Integrating In Situ Immune Expression Landscape with Gene Expression-Based Subtyping to Characterize Breast Cancer Heterogeneity.

Background: We previously identified three clinically relevant immune [i.e., low-tumor-infiltrating lymphocyte (TIL), high-TIL, and high-interferon-stimulated gene (ISG)] subtypes of luminal breast cancer using RNA sequencing in a cohort of women from Hong Kong. In this study, we evaluated whether standard, in situ immunohistochemistry (IHC), a more clinically accessible approach, could capture similar immune heterogeneity across intrinsic (PAM50) subtypes.

Methods: In 148 patients with invasive breast cancer, we performed dual IHC staining for eight markers (CD3, CD8, CD20, FOXP3, CD68, CD163, PDL1, and IDO1) with pan-cytokeratin and quantified immune-positive cells in stromal regions by digital image analysis.

Results: IHC marker expression strongly correlated with gene expression-based immune and intrinsic subtypes. Compared with luminal tumors classified as low-TIL, high-TIL tumors showed higher levels of CD3, CD8, CD20, PDL1, and IDO1. Similarly, high-ISG tumors expressed higher CD3, CD8, CD20, PDL1, and IDO1 than low-TIL tumors but were distinguished from high-TIL tumors by elevated CD163. Immune marker expression was generally higher in HER2-enriched and basal-like tumors than in luminal A and B tumors, though substantial variability existed within each subtype. Luminal B tumors expressed higher levels of CD3, CD8, CD20, and CD163 compared with luminal A tumors. Notably, immune infiltration was more strongly aligned with aggressive tumor features such as high grade, risk of recurrence scores, and TP53 mutations than with estrogen receptor/progesterone receptor expression.

Conclusions: These findings confirm that subsets of luminal tumors harbor inflamed or macrophage-driven immune microenvironments.

Impact: Parsimonious IHC panels can perform immune classification, supporting their potential utility in refining subtype stratification and informing clinical decision-making, particularly in resource-limited settings.