Frequency of germline pathogenic variants in breast cancer predisposition genes among young Turkish breast cancer patients.

PURPOSE: One of the most important risk factors for hereditary breast and ovarian cancer is young age. We aim to report the frequency of pathogenic/likely pathogenic variants in breast cancer predisposing genes in young (≤ 40 years old) breast cancer patients who undergone 26-gene inherited cancer panel at our Breast Health Center. METHODS: Medical records of breast cancer patients who were referred to genetic counseling based on NCCN criteria and were ≤ 40 years of age are reviewed. The frequency of germline pathogenic/likely pathogenic variants who undergone 26-gene inherited cancer panel was analyzed. RESULTS: Among 414 breast cancer patients who were ≤ 40 years of age, 308 undergone 26-gene inherited cancer panel and 108 had next generation sequencing (NGS)-based BRCA 1 and 2 genetic testing. Median age was 35 (22-40), Family history in first degree relatives was present in 14% of patients. Forty-five percent of patients met one of the NCCN criteria for genetic testing, 41% of them met two criteria, and 14% of patients fulfilled ≥ 3 criteria. Seventy pathogenic/likely pathogenic variants (PV/LPV) were found in 65 (21%) patients. PV/LPs in BRCA genes and non-BRCA genes represented 53% and 44% of all PV/LPVs, accounting for 12% and 10% of patients in the study cohort respectively. Two PVs were present in 5 patients and eleven PVs were novel. The most common PVs were in BRCA 1 (n:18), BRCA 2 (n:19), ATM (n:7), CHEK2 (n:7) and TP53 (n:5) genes. Thirty-one percent of the patients with triple-negative tumors and 25% of the patients with hormone receptor-positive tumors had PV/LPVs with panel testing. Family history in first degree relatives (p = 0.029), the number of met NCCN criteria (p = 0.036) and axillary nodal involvement (p = 0.000) were more common in patients with PVs. When combined with patient group (n:106) who had only BRCA1 and 2 gene testing, 16% of Turkish breast cancer patients ≤ 40 years of age had PVs in BRCA genes. CONCLUSION: One fifth of Turkish breast cancer patients ≤ 40 years of age had at least one PV/LPV in breast cancer predisposing genes with 26-gene inherited cancer panel. The frequency of PV/LPVs was higher in triple-negative young-onset patients compared to hormone receptor and Her-2 positive subtypes. Our findings regarding to frequency PV/LPVs in BRCA 1/2 and non-BRCA genes in young-onset breast cancer patients are in line with the literature.

A Multicenter Study of Genotype Variation/Demographic Patterns in 2475 Individuals Including 1444 Cases With Breast Cancer in Turkey.

Objective: Breast cancer (BC) is the most common cancer type in women and may be inherited, mostly in an autosomal dominant pattern. The clinical diagnosis of BC relies on the published diagnostic criteria, and analysis of two genes, BRCA1 and BRCA2, which are strongly associated with BC, are included in these criteria. The aim of this study was to compare BC index cases with non-BC individuals in terms of genotype and diagnostic features to investigate the genotype/demographic information association. Materials and Methods: Mutational analyses for the BRCA1/BRCA2 genes was performed in 2475 individuals between 2013-2022 from collaborative centers across Turkey, of whom 1444 with BC were designated as index cases. Results: Overall, mutations were identified in 17% (421/2475), while the percentage of mutation carriers in cases of BC was similar, 16.6% (239/1444). BRCA1/BRCA2 gene mutations were detected in 17.8% (131/737) of familial cases and 12% (78/549) of sporadic cases. Mutations in BRCA1 were found in 4.9%, whereas 12% were in BRCA2 (p<0.05). Meta-analyses were performed to compare these results with other studies of Mediterranean-region populations. Conclusion: Patients with BRCA2 mutations were significantly more common than those with BRCA1 mutations. In sporadic cases, there was a lower proportion with BRCA1/BRCA2 variants, as expected, and these results were consistent with the data of Mediterranean-region populations. However, the present study, because of the large sample size, revealed more robust findings than previous studies. These findings may be helpful in facilitating the clinical management of BC for both familial and non-familial cases.

BRCA Variations Risk Assessment in Breast Cancers Using Different Artificial Intelligence Models.

Artificial intelligence provides modelling on machines by simulating the human brain using learning and decision-making abilities. Early diagnosis is highly effective in reducing mortality in cancer. This study aimed to combine cancer-associated risk factors including genetic variations and design an artificial intelligence system for risk assessment. Data from a total of 268 breast cancer patients have been analysed for 16 different risk factors including genetic variant classifications. In total, 61 BRCA1, 128 BRCA2 and 11 both BRCA1 and BRCA2 genes associated breast cancer patients' data were used to train the system using Mamdani's Fuzzy Inference Method and Feed-Forward Neural Network Method as the model softwares on MATLAB. Sixteen different tests were performed on twelve different subjects who had not been introduced to the system before. The rates for neural network were 99.9% for training success, 99.6% for validation success and 99.7% for test success. Despite neural network's overall success was slightly higher than fuzzy logic accuracy, the results from developed systems were similar (99.9% and 95.5%, respectively). The developed models make predictions from a wider perspective using more risk factors including genetic variation data compared with similar studies in the literature. Overall, this artificial intelligence models present promising results for BRCA variations' risk assessment in breast cancers as well as a unique tool for personalized medicine software.