Assessing the prognostic value of stemness-related genes in breast cancer patients

Breast cancer (BC) is currently one of the deadliest tumors worldwide. Cancer stem cells (CSCs) are a small group of tumor cells with self-renewal and differentiation abilities and high treatment resistance. One of the reasons for treatment failures is the inability to completely eliminate tumor stem cells. By using the edgeR package, we identified stemness-related differentially expressed genes in GSE69280. Via Lasso-penalized Cox regression analysis and univariate Cox regression analysis, survival genes were screened out to construct a prognostic model. Via nomograms and ROC curves, we verified the accuracy of the prognostic model. We selected 4 genes (PSMB9, CXCL13, NPR3, and CDKN2C) to establish a prognostic model from TCGA data and a validation model from GSE24450 data. We found that the low-risk score group had better OS than the high-risk score group, whether using TCGA or GSE24450 data. A prognostic model including four stemness-related genes was constructed in our study to determine targets of breast cancer stem cells (BCSCs) and improve the treatment effect.