Integrative Analysis of Genetic Variation in Breast Cancer: A Retrospective Study of the Albanian Cohort

Breast cancer is a disease characterized by genomic alterations that influence prognosis and therapeutic response. Immunohistochemical biomarkers, including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki-67, are routinely used for tumor classification and risk stratification. In a recent cohort of Albanian women, significant associations were observed between these biomarkers and clinicopathological parameters, with hormone receptor-positive tumors representing the predominant subtype and Ki-67 correlating with tumor stage and nodal involvement. Here, we investigate copy number variations (CNVs) and loss of heterozygosity (LOH) within the BRCA1 and BRCA2 genes in a selected subgroup with a family history of the disease and integrate these findings with the evaluated prognostic biomarkers. From a retrospective cohort of 252 breast cancer patients, formalin-fixed, paraffin-embedded (FFPE) breast cancer tissue blocks from 17 patients with a documented family history were selected. DNA was extracted using the QIAamp™ DNA FFPE Tissue Kit, and genome-wide CNV profiling was performed using an Affymetrix platform. CNV and LOH, including copy-neutral LOH, were assessed and correlated with molecular subtypes defined by ER, PR, HER2, and Ki-67 expression. Copy number alterations affecting BRCA1 and BRCA2 were identified in 12/17 cases. BRCA1 deletions were observed in 29.4% of tumors, while LOH at the BRCA1 locus was detected in 47.1% of cases. BRCA2 deletions were identified in 17.6% and LOH in 35.3% of samples. BRCA1 alterations were predominantly associated with triple-negative breast cancer, where all cases showed evidence of genomic loss or allelic imbalance. The observed alterations in BRCA1 and BRCA2 highlight the importance of integrating genomic data with immunohistochemical biomarkers. These findings provide preliminary evidence of BRCA-associated genomic instability patterns in breast cancer patients in Albania and support the potential utility of CNV analysis to refine risk stratification and guide targeted therapeutic strategies.