In the rapidly evolving field of genomics, understanding the genetic basis of complex diseases like breast cancer, particularly its familial/hereditary forms, is crucial. Current methods often examine genomic variants—such as Single Nucleotide Variants (SNVs), insertions/deletions (Indels), and Copy Number Variations (CNVs)—separately, lacking an integrated approach. Here, we introduced a robust, flexible methodology for a comprehensive variants’ analysis using Whole Exome Sequencing (WES) data. Our approach uniquely combines meticulous validation with an effective variant filtering strategy. By reanalyzing two germline WES datasets from BRCA1/2 negative breast cancer patients, we demonstrated our tool’s efficiency and adaptability, uncovering both known and novel variants. This contributed new insights for potential diagnostic, preventive, and therapeutic strategies. Our method stands out for its comprehensive inclusion of key genomic variants in a unified analysis, and its practical resolution of technical challenges, offering a pioneering solution in genomic research. This tool presents a breakthrough in providing detailed insights into the genetic alterations in genomes, with significant implications for understanding and managing hereditary breast cancer.

A method to comprehensively identify germline SNVs, INDELs and CNVs from whole exome sequencing data of BRCA1/2 negative breast cancer patients

Bianchi, A.;Zelli, V.
;
D'Angelo, A.;Di Matteo, A.;Scoccia, G.;Zazzeroni, F.;Alesse, E.;Di Marco, A.;Tessitore, A.
2024-01-01

Abstract

In the rapidly evolving field of genomics, understanding the genetic basis of complex diseases like breast cancer, particularly its familial/hereditary forms, is crucial. Current methods often examine genomic variants—such as Single Nucleotide Variants (SNVs), insertions/deletions (Indels), and Copy Number Variations (CNVs)—separately, lacking an integrated approach. Here, we introduced a robust, flexible methodology for a comprehensive variants’ analysis using Whole Exome Sequencing (WES) data. Our approach uniquely combines meticulous validation with an effective variant filtering strategy. By reanalyzing two germline WES datasets from BRCA1/2 negative breast cancer patients, we demonstrated our tool’s efficiency and adaptability, uncovering both known and novel variants. This contributed new insights for potential diagnostic, preventive, and therapeutic strategies. Our method stands out for its comprehensive inclusion of key genomic variants in a unified analysis, and its practical resolution of technical challenges, offering a pioneering solution in genomic research. This tool presents a breakthrough in providing detailed insights into the genetic alterations in genomes, with significant implications for understanding and managing hereditary breast cancer.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/231901
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