Tumor Microenvironment Characterization in Breast Cancer Identifies Prognostic Pathway Signatures.

ABSTRACT: Breast cancer is one of the most common female malignancies worldwide. Due to its early metastases formation and a high degree of malignancy, the 10 year-survival rate of metastatic breast cancer does not exceed 30%. Thus, more precise biomarkers are urgently needed. In our study, we first estimated the tumor microenvironment (TME) infiltration using the xCell algorithm. Based on TME infiltration, the three main TME clusters were identified using consensus clustering. Our results showed that the three main TME clusters cause significant differences in survival rates and TME infiltration patterns (log-rank test, p = 0.006). Then, multiple machine learning algorithms were used to develop a nine-pathway-based TME-related risk model to predict the prognosis of breast cancer (BRCA) patie

SUBMITTER: Li J 

PROVIDER: S-EPMC9690299 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature