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Updated: Jul 17, 2025
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Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
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Copy Number Variations (CNVs) Account for 10.8% of Pathogenic Variants in Patients Referred for Hereditary Cancer
Konstantinos Agiannitopoulos1, Georgia Pepe2, Georgios N Tsaousis2
1Genekor Medical S.A, Athens, Greece; kagiannitopoulos@genekor.com.
Cancer Genomics & Proteomics
|August 29, 2023
Summary
Germline copy number variations (CNVs) are significant genetic contributors to inherited cancers. Analyzing CNVs using next-generation sequencing (NGS) multigene panels is crucial for improving diagnostic yield in hereditary cancer testing.
Area of Science:
- Genetics
- Oncology
- Bioinformatics
Background:
- Germline copy number variation (CNV) is a key genetic factor in inherited cancer predisposition.
- Next-generation sequencing (NGS) technologies are increasingly used for multi-gene panel analysis in clinical settings.
Purpose of the Study:
- To evaluate the performance of computational tools for detecting CNVs from NGS data.
- To assess the contribution of CNVs to pathogenic variants in cancer susceptibility testing.
Main Methods:
- Screened 2,163 patients for cancer susceptibility using targeted NGS on a 52-gene panel.
- Evaluated the SeqPilot CNV module, panelcn.MOPS, and digitalMLPA for CNV detection from NGS data.
Main Results:
- Pathogenic/likely pathogenic variants were found in 21.5% of patients.
- CNVs accounted for 10.8% of all pathogenic variants, with higher rates in colorectal (28.6%) and breast/ovarian (10.2%/6.8%) cancer patients.
Conclusions:
- In silico CNV detection from NGS data is a viable and cost-effective diagnostic method.
- CNVs represent a significant proportion of pathogenic variants, making their evaluation essential for enhancing hereditary cancer analysis yields.
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