A lncRNA prognostic signature associated with immune infiltration and tumour mutation burden in breast cancer

• DOI: 10.1111/jcmm.15762
• Publication Date: 2020-09-24T01:19:43Z
• Authors: Zijian Liu; Mi Mi; Xiaoqian Li; Xin Zheng; Gang Wu; Liling Zhang
• Keywords: Infiltration (HVAC)

Current studies have shown that long non-coding RNAs (lncRNAs) may serve as prognostic biomarkers in multiple cancers. Therefore, we postulated expression patterns of lncRNAs combined into a single signature could improve clinicopathological risk stratification and prediction overall survival rate for breast cancer patients. Two algorithms, Least Absolute Shrinkage Selector Operation (LASSO) Support Vector Machine-Recursive Feature Elimination (SVM-RFE), were used to select candidate lncRNAs. Univariate multivariate Cox regression analyses employed construct seven-lncRNA cancer. Stratified analysis revealed the was significantly associated with factors. For clinical use, developed nomogram model predict odds death Single-sample gene set enrichment (ssGSEA), CIBERSORT algorithm ESTIMATE method assess relative immune cell infiltrations each sample. Differentially infiltration cells diverse tumour mutation burden (TMB) scores might give rise efficacy lncRNA predicting Correlation implied LINC01215 immune-related signalling pathways. A is reliable tool prognosis