UNLABELLED

Breast cancer (BC) remains a highly heterogeneous disease, complicating diagnosis and treatment. This study investigates the prognostic significance of Anillin () and Kinase Insert Domain Receptor () genes, focusing on their mutational and expression landscapes in BC using data from The Cancer Genome Atlas (TCGA). We found that high expression is strongly associated with poor overall survival, highlighting its potential as a robust prognostic marker. In contrast, , despite its higher mutation frequency, showed a less significant correlation with survival outcomes. Machine learning (ML) models incorporating transcriptional and translational data further supported prognostic value, demonstrating superior accuracy in survival stage prediction when both genes were analyzed together. Functional enrichment analysis revealed that is primarily involved in cell cycle regulation, while is linked to angiogenesis, suggesting that combined targeting of these pathways could enhance therapeutic efficacy. These findings underscore the potential of and as complementary biomarkers in BC prognosis and highlight the need for further validation in diverse cohorts.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40203-024-00301-5.