Abstract
Background
Unlike estrogen receptor (ER)-negative breast cancer, ER-positive breast cancer outcome is less influenced by lymphocyte content, indicating the presence of immune tolerance mechanisms that may be specific to this disease subset.
Methods
A supervised analysis of microarray data from the ACOSOG Z1031 (Alliance) neoadjuvant aromatase inhibitor (AI) trial identified upregulated genes in Luminal (Lum) B breast cancers that correlated with AI-resistant tumor proliferation (percentage of Ki67-positive cancer nuclei, Pearson r > 0.4) (33 cases Ki67 > 10% on AI) vs LumB breast cancers that were more AI sensitive (33 cases Ki67 < 10% on AI). Overrepresentation analysis was performed using WebGestalt. All statistical tests were two-sided.
Results
Thirty candidate genes positively correlated (r ≥ 0.4) with AI-resistant proliferation in LumB and were upregulated greater than twofold. Gene ontologies identified that the targetable immune checkpoint (IC) components IDO1, LAG3, and PD1 were overrepresented resistance candidates (P ≤ .001). High IDO1 mRNA was associated with poor prognosis in LumB disease (Molecular Taxonomy of Breast Cancer International Consortium, hazard ratio = 1.43, 95% confidence interval = 1.04 to 1.98, P = .03). IDO1 also statistically significantly correlated with STAT1 at protein level in LumB disease (Pearson r = 0.74). As a composite immune tolerance signature, expression of IFN-γ/STAT1 pathway components was associated with higher baseline Ki67, lower estrogen, and progesterone receptor mRNA levels and worse disease-specific survival (P = .002). In a tissue microarray analysis, IDO1 was observed in stromal cells and tumor-associated macrophages, with a higher incidence in LumB cases. Furthermore, IDO1 expression was associated with a macrophage mRNA signature (M1 by CIBERSORT Pearson r = 0.62 ) and by tissue microarray analysis.
Conclusions
Targetable IC components are upregulated in the majority of endocrine therapy–resistant LumB cases. Our findings provide rationale for IC inhibition in poor-outcome ER-positive breast cancer.
High-Throughput Tissue Microarray Analysis to Evaluate Genes Uncovered by cDNA Microarray Screening in Renal Cell Carcinoma