Necroptosis-related lncRNA to establish novel prognostic signature and predict the immunotherapy response in breast cancer.

BACKGROUND

Necroptosis is a type of programmed cell death, and recent researches have showed that lncRNAs could regulate the process of necroptosis in multiple cancers. We tried to screen necroptosis-related lncRNAs and investigate the immune landscape in breast cancer (BC).

METHODS

The samples of breast normal and cancer tissue were acquired from TCGA and GTEx databases. A risk prognostic model was constructed based on the identified necroptosis-related lncRNAs by Cox regression and least absolute shrinkage and selection operator (LASSO) method. Moreover, the forecast performance of this model was verified and accredited by synthetic approach. Subsequently, an accurate nomogram was constructed to predict the prognosis of BC patients. The biological differences were investigated through GO, GSEA, and immune analysis. The immunotherapy response was estimated through tumor mutation burden (TMB) and tumor immune dysfunction and exclusion (TIDE) score.

RESULTS

A total of 251 necroptosis-related lncRNAs were identified by differential coexpression analysis, and SH3BP5-AS1, AC012073.1, AC120114.1, LINC00377, AL133467.1, AC036108.3, and AC020663.2 were involved in the risk model, which had an excellent concordance with the prediction. The pathway analyses showed that immune-related pathways were relevant to the necroptosis-related lncRNAs risk model. And the risk score was significantly correlated with immune cell infiltration, as well as the ESTIMATE score. Most notably, the patients of higher risk score were characterized with increased TMB and decreased TIDE score, indicating that these patients showed better immune checkpoint blockade response.

CONCLUSION

These findings were conducive to understand the function of necroptosis-related lncRNAs in BC and provide a potential promising therapeutic strategy for BC.