Development of a single-cell derived MDSCs signature score for prognostic risk stratification and therapeutic decision guidance in breast cancer.

ABSTRACT:

Background

Myeloid-derived suppressor cells (MDSCs) function as critical immunosuppressive constituents within the breast cancer tumor microenvironment (TME). However, their molecular variability and clinical translation potential remain inadequately characterized.

Methods

By combining single-cell RNA sequencing (scRNA-seq) with bulk multi-omics datasets, we screened and confirmed MDSCs signature genes specific to breast cancer. A prognostic risk scoring model was constructed using machine learning approaches and tested across multiple independent patient cohorts. The model's predictive capacity for chemotherapy sensitivity, immunotherapy responsiveness, and TME features was systematically assessed.

Results

After integrating the single-cell datasets GSE161529 and GSE1

SUBMITTER: Yin J 

PROVIDER: S-EPMC12664814 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature