Tumor Profiling Using an NGS Cancer Hotspot Panel in Ukrainian Breast Cancer Patients: Initial Findings of Mutation Frequencies and Clinicopathologic Characteristics.

BackgroundMolecular profiling with next-generation sequencing (NGS) can improve breast-cancer (BC) diagnostics, prognostication, and treatment selection. Despite this potential, tumor genomic testing has been insufficiently studied and implemented in Ukraine. This exploratory study aimed to identify and clinically analyze variants in tumor suppressor genes, oncogenes, as well as genes involved in epigenetic regulation and cellular signaling pathways, in tumor tissue samples from Ukrainian BC patients using NGS assessing a 50-gene targeted panel.MethodsThis was a retrospective cross-sectional study. Tumor tissue from 57 consecutively enrolled women with newly diagnosed, histologically confirmed BC was analyzed using the Ion AmpliSeq™ Cancer Hotspot Panel v2 (50 genes). Variants were filtered by stringent quality criteria and classified according to ACMG and AMP/ASCO/CAP. Group comparisons were evaluated using Fisher's exact and nonparametric tests; correlations were evaluated using Spearman's test.ResultsVariants were detected in 32 of 57 (56.1%) tumors across eight genes. The highest number of variants were detected in TP53 gene (15; 48.38%), followed by PIK3CA gene (5; 16.12%). The most recurrent single variant was PIK3CA c.3140A>G (H1047R) (11/57; 19.3%). Carriers of PIK3CA variants tended to be older and more often had ER/PR-positive, Luminal A tumors, and lower Ki-67 index. TP53 alterations tended to occur in ER-negative and triple-negative tumors, although these trends did not reach statistical significance in this cohort.ConclusionsThis study provides an initial NGS-based characterization of variants in Ukrainian BC and supports previously reported associations of PIK3CA and TP53 with clinicopathological phenotypes. Our findings should be considered exploratory and hypothesis-generating, and may support future studies on genomic profiling for patient stratification and trial enrollment in settings with limited local genomic data.