Andrey Kechin

BRACNAC: A BRCA1 and BRCA2 Copy Number Alteration Caller from Next-Generation Sequencing Data

Detecting copy number variations (CNVs) and alterations (CNAs) in the BRCA1 and BRCA2 genes is essential for testing patients for targeted therapy applicability. However, the available bioinformatics tools were initially designed for identifying CNVs/CNAs in whole-genome or -exome (WES) NGS data or targeted NGS data without adaptation to the BRCA1/2 genes. Most of these tools were tested on sample cohorts of limited size, with their use restricted to specific library preparation kits or sequencing platforms. We developed BRACNAC, a new tool for detecting CNVs and CNAs in the BRCA1 and BRCA2 genes in NGS data of different origin. The underlying mechanism of this tool involves various coverage normalization steps complemented by CNV probability evaluation. We estimated the sensitivity and specificity of our tool to be 100% and 94%, respectively, with an area under the curve (AUC) of 94%. The estimation was performed using the NGS data obtained from 213 ovarian and prostate cancer samples tested with in-house and commercially available library preparation kits and additionally using multiplex ligation-dependent probe amplification (MLPA) (12 CNV-positive samples). Using freely available WES and targeted NGS data from other research groups, we demonstrated that BRACNAC could also be used for these two types of data, with an AUC of up to 99.9%. In addition, we determined the limitations of the tool in terms of the minimum number of samples per NGS run (≥20 samples) and the minimum expected percentage of CNV-negative samples (≥80%). We expect that our findings will improve the efficacy of BRCA1/2 diagnostics. BRACNAC is freely available at the GitHub server.

A spectrum of BRCA1 and BRCA2 germline deleterious variants in ovarian cancer in Russia

Pathogenic variants (PVs) in BRCA1 and BRCA2 genes are essential biomarkers of an increased breast and ovarian cancer risk and tumor sensitivity to poly ADP ribose polymerase inhibitors. In Russia, eight PVs were thought to be the most common, among which BRCA1 c.5266dup is the most frequently identified one. We show the distribution of BRCA1/2 PVs identified with quantitative PCR and targeted next-generation sequencing in 1399 ovarian cancer patients recruited into the study from 72 Russian regions in 2015-2021. The most abundant PVs were c.5266dup (41.0%), c.4035del (7.0%), c.1961del (6.3%), c.181 T > G (5.2%), c.3756_3759del (1.8%), c.3700_3704del (1.5%), and c.68_69del (1.5%), all found in BRCA1 and known to be recurrent in Russia. Several other frequent PVs were identified: c.5152 + 1G > T (1.2%), c.1687C > T (1.0%), c.4689C > G (0.9%), c.1510del (0.6%), c.2285_2286del (0.6%) in the BRCA1 gene; and c.5286 T > G (1.2%), c.2808_2811del (0.8%), c.3847_3848del (0.8%), c.658_659del (0.7%), c.7879A > T (0.6%), in the BRCA2 gene. For the most common PV in the BRCA2 gene c.5286 T > G, we suggested that it arose about 700 years ago and is a new founder mutation. This study extends our knowledge about the BRCA1 and BRCA2 pathogenic variants variability.