Characterization of tumor microenvironment infiltration and therapeutic responses of cell cycle-related genes' signature in breast cancer.

BACKGROUND

It is unknown how the cell cycle plays a role in breast cancer (BC). This study aimed to establish a clinically applicable predictive model to predict the therapeutic responses and overall survival in BC patients.

MATERIALS AND METHODS

Cell cycle-related genes (CCGs) were identified within the Cancer Genome Atlas cohort (n is equal to 1001) and the Gene Expression Omnibus cohort (n is equal to 3265). An analysis of univariate and multivariate Cox was then conducted to develop a nomogram based on CCGs. After validating the nomogram, risk cohort stratification was established and the predictive value was examined. Finally, immune cell infiltration and therapeutic responses were analysed.

RESULTS

Based on 15 CCGs, 4 prognostic predictors were identified and entered into the nomogram. According to the curves of calibration, the estimated and observed value of the nomogram is in optimal agreement. Subsequently, stratification into two risk cohorts showed that the predictive value, immune cell infiltration and overall survival were better among patients with low risk. Immune checkpoint expression in patients with BC at higher risk was downregulated. Furthermore, the results of the study revealed that doxorubicin, paclitaxel, docetaxel, cisplatin and vinorelbine all had higher IC50 values in patients with high-risk BC.

CONCLUSION

The nomogram based on CCG could assess tumour immune micro-environment regulation and therapeutic responses of immunotherapy in BC. Moreover, it may provide novel information on the control of immune micro-environment infiltration in BC and aid in the development of targeted immunotherapy.