Prognostic factors of early breast cancer

Four-lncRNA immune prognostic signature for triple-negative breast cancer Running title: Immune lncRNAs predict prognosis of TNBC

OBJECTIVE

We aimed to explore key immune-related long non-coding RNAs (lncRNAs) and their effect in predicting of prognosis of triple-negative breast cancer (TNBC).

METHODS

Four datasets of TNBC were downloaded from TCGA and GEO databases. ImmPort database was utilized to acquire immune-related mRNAs. Single sample gene set enrichment analysis (ssGSEA) and correlation analysis were utilized to screen immune-related lncRNAs. Univariate and multivariate Cox regression analyses were utilized to screen independent prognostic lncRNAs to establish prognostic risk model, and the model was evaluated by survival analysis and nomogram. Differential functions and immune cells infiltration in high and low risk group were analyzed by Gene set variation analysis and ssGSEA. Finally, competitive endogenous RNAs was constructed.

RESULTS

We revealed 62 immune-related lncRNAs, of which four lncRNAs (RP11-890B15.3, RP11-1024P17.1, MFI2-AS1 and RP11-180N14.1) had independent prognostic value. These four lncRNAs-based prognostic risk model could stratify the TNBC patients into high and low risk groups, and patients with high risk displayed unfavorable outcomes. Nomogram indicated that the prognostic model could indicate TNBC patients survival very well. We further found that high risk group showed significantly enriched immune response to tumor cell, humoral immune response and high infiltrating abundance of regulatory T cell, Type 2 T helper cell, eosinophil, etc. LncRNAs RP11-180N14.1, RP11-1024P17.1 and RP11-890B15.3 regulated more mRNAs by targeting various miRNAs. While MFI2-AS1 regulated three mRNAs by sponging miR-3150a-3p.

CONCLUSION

These four lncRNAs were prognostic biomarkers and could be possible therapeutic targets in TNBC.