A six-mRNA signature-based model for the prognosis prediction of breast cancer

Abstract

BackgroundDue to the lack of predictors, high mortality and poor prognosis have always been a serious threat to the breast cancer (BC) patients. Accumulating studies have shown that molecular markers which affect the tumor microenvironment (TME) play an important role in the development of cancer. Here, we aim to use machine learning to identify a new prognostic gene signature and independent prognostic factors related to BC survival through comprehensive bioinformatics analysis.Results This 6-mRNA signature-based model is not only an important indicator to predict the prognosis and survival of BC, but also a potential indicator to monitor the clinical therapeutic effect with certain clinical significance.Conclusions A new 6-gene prognostic signature was discovered and it is a promising independent predictor. The 6 feature genes can function as important biomarkers for BC clinical treatment. At the same time, our study also provides a new insight to explore the molecular mechanism of TME and immune cells that influence BC progress.