The hub ten gene-based risk score system using RNA mA methylation regulator features and tumor immune microenvironment in breast cancer.

BACKGROUND

RNA N-methyladenosine (mA) modification is primarily regulated by mA regulators, which play significant epigenetic regulatory roles in tumorigenesis, tumor development, and tumor immune microenvironment. However, the correlation between mA regulators and immune cell infiltration in breast cancer remains unclear.

METHODS

In this study, mA modification patterns were evaluated based on 31 mA modification regulators. mA clusters were determined by consensus clustering. Immune landscape and immune cell infiltration subgroups were characterized by mA clusters. Key module and hub genes related to mA regulators and immune infiltration cells were identified by WGCNA. LASSO algorithm was applied to select prognostic signatures. Multivariate Cox regression analysis was applied to assess the prognostic value of gene signatures.

RESULTS

Two distinct mA clusters were determined based on the expression of 31 mA modification regulators and characterized by two tumor immune microenvironment (TIME) immune cell infiltration subgroups. Further, a total of 1971 differentially expressed genes between breast cancer patients and healthy controls were screened, nine modules associated with clinical characteristics of breast cancer patients were identified. Later, one key module and 13 hub genes correlated with mA regulators and immune infiltration cells were identified. LASSO Cox regression analysis selected and constructed a ten-gene prognostic model to build a risk score system for individual breast cancer patient prognosis. The performance of the ten-gene-based risk score system was further validated in an independent dataset with an AUC of 0.659.

CONCLUSIONS

This study revealed that mA modification regulators played a significant role in the TIME regulation of breast cancer. The hub ten gene-based risk score system is valuable in predicting the prognosis of breast cancer patients, which may provide potential significance for breast cancer diagnosis, prognosis, and immunotherapy in the future.