Next step in molecular genetics of hereditary breast/ovarian cancer: Multigene panel testing in clinical actionably genes and prioritization algorithms in the study of variants of uncertain significance

Castillo-Guardiola, Verónica; Rosado-Jiménez, Laura; Sarabia-Meseguer, MaDesamparados; Marín-Vera, Miguel; Macías-Cerrolaza, José Antonio; García-Hernández, Rosario; Zafra-Poves, Marta; Sánchez-Henarejos, Pilar; Moreno-Locubiche, M.Á.; Cuevas-Tortosa, Encarnación; Arnaldos-Carrillo, María; Peña, Francisco Ayala de la; Alonso-Romero, José Luis; Noguera-Velasco, José Antonio; Ruíz-Espejo, Francisco

doi:10.1016/j.ejmg.2022.104468

Cited by 8 publications

(9 citation statements)

References 40 publications

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“…Up to 10 non-solved cases gained new insights due to the reevaluation of our prioritized variants. Our variant prioritization approach was also applied for VUS reclassification, a major challenge to unlock the diagnosis of rare pathologies [10,[55][56][57]. Indeed, in our IRD subcohort, top 5 genes with more deleterious variants in IRD solved cases, present a higher degree of uncertainty in variant annotation (proportion of VUS and deleterious variants) in unsolved IRD cases.…”

Section: Discussionmentioning

confidence: 99%

“…The pipeline is based on GATK 4.1 variant caller [26], and uses BWA-MEM aligner [27] to the GRCh37/hg19 reference genome. The following databases were used for annotation: i) allele frequency: gnomAD [17], 1000genomes [28], and Kaviar [29]; ii) pathogenicity prediction: SIFT [30], PolyPhen [31], CADD [32], LRT [33], M-CAP [34], MetaLR [35], MetaSVM [35], MutationAssesor [36], MutationTaster [37], PROVEAN [38], and FATHMM [39]; iii) splicing prediction: ada_score [40] and rf_score [40]; iv) ClinVar [41]; v) conservation: phastCons20way [42] and phyloP20way [43]; vi) gene tolerance to loss of function (LoF) variants: LoFtool [44], and ExACpLI [12]; vii) constrained coding regions by means of gnomAD_CCR [45]; and viii) potential loss of heterozygosity regions, annotated with PLINK [46]. The pipeline is available at https://github.com/TBLabFJD/VariantCallingFJD.…”

Section: Methodsmentioning

confidence: 99%

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Aggregated genomic data as cohort-specific allelic frequencies can boost variants and genes prioritization in non-solved cases of inherited retinal dystrophies

Iancu

Perea-Romero

Núñez‐Moreno

et al. 2022

Preprint

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BackgroundThe introduction of next-generation sequencing in the diagnosis of genetic diseases has increased the known repertoire of causal variants and genes involved, as well as the amount of genomic information produced, that is not always shared or reused.MethodsWe built an allelic frequency database for a heterogeneous cohort of genetic diseases to explore the aggregated genomic information and boost the diagnosis in inherited retinal dystrophies (IRD). We retrospectively selected 5683 index-cases with clinical exome available, 1766 with IRD, and the rest with diverse genetic diseases. In our IRD cohort, 46% of the patients do not have conclusive diagnosis at the time of writing. We calculated the specific allele-frequencies of the solved and non-solved IRD subcohorts and compared them with suitable pseudocontrols that were used to prioritize variants. In addition, we developed a method to highlight genes with more frequent pathogenic variants in non-solved IRD cases than in pseudocontrols weighted by the increment of benign variants in the same comparison. Our resource was also used to calculate the carrier frequency of deleterious variants in IRD genes.ResultsPrioritized variants were significantly enriched in deleterious variants in non-solved IRD cases but not in solved. Focusing on non-solved IRD cases, we prioritized variants with a significant increment of frequencies in cases compared to pseudocontrols. Among them, eight variants may contribute to explain the phenotype of 10 cases. Applied to variants of uncertain significance (VUS) monitored in our laboratory, we detected 11 more frequent in IRD than in pseudocontrols, and 10 of them were reclassified as likely-pathogenic according to ACMG guidelines. We also identified 18 genes with an accumulated pathogenicity in non-solved IRD samples for further studies that provided new insights in five cases. Most prevalent genes carrying pathogenic mutations are ABCA4 (∼7%) and USH2A (∼3%).ConclusionsA cohort-specific database of allele frequencies is able to diagnose cryptic non-solved IRD cases, reclassify VUS, propose candidate genes, and calculate CF on genes of interest. The database operates as an engine providing new hypotheses in non-solved cases as well as offering new resources for genetic counselling.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Aggregated genomic data as cohort-specific allelic frequencies can boost variants and genes prioritization in non-solved cases of inherited retinal dystrophies

Iancu

Perea-Romero

Núñez‐Moreno

et al. 2022

Preprint

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show abstract

“…Up to eight non-solved cases gained new insights due to the reevaluation of our prioritized variants. Our variant prioritization approach was also applied for VUS reclassification, a major challenge to unlock the diagnosis of rare pathologies [ 10 , 30 , 31 , 32 ]. Indeed, in our IRD subcohort, the top five genes with more deleterious variants in IRD solved cases present a higher degree of uncertainty in variant annotation (the proportion of VUS and deleterious variants) in unsolved IRD cases.…”

Section: Discussionmentioning

confidence: 99%

Aggregated Genomic Data as Cohort-Specific Allelic Frequencies can Boost Variants and Genes Prioritization in Non-Solved Cases of Inherited Retinal Dystrophies

Iancu

Perea-Romero

Núñez‐Moreno

et al. 2022

IJMS

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The introduction of NGS in genetic diagnosis has increased the repertoire of variants and genes involved and the amount of genomic information produced. We built an allelic-frequency (AF) database for a heterogeneous cohort of genetic diseases to explore the aggregated genomic information and boost diagnosis in inherited retinal dystrophies (IRD). We retrospectively selected 5683 index-cases with clinical exome sequencing tests available, 1766 with IRD and the rest with diverse genetic diseases. We calculated a subcohort’s IRD-specific AF and compared it with suitable pseudocontrols. For non-solved IRD cases, we prioritized variants with a significant increment of frequencies, with eight variants that may help to explain the phenotype, and 10/11 of uncertain significance that were reclassified as probably pathogenic according to ACMG. Moreover, we developed a method to highlight genes with more frequent pathogenic variants in IRD cases than in pseudocontrols weighted by the increment of benign variants in the same comparison. We identified 18 genes for further studies that provided new insights in five cases. This resource can also help one to calculate the carrier frequency in IRD genes. A cohort-specific AF database assists with variants and genes prioritization and operates as an engine that provides a new hypothesis in non-solved cases, augmenting the diagnosis rate.

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“…Using this approach, were analyzed 131 variants, consisting of 89 VUS (variant of undetermined value) and 42 unclassified variants (unclassifiable by current methods) within the BRCT repeats, and were able to differentiate them into 78 deleterious and 53 tolerated variants (Sinha et al, 2020). Verónica Castillo-Guardiola (2022) applied an algorithm to prioritize VUS, and out of the 70 VUS, 19 were classified as variants with high-risk of having deleterious effect that needed to be further explored (Castillo-Guardiola et al, 2022). Thus, the ActiveDriverDB tool, own models or algorithms are great alternative approach for genetic variants annotation.…”

Section: Discussionmentioning

confidence: 99%

Pathogenicity Reclassification of Genetic Variants Related to Early-Onset Breast Cancer among Women of Mongoloid Origin

Gervas

Molokov

Бабышкина

et al. 2022

Asian Pac J Cancer Prev

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Background: Germline alterations in BRCA1, BRCA2, and other genes are responsible for early-onset breast cancer. However, up to 20% of molecular tests report genetic variant of unknown significance (VUS) or novel variants that have never been previously described and their clinical significance are unknown. This study aimed to reclassify variant of unknown significance (VUS) or novel variants by using the ActiveDriveDB database that annotates variants through the lens of sites of post-translational modifications (PTM). Methods: Our study included thirty-eighth young Buryat BC patients, belonging to the Mongoloid race and anthropologically to the Central Asia. Genomic DNA was extracted from the peripheral blood lymphocytes using the phenol/chloroform method. DNA library were prepared using the Hereditary Cancer SolutionTM kit (Sophia GENETICS, Switzerland) to cover 27 genes, such as ATM, APC,

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Next step in molecular genetics of hereditary breast/ovarian cancer: Multigene panel testing in clinical actionably genes and prioritization algorithms in the study of variants of uncertain significance

Cited by 8 publications

References 40 publications

Aggregated genomic data as cohort-specific allelic frequencies can boost variants and genes prioritization in non-solved cases of inherited retinal dystrophies

Aggregated genomic data as cohort-specific allelic frequencies can boost variants and genes prioritization in non-solved cases of inherited retinal dystrophies

Aggregated Genomic Data as Cohort-Specific Allelic Frequencies can Boost Variants and Genes Prioritization in Non-Solved Cases of Inherited Retinal Dystrophies

Pathogenicity Reclassification of Genetic Variants Related to Early-Onset Breast Cancer among Women of Mongoloid Origin

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