Landscape of prognosis and immunotherapy responsiveness under tumor glycosylation-related lncRNA patterns in breast cancer

Aberrant glycosylation, a post-translational modification of proteins, is regarded to engage in tumorigenesis and malignant progression of breast cancer (BC). The altered expression of glycosyltransferases causes abnormal glycan biosynthesis changes, which can serve as diagnostic hallmarks in BC. This study attempts to establish a predictive signature based on glycosyltransferase-related lncRNAs (GT-lncRNAs) in BC prognosis and response to immune checkpoint inhibitors (ICIs) treatment. We firstly screened out characterized glycosyltransferase-related genes (GTGs) through NMF and WGCNA analysis and identified GT-lncRNAs through co-expression analysis. By using the coefficients of 8 GT-lncRNAs, a risk score was calculated and its median value divided BC patients into high- and low-risk groups. The analyses unraveled that patients in the high-risk group had shorter survival and the risk score was an independent predictor of BC prognosis. Besides, the predictive efficacy of our risk score was higher than other published models. Moreover, ESTIMATE analysis, immunophenoscore (IPS), and SubMAP analysis showed that the risk score could stratify patients with distinct immune infiltration, and patients in the high-risk group might benefit more from ICIs treatment. Finally, the vitro assay showed that MIR4435-2HG might promote the proliferation and migration of BC cells, facilitate the polarization of M1 into M2 macrophages, enhance the migration of macrophages and increase the PD-1/PD-L1/CTLA4 expression. Collectively, our well-constructed prognostic signature with GT-lncRNAs had the ability to identify two subtypes with different survival state and responses to immune therapy, which will provide reliable tools for predicting BC outcomes and making rational follow-up strategies.

Automated summary

This study establishes a predictive signature based on glycosyltransferase-related lncRNAs (GT-lncRNAs) in breast cancer prognosis and response to immune checkpoint inhibitors (ICIs) treatment. The risk score calculated from the coefficients of 8 GT-lncRNAs can divide breast cancer patients into high- and low-risk groups, with the high-risk group showing shorter survival and the risk score being an independent predictor of breast cancer prognosis. The risk score can also stratify patients with distinct immune infiltration and patients in the high-risk group might benefit more from ICIs treatment. The well-constructed prognostic signature with GT-lncRNAs provides reliable tools for predicting breast cancer outcomes and making rational follow-up strategies.