Longitudinal single-cell profiling of breast tumors highlights immune and epigenetic mechanisms associated with sensitivity to aromatase inhibitors
Year: 2026
Type: article
Abstract: Estrogen receptor (ER)-positive breast cancer treatment is based primarily on endocrine therapy. To dissect mechanisms of sensitivity to aromatase inhibitors in ER-positive breast cancer, we profiled tumor biopsies from 25 patients during neoadjuvant therapy using single-cell RNA sequencing, immune receptor sequencing and enhancer activity mapping. Malignant cells with high ER signaling and elevated activity of enhancers with ER binding sites were sensitive to treatment. Resistance was associated with androgen receptor signaling, dedifferentiation and epithelial–mesenchymal transition. Poor responders preferentially used the androgen receptor cis-regulome under treatment pressure. The baseline tumor microenvironment was associated with tumor downstaging. Poor responders exhibited a ‘hot’, yet ineffective immune landscape enriched for naive lymphoid and undifferentiated myeloid cells. Good responders showed an active immune microenvironment with sustained clonal expansion of T cells. Our longitudinal single-cell analyses elucidate the genetic, cellular and epigenetic mechanisms driving sensitivity and resistance to neoadjuvant aromatase inhibition in ER-positive breast cancer. This longitudinal single-cell study of estrogen receptor (ER)-positive breast cancer suggests that strong estrogen signaling, ER-linked enhancers and active T cell responses could predict sensitivity to aromatase inhibitors, whereas resistance involves androgen signaling though hormone-sensing enhancer activity.
Source: Nature Genetics
Authors: Ilayda Altinönder, Villads Winton, Khang Lê Quý, Marie Fongaard, Pål Marius Bjørnstad, Elin Edda Seland Agustsdottir, Stephanie Beate Geisler, Manouchehr Seyedzadeh, Unn-Cathrin Buvarp, Marianne Lyngra, Arnoldo Frigessi, Diether Lambrechts, Vessela Kristensen, Anthony Mathelier, Victor Greiff, Jürgen Geisler, Xavier Tekpli
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $12,690
OpenAlex ID: W7225238170