Case report: Deciphering the clinical significance of a novel partial BRCA1 exon 10 duplication in a patient with triple-negative breast cancer - Faversani, Alice; Manuelli, Debora; Barteselli, Davide; Melloni, Giulia; Santaniello, Carlo; Corsaro, Luigi; Sacco, Davide; Clerici, Davide; Gargiulo, Laura; Ferrara, Fulvio; Costantino, Lucy (Frontiers in Oncology, 2025)
Pathogenic/likely pathogenic germline variants in the BRCA1 and BRCA2 genes are associated with an increased risk of developing cancer, particularly breast and/or ovarian tumors. The identification and correct classification of these variants is crucial to find individuals with an increased risk of cancer and to support physicians in their clinical and therapeutic decisions. In addition, the status of BRCA1 and BRCA2 variants is important for appropriate management of patients’ family members. Here, we describe the case of a woman who developed triple-negative breast cancer at the age of 49 years. NGS analysis of BRCA1 and BRCA2 genes revealed the presence of a new partial BRCA1 exon 10 duplication of 2.012 bp. The identified duplication comprises 395 nucleotides from the final portion of intron 9 and 1617 nucleotides from the beginning of exon 10. Using specific primers, we were able to identify the breakpoint at the DNA level and characterize the alteration as a tandem duplication leading to the formation of a premature stop codon after 10 residues. RNA analysis allowed to confirm the production of an altered mRNA showing the duplicated sequence. In this way, we were able to assign a clinical significance to the new alteration and classify it as a pathogenic variant. Although new ClinGen ENIGMA guidelines have been produced to provide tools for the accurate interpretation of variants in the BRCA1 and BRCA2 genes, defining the clinical significance of copy number variants, particularly duplications, remains a challenging goal that requires complex approaches to accurately determine the role of such variants. Other investigations, such as the detection of breakpoints by RNA analysis, are often essential to classify the identified alteration. Our study suggests that RNA transcript analysis is an ideal methodology to support the accurate classification of variants and clarify their effects.