Spatial multi-omics analysis of tumor-stroma boundary cell features for predicting breast cancer progression and therapy response.

ABSTRACT:

Background

The tumor boundary of breast cancer represents a highly heterogeneous region. In this area, the interactions between malignant and non-malignant cells influence tumor progression, immune evasion, and drug resistance. However, the spatial transcriptional profile of the tumor boundary and its role in the prognosis and treatment response of breast cancer remain unclear.

Method

Utilizing the Cottrazm algorithm, we reconstructed the intricate boundaries and identified differentially expressed genes (DEGs) associated with these regions. Cell-cell co-positioning analysis was conducted using SpaCET, which revealed key interactions between tumor-associated macrophage (TAMs) and cancer-associated fibroblasts (CAFs). Additionally, Lasso regression analysis was employed to de

SUBMITTER: Wu Y 

PROVIDER: S-EPMC11979139 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature