Identification of genes associated with survival of breast cancer patients.

BACKGROUND

We aimed to investigate the potential of microRNA expression profiles to predict survival in breast cancer.

METHODS

MicroRNA and mRNA expression data of breast cancer were downloaded from The Cancer Genome Atlas. LASSO regression was used to identify microRNAs signature predicting survival of breast cancer patients. Transfection experiment was conducted to explore the influence of microRNAs on their potential targets.

RESULTS

We identified 56 differentially expressed microRNAs in breast cancer tissues compared to adjacent normal tissues. 10 microRNAs with non-zero coefficient were selected from the 56 microRNAs using LASSO Cox regression. After predicting the targets for the 10 microRNAs, we further obtained 155 targets that were associated with overall survival of breast cancer patients. Spearman's correlation analysis found that the expression of SCUBE2, SCRN3, YTHDF3, ITFG1, ITPRIPL2, and JAK1 was an inversely correlated with their microRNAs. Transfection experiment showed that YTHDF3 was down-regulated in cells transfected with miR-106b-5p mimics compared with those transfected with negative control of mimics (fold change 4.21; P < 0.01).

CONCLUSIONS

In conclusion, we identified a 10-miRNA signature associated with prognosis of breast cancer patients. The expression of YTHDF3 was down-regulated by miR-106b-5p.