Development and Verification of a Prognostic Stemness-Related Gene Signature in Triple-Negative Breast Cancer

Background. It is well known that cancer stem cells can induce metastasis, which causes the majority of cancer-related death, especially in triple-negative breast (TNBC). TNBC features a high metastatic rate and low metastasis-free survival regarded as most malignant subtype cancer. The purpose this study to explore prognostic biomarkers predict metastasis Methods. human cancerSUM149PT were used for study. cell spheres (sum149-Stem) paired adherent (sum149-Tumor) collected extract total RNAs. RNA-seq was analysis mRNA expression cells. Two different gene omnibus datasets (https://www.ncbi.nlm.nih.gov/gds), GSE58812 GSE33926, mechanism genes between Seven showed function all datasets. STITCH database (https://www.stitchdata.com/) possible metastasis-inhibiting drugs target seven genes. Each compared by Pearson analysis. receiver operating characteristic curve (ROC) Kaplan–Meier performed assess ability seven-gene modeling two GEO Results. A subset 7 stemness-related (SRGs) containing UCN, ST3GAL5, FDPS, HK2, MALL, LMTK3, CRHR2 identified three independent cohorts. Univariate Cox ST3GAL5 plays an antitumor role other 6 promote progression TNBC. 7-SRGs model constructed with dataset. Most significant patients risk levels. Additionally, predictive value another dataset patients. ROC curves indicated has metastasis. Conclusions. Expression signature at diagnosis