Germline BRCA1/2 alteration has been linked to an increased risk of hereditary breast and ovarian cancer syndromes. As a result, genetic testing, based on NGS, allows us to identify a high number of variants of uncertain significance (VUS) or conflicting interpretation of pathogenicity (CIP) variants. The identification of CIP/VUS is often considered inconclusive and clinically not actionable for the patients' and unaffected carriers' management. In this context, their assessment and classification remain a significant challenge. The aim of the study was to investigate whether the in silico prediction tools (PolyPhen-2, SIFT, Mutation Taster and PROVEAN) could predict the potential clinical impact and significance of BRCA1/2 CIP/VUS alterations, eventually impacting the clinical management of Breast Cancer subjects. In a cohort of 860 BC patients, 10.6% harbored BRCA1 or BRCA2 CIP/VUS alterations, mostly observed in BRCA2 sequences (85%). Among them, forty-two out of fifty-five alterations were predicted as damaging, with at least one in silico that used tools. Prediction agreement of the four tools was achieved in 45.5% of patients. Moreover, the highest consensus was obtained in twelve out of forty-two (28.6%) mutations by considering three out of four in silico algorithms. The use of prediction tools may help to identify variants with a potentially damaging effect. The lack of substantial agreement between the different algorithms suggests that the bioinformatic approaches should be combined with the personal and family history of the cancer patients.
In Silico Prediction of BRCA1 and BRCA2 Variants with Conflicting Clinical Interpretation in a Cohort of Breast Cancer Patients
Stefania Stella
;Silvia Rita Vitale;Michele Massimino;Federica MARTORANA;Irene Tornabene;Cristina Tomarchio;Melissa Drago;Giuliana Pavone;Cristina Gorgone;Chiara Barone;Sebastiano Bianca;Livia Manzella
2024-01-01
Abstract
Germline BRCA1/2 alteration has been linked to an increased risk of hereditary breast and ovarian cancer syndromes. As a result, genetic testing, based on NGS, allows us to identify a high number of variants of uncertain significance (VUS) or conflicting interpretation of pathogenicity (CIP) variants. The identification of CIP/VUS is often considered inconclusive and clinically not actionable for the patients' and unaffected carriers' management. In this context, their assessment and classification remain a significant challenge. The aim of the study was to investigate whether the in silico prediction tools (PolyPhen-2, SIFT, Mutation Taster and PROVEAN) could predict the potential clinical impact and significance of BRCA1/2 CIP/VUS alterations, eventually impacting the clinical management of Breast Cancer subjects. In a cohort of 860 BC patients, 10.6% harbored BRCA1 or BRCA2 CIP/VUS alterations, mostly observed in BRCA2 sequences (85%). Among them, forty-two out of fifty-five alterations were predicted as damaging, with at least one in silico that used tools. Prediction agreement of the four tools was achieved in 45.5% of patients. Moreover, the highest consensus was obtained in twelve out of forty-two (28.6%) mutations by considering three out of four in silico algorithms. The use of prediction tools may help to identify variants with a potentially damaging effect. The lack of substantial agreement between the different algorithms suggests that the bioinformatic approaches should be combined with the personal and family history of the cancer patients.File | Dimensione | Formato | |
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In Silico Prediction of BRCA1 and BRCA2 Variants with Conflicting Clinical Interpretation in a Cohort of Breast Cancer Patients.pdf
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