Identifying prognostic markers in spatially heterogeneous breast cancer microenvironment

Area of Science:

• Oncology
• Immunology
• Genomics

Background:

• The tumor microenvironment significantly influences breast cancer progression and treatment response.
• Understanding spatial heterogeneity is crucial for identifying new therapeutic targets and biomarkers.

Purpose of the Study:

• To investigate the spatial heterogeneity of the breast cancer microenvironment using Digital Spatial Profiling (DSP).
• To identify novel diagnostic and prognostic markers within different cellular compartments of breast tumors.

Main Methods:

• Analysis of 107 regions of interest from 65 untreated breast cancer tissue samples using GeoMx DSP technology.
• Evaluation of prognostic markers in tumor and immune cell-enriched regions.
• Univariate Cox analysis to identify prognosis-related metabolic genes.
• Immunostaining validation of key identified markers (EMILIN2, SURF4, LYPLA1).

Main Results:

• Significant spatial heterogeneity in marker gene expression was observed across tumor, immune, and normal epithelial areas.
• Tumor cell-enriched regions showed distinct immune cell profiles compared to immune cell-enriched regions (e.g., higher T follicular helper cells, lower regulatory T cells).
• Five prognosis-related metabolic genes were identified through Cox analysis.
• Spatial variations in HLA gene families, immune checkpoints, and metabolic genes were characterized.

Conclusions:

• Spatial heterogeneity is a key feature of the breast cancer microenvironment.
• DSP technology provides valuable insights into tumor-immune interactions and spatial biomarker discovery.
• Identified genes and cell populations represent potential novel diagnostic and prognostic markers for breast cancer.