Comparison of Pathogenicity Prediction Tools on Somatic Variants

Suybeng, Voreak; Koeppel, Florence; Harlé, Alexandre; Rouleau, Etienne

doi:10.1016/j.jmoldx.2020.08.007

Cited by 20 publications

(22 citation statements)

References 24 publications

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“…This is recognised by the ACMG guidelines for germline variants and AMP guidelines for somatic variant curation by specifying pathogenicity predictors must only be applied as supporting evidence in variant classification [ 1 ]. A detailed comparison of pathogenicity prediction tools may be found in Suybeng et al [ 37 ]. Machine-learning approaches such as natural language processing to train curation models from medical literature, and deep-learning methods for variants may provide greater value in increasing the throughput of clinical variant interpretation, and perhaps provide the greatest hope in relieving the curation bottleneck [ 38 , 39 ].…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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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.

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Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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“…The performance of variant impact prediction methods is hard to assess unambiguously. Independent studies (Chan et al 2007 ; Dong et al 2015 ; Ghosh et al 2017 ; Gunning et al 2020 ; Leong et al 2015 ; Li et al 2018 ; Livesey and Marsh 2020 ; Michels et al 2019 ; Miosge et al 2015 ; Suybeng et al 2020 ; Tian et al 2019 ; Yadegari and Majidzadeh 2019 ) have compared a limited number of methods each, using specific sets of variants and evaluation tests, but ignoring potential training circularities, and making cutoff assumptions that may not fit each method equally well. In contrast, efforts to systematically and objectively assess variant impact prediction methods come from the Critical Assessment of Genome Interpretation (CAGI) community.…”

Section: Main Textmentioning

confidence: 99%

Genome interpretation using in silico predictors of variant impact

et al. 2022

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Estimating the effects of variants found in disease driver genes opens the door to personalized therapeutic opportunities. Clinical associations and laboratory experiments can only characterize a tiny fraction of all the available variants, leaving the majority as variants of unknown significance (VUS). In silico methods bridge this gap by providing instant estimates on a large scale, most often based on the numerous genetic differences between species. Despite concerns that these methods may lack reliability in individual subjects, their numerous practical applications over cohorts suggest they are already helpful and have a role to play in genome interpretation when used at the proper scale and context. In this review, we aim to gain insights into the training and validation of these variant effect predicting methods and illustrate representative types of experimental and clinical applications. Objective performance assessments using various datasets that are not yet published indicate the strengths and limitations of each method. These show that cautious use of in silico variant impact predictors is essential for addressing genome interpretation challenges.

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“…The assessment and identification of some somatic variants of KRAS mutations that are pathogenic (oncogenic) and function could be of strong interest to including patients with these variants into clinical trials [ 231 , 232 , 233 ]. Along with the development of high-covering NGS panels, the underlying point is whether a NSCLC with an unknown variant of KRAS should or should not be included in a precision oncology trial.…”

Section: Opportunities and Challenges For The Thoracic Pathologistsmentioning

confidence: 99%

“…Along with the development of high-covering NGS panels, the underlying point is whether a NSCLC with an unknown variant of KRAS should or should not be included in a precision oncology trial. Well-established pathogenic and benign variants are quite easily recognized, but there is still an urgent need to broaden the classification of a variant of interest from the unknown significance category, from either the potentially benign to the potentially pathogenic (oncogenic) categories, to support the inclusion of a patient in a clinical trial [ 231 , 232 , 233 ].…”

Section: Opportunities and Challenges For The Thoracic Pathologistsmentioning

confidence: 99%

Daily Practice Assessment of KRAS Status in NSCLC Patients: A New Challenge for the Thoracic Pathologist Is Right around the Corner

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Hofman

Brest

et al. 2022

Cancers

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KRAS mutations are among the most frequent genomic alterations identified in non-squamous non-small cell lung carcinomas (NS-NSCLC), notably in lung adenocarcinomas. In most cases, these mutations are mutually exclusive, with different genomic alterations currently known to be sensitive to therapies targeting EGFR, ALK, BRAF, ROS1, and NTRK. Recently, several promising clinical trials targeting KRAS mutations, particularly for KRAS G12C-mutated NSCLC, have established new hope for better treatment of patients. In parallel, other studies have shown that NSCLC harboring co-mutations in KRAS and STK11 or KEAP1 have demonstrated primary resistance to immune checkpoint inhibitors. Thus, the assessment of the KRAS status in advanced-stage NS-NSCLC has become essential to setting up an optimal therapeutic strategy in these patients. This stimulated the development of new algorithms for the management of NSCLC samples in pathology laboratories and conditioned reorganization of optimal health care of lung cancer patients by the thoracic pathologists. This review addresses the recent data concerning the detection of KRAS mutations in NSCLC and focuses on the new challenges facing pathologists in daily practice for KRAS status assessment.

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Comparison of Pathogenicity Prediction Tools on Somatic Variants

Cited by 20 publications

References 24 publications

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

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

Genome interpretation using in silico predictors of variant impact

Daily Practice Assessment of KRAS Status in NSCLC Patients: A New Challenge for the Thoracic Pathologist Is Right around the Corner

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