Abstract
BACKGROUND: The role of pyroptosis and lncRNAs in breast cancer remains controversial. This study aimed to explore the pyroptosis-related lncRNAs in breast cancer. METHODS: All the data used for bioinformatics analysis were downloaded from The Cancer Genome Atlas database. Limma package was used to perform difference analysis, and distinguish mRNA and lncRNA. Survival package was used to conduct prognosis analysis. LASSO algorithm, univariate cox analysis and multivariate cox analysis were used to construct the prognosis model. P value <0.05 was regarded as statistically significant. RESULTS: Based on the seven pyroptosis-related lncRNAs tightly associated with patients' prognosis, a prognostic prediction model was finally developed, which showed powerful effectiveness (Training cohort, one-year AUC = 0.82, 95% Cl = 0.69-0.95, three-year AUC = 0.77, 95% Cl = 0.68-0.85, five-year AUC = 0.74, 95% Cl = 0.66-0.82; Validation cohort, one-year AUC = 0.68, 95% Cl = 0.53-0.84, three-year AUC = 0.72, 95% Cl = 0.64-0.81, five-year AUC = 0.67, 95% Cl = 0.57-0.77). GSEA analysis demonstrated that the protein secretion, angiogenesis, TGF-β signaling and MTORC1 signaling might be involved in the high-risk patients. Moreover, immune infiltration analysis showed that the risk score was positively correlated with Tgd and Th2 cells, yet negatively correlated with CD8+ T cells, cytotoxic cells and T helper cells, which might partly explain the poor prognosis of high-risk patients. Finally, the expression level of seven model lncRNAs in the real world was validated by qRT-PCR using four cancer cell lines (MCF-7, T47D, MDA-MB-231, MDA-MB-469). CONCLUSION: In conclusion, our study identified lncRNAs that are remarkably correlated with patients' survival and might participate in the pyroptosis process, which might be underlying tumor biomarker and therapeutic targets. This study may provide direction for future research.