 2020Editorial Decision: Revise Minor
02 Nov 20201st Revision Received
02 Nov 2020Submission Checks Completed
02 Nov 2020Assigned to Editor
02 Nov 2020Review(s) Completed, Editorial Evaluation Pending
06 Nov 2020Reviewer(s) Assigned
14 Dec 2020Editorial Decision: Revise Minor
12 Jan 20212nd Revision Received
12 Jan 2021Review(s) Completed, Editorial Evaluation Pending
12 Jan 2021Submission Checks Completed
12 Jan 2021Assigned to Editor
14 Jan 2021Editorial Decision: Accept