Background <p>Immune checkpoint inhibitors (ICIs) can improve the pathological complete response (pCR) rate in estrogen receptor-positive (ER+)/human epidermal growth factor receptor 2-negative (HER2−) breast cancer (BC), particularly in patients with low estrogen receptor alpha (ERα) expression. This would imply that ERα expression could be a predictive biomarker for ICI response. In clinical trials, centralized immunohistochemistry (IHC) minimizes variability, but routine clinical practice faces challenges from staining artifacts and interpretation variability. Transcriptomic analyses offer a standardized, quantitative alternative. Based on this, we investigated <i>ESR1</i>, the gene encoding ERα, as a predictive biomarker for ICI response.</p> Methods <p>We analyzed bulk and single-cell RNA sequencing (RNAseq) BC cohorts. Patients were stratified by <i>ESR1</i> expression.</p> Results <p>In the ER+/HER2− subtype, high <i>ESR1</i> expression was associated with significantly less tumor-infiltrating lymphocytes. High <i>ESR1</i> expression was also associated with lower levels of key immune populations such as CD8<sup>+</sup> T cells, CD4<sup>+</sup> T effector memory T cells, type 1 macrophages, B cells, and dendritic cells, suggesting a less inflamed tumor microenvironment (TME). High <i>ESR1</i> also correlated with decreased cytolytic activity and lower pCR rates after neoadjuvant chemoimmunotherapy. Single-cell RNAseq further revealed an inverse correlation between <i>ESR1</i> expression and ICI response across cancer epithelial, normal epithelial, endothelial, and myeloid cells. Additionally, the predictive performance of <i>ESR1</i> surpassed <i>PDL1</i> in ER+ BC.</p> Conclusions <p>High <i>ESR1</i> expression was associated with an immunosuppressive TME in ER+/HER2− BC and is a more robust predictive biomarker for ICI response in this BC subtype.</p>

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ESR1 Expression Negatively Correlates with Immune Cell Infiltration and Response to Immune Checkpoint Inhibitors in Estrogen Receptor-Positive/HER2-Negative Breast Cancer

  • Jun Arima,
  • Kohei Chida,
  • Rongrong Wu,
  • Kohei Taniguchi,
  • Amber McKenery,
  • Brian G. Morreale,
  • Andrea M. Monell,
  • Scott I. Abrams,
  • John M. L. Ebos,
  • Kenichi Hakamada,
  • Takashi Ishikawa,
  • Seita Hagihara,
  • Kosei Kimura,
  • Mitsuhiko Iwamoto,
  • Sang-Woong Lee,
  • Kazuaki Takabe

摘要

Background

Immune checkpoint inhibitors (ICIs) can improve the pathological complete response (pCR) rate in estrogen receptor-positive (ER+)/human epidermal growth factor receptor 2-negative (HER2−) breast cancer (BC), particularly in patients with low estrogen receptor alpha (ERα) expression. This would imply that ERα expression could be a predictive biomarker for ICI response. In clinical trials, centralized immunohistochemistry (IHC) minimizes variability, but routine clinical practice faces challenges from staining artifacts and interpretation variability. Transcriptomic analyses offer a standardized, quantitative alternative. Based on this, we investigated ESR1, the gene encoding ERα, as a predictive biomarker for ICI response.

Methods

We analyzed bulk and single-cell RNA sequencing (RNAseq) BC cohorts. Patients were stratified by ESR1 expression.

Results

In the ER+/HER2− subtype, high ESR1 expression was associated with significantly less tumor-infiltrating lymphocytes. High ESR1 expression was also associated with lower levels of key immune populations such as CD8+ T cells, CD4+ T effector memory T cells, type 1 macrophages, B cells, and dendritic cells, suggesting a less inflamed tumor microenvironment (TME). High ESR1 also correlated with decreased cytolytic activity and lower pCR rates after neoadjuvant chemoimmunotherapy. Single-cell RNAseq further revealed an inverse correlation between ESR1 expression and ICI response across cancer epithelial, normal epithelial, endothelial, and myeloid cells. Additionally, the predictive performance of ESR1 surpassed PDL1 in ER+ BC.

Conclusions

High ESR1 expression was associated with an immunosuppressive TME in ER+/HER2− BC and is a more robust predictive biomarker for ICI response in this BC subtype.