Breast cancer (BC) is one of the most common malignancies. There is a need for novel approaches to screening for genetic mutations in patients with BC that will help to reduce high mortality rates caused by this disease and improve treatment outcomes. In this study we employed next generation sequencing to screen a few key genes associated with the risk of breast cancer for mutations. We also evaluated their pathogenicity using the previously proposed bioinformatics-based algorithm and analyzed the associations between some of the detected mutations and the clinical manifestations of the disease. Our study recruited 16 female patients with BC (mean age was 50.7 ± 11.3 years). A total of 58 mutations were detected in the oncogenes BRCA1, BRCA2, ATM, CDH1, CHEK2 and TP53. Bioinformatic analysis of the sequencing data revealed 14 mutations that affect the sequence of the encoded proteins. Most deleterious mutations were harbored by the genes BRCA1/2, ATM and TP53.