Protein-based immune profiles of basal-like vs. luminal breast cancers

Abstract

Tumor-infiltrating lymphocytes play an important, but incompletely understood role in chemotherapy response and prognosis. In breast cancer, there appear to be distinct immune responses by subtype, but most studies have used limited numbers of protein markers or bulk sequencing of RNA to characterize immune response, in which spatial organization cannot be assessed. To identify immune phenotypes of Basal-like vs. Luminal breast cancer we used the GeoMx® (NanoString) platform to perform digital spatial profiling of immune-related proteins in tumor whole sections and tissue microarrays (TMA). Visualization of CD45, CD68, or pan-Cytokeratin by immunofluorescence was used to select regions of interest in formalin-fixed paraffin embedded tissue sections. Forty-four antibodies representing stromal markers and multiple immune cell types were applied to quantify the tumor microenvironment. In whole tumor slides, immune hot spots (CD45+) had increased expression of many immune markers, suggesting a diverse and robust immune response. In epithelium-enriched areas, immune signals were also detectable and varied by subtype, with regulatory T-cell (T_reg) markers (CD4, CD25, and FOXP3) being higher in Basal-like vs. Luminal breast cancer. Extending these findings to TMAs with more patients (n = 75), we confirmed subtype-specific immune profiles, including enrichment of T_reg markers in Basal-likes. This work demonstrated that immune responses can be detected in epithelium-rich tissue, and that TMAs are a viable approach for obtaining important immunoprofiling data. In addition, we found that immune marker expression is associated with breast cancer subtype, suggesting possible prognostic, or targetable differences.

Figure 1). Subtype immune marker heterogeneity is apparent in epithelium-enriched regions versus immune hot spots.

(a) Representative whole tumor slide stained with CD45 (red), CD68 (yellow), and pan-Cytokeratin (green), in addition to 61 oligo-conjugated antibodies for immune and tumor cell markers. (b) Regions of interest (ROIs) were selected based on cellularity, large (650 μm), medium (500 μm), and small (300 μm). (c) Heatmap of protein expression for whole slide dataset with immunohistochemistry (IHC) subtype and cellularity labeled. Protein class clusters are denoted by colored bars and branches, with dark blue denoting stromal proteins, light blue denoting T cell and immune activation markers, and pink denoting immunosuppressive markers. (d-e) Volcano plots for Basal-like vs Luminal A subtypes were run separately for D) immune hot spot ROIs and E) epithelium-enriched ROIs. Data points are represented as black dots with annotation for markers with q < 0.05 and fold change > 2. Dashed lines indicate the cut off q < 0.05 and fold change < 2.

Figure 2). T_reg marker expression is higher in Basal-like tumors.

(a) T regulatory (T_reg) signatures were higher in Basal-like tumors compared to Luminal A tumors only in epithelium-enriched (p = 0.02) areas but not in immune-high regions (p = 0.86). (b) Higher T_reg signature expression in Basal-like tumors in tissue microarrays (TMAs) (p = 0.0078). (c) Receiver operating characteristic (ROC) analysis shows 92.9% sensitivity in Basal-like versus Luminal A classification based on T_reg signature expression. (d) Significant differences in immune marker expression between Luminal A and Basal-like tumors in TMAs. Volcano plot of Basal-like versus Luminal A. Data points are represented as black dots with annotation for markers with q < 0.05 and fold change > 2. Dashed lines indicate the cut off q < 0.05 and fold change < 2.