Abstract：ObjectiveAnoikis is a distinct form of apoptosis that primarily takes place when cells become detached from the extracellular matrix, resulting in the loss of anchoring. It plays a crucial role in preserving the homeostasis of the in vivo environment. This study is aimed at developing a gene set and prognostic model associated with anoikis in triple-negative breast cancer (TNBC), which could also be utilized to predict effective therapeutic interventions for patients.MethodsUnivariate and multivariate Cox analyses were conducted on TNBC patients within the TCGA-BRCA dataset to identify the anoikis-related gene signature (ARGS). The Gene Expression Omnibus (GEO) dataset was employed for independent validation. Subsequently, a nomogram model was constructed by integrating ARGS with clinicopathological parameters. Multiple statistical methods were employed to assess the predictive capability of the model. The sensitivity to therapeutic agents was analyzed in stratified TNBC patients based on ARGS. To investigate the predicted drug susceptibility, CCK-8 cell viability assay and flow cytometry were performed.ResultsWe constructed a seven-gene ARGS and calculated the risk score, stratifying TNBC patients into high-risk and low-risk groups. Significantly worse overall survival (OS) was observed in the high-risk group compared with the low-risk group. Subsequently, we generated a nomogram model exhibiting excellent performance and stratification of patient survival, predicting heightened sensitivity to tyrosine kinase inhibitors (TKIs) in high-risk TNBC patients. In addition, we found that the higher the risk score of the TNBC cell lines, the greater the sensitivity to TKIs.ConclusionsAn ARGS was established in TNBC to predict patient survival and drug sensitivity. Additionally, a nomogram model was constructed, incorporating clinicopathological parameters to further enhance the prediction ability of patient survival.
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2023,Vol. 20
