<p>Breast cancer, a prevalent malignancy worldwide, necessitates the identification of novel prognostic markers and therapeutic targets. This study delved into the significance of genes related to anoikis in breast cancer, with the aim of enhancing our understanding of its pathogenesis and treatment strategies. Initially, we identified differentially expressed anoikis genes in breast cancer tissues compared to normal tissues, revealing a complex landscape of gene expression. Through unsupervised clustering based on these genes, we uncovered three distinct subtypes that exhibited unique prognostic outcomes. Subsequently, utilizing LASSO and Cox regression analyses, we developed a risk score model that accurately predicted patient survival in both discovery and validation cohorts. Furthermore, we explored the functional implications of these genes and discovered associations with immune cell infiltration as well as drug sensitivity. Our analysis on drug sensitivity revealed potential antineoplastic agents that could be tailored for specific subtypes of breast cancer. In conclusion, this comprehensive analysis provides novel insights into the role played by genes related to anoikis in breast cancer and holds promise for improved prognostic assessment and targeted therapy development.</p>