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398eP The role of artificial intelligence (AI) in optimizing the breast cancer care pathway

2026·0 Zitationen·ESMO OpenOpen Access
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10

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2026

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Abstract

is to assess the frequency and spectrum of germline mutations in the BRCA1 and BRCA2 genes in a cohort of patients with TNBC in the Republic of Belarus.Methods: A single-center study included 114 patients with pathologically confirmed TNBC (mean age 47 years, range 27-70 years).Genotyping of the most common pathogenic variants of the BRCA1 and BRCA2 genes in the population was performed using PCR.Stage, Ki-67 index, differentiation degree and family history were analyzed as well.Results: Pathogenic germline mutations of the BRCA1 gene were detected in 38 patients, representing 33.3% of the entire cohort.Mutations in the BRCA2 gene were not detected.The predominant mutation was 5382insC (exon 20), detected in 68.4% of carriers.Other variants were less common: 4153delA (exon 11) -16.0%, 300T>G (exon 5) -13.0%, 3875del4 (exon 11) -2.6%.The average age of patients with BRCA1-associated TNBC was 47.1 years.Mutation carriers were more often diagnosed with stage IIB (34.2%) and stage III (25.0%) disease.A positive family history of breast or ovarian cancer was observed in 52.6% (20 of 38) of patients with the mutation.In the overall cohort, tumors were characterized by a high proliferative index (mean Ki-67 60.5%) and poor differentiation (G3 in 54.2% of cases). Conclusions:The study revealed an exceptionally high prevalence (33.3%) of germline BRCA1 mutations in Belarusian patients with TNBC.The prevalence of a specific variant, 5382insC (68.4%), determines the algorithm for targeted genetic testing.The obtained data substantiate the need for routine genetic screening (for key mutations, including 185delAG, 4153delA, 5382insC, 300T>G, 6174delT, and 3875delGTCT) for all patients with TNBC, regardless of age and stage.This is a prerequisite for the prescription of personalized targeted therapy and the organization of preventive measures for family members.

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Radiomics and Machine Learning in Medical ImagingArtificial Intelligence in Healthcare and EducationBiomarkers in Disease Mechanisms
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