Background: Chromatin regulators (CRs) are indispensable upstream regulatory factors of epigenetics and play an important role in cancer progression. Herein, we explored the relationship between CRs and breast cancer (BC) through bioinformatics to improve BC prognosis and treatment.
Methods: The RNA sequencing (RNA-seq) profiles and clinical data were retrieved from the Gene Expression Omnibus (GEO) database. Univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression were used to build a prognostic model. Patients were divided into high and low-risk groups according to the risk score. Then, a nomogram was constructed based on the selected clinical features and risk score. The differences in immune cell infiltration and checkpoints were estimated for the high and low-risk groups.
Results: We established and validated a prognostic model of BC patients based on 4 CRs-related genes (MORF4L1, NCOA4, TTK and JMJD4). The high-risk group presented poor prognosis. The immune-correlation analysis also showed that the high-risk group might response to immunotherapy.
Conclusion: We successfully established a reliable 4 CRs-related prognostic model and provided novel insights for evaluating immune infiltration and guiding the treatment of BC patients.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.