Abstract 5539: Single-cell and spatial approaches of identifying targets in endocrine therapy-resistant breast cancer

Even though most women with estrogen receptor (ER) positive breast tumors can benefit from endocrine therapy (ET), up to 40% of these patients will experience relapse. The percentage of tumor cells expressing ER varies from 1 to 100%, and some studies suggest that higher expression of ER positively correlates with ET efficiency and reduced rate of tumor relapse. We have previously identified a cell population with active NFĸB and integrated stress response pathways that is able to survive selective pressure of ET and contribute to the tumor relapse. However, we and others routinely use models that are highly enriched for ER-expressing cells to study the effect of ET. Much less is known about ET efficiency for breast cancers with a low to moderate number of ER-expressing cells, which tend to be more aggressive. Here, we decided to use patient-derived xenograft organoids (PDxOs) and a single-cell-based approach in order to study how breast cancer models with low to moderate levels of ER expression respond to ET. In addition to the already established PDxOs (HCI003 and HCI017), we developed another two models (UIC013 and UIC020), in which 22%, 30%, 12%, and 7% of cells express ERα, respectively. Using single-cell RNA sequencing (scRNAseq), we established that each PDxO has a model-specific transcriptional profile that is reflected in differentially activated pathways and in the expression of clinically relevant markers associated with more aggressive phenotypes. More specifically, we found that HCI003 and UIC020 are enriched for gene signatures associated with ET resistance and breast cancer stem cells, whereas UIC013 is enriched for invasive/EMT signatures. To understand whether PDxOs are sensitive to ET, we treated each model with fulvestrant and 4-hydroxytamoxifen. We found that some of the cell populations are lost with ET, suggesting that they are responsive to ET, while others showed no change or even enrichment with ET, suggesting that they are resistant to ET. To identify alternative therapeutic options for the ET-resistant cell population, we used DREEP analysis (DRug Estimation from single-cell Expression Profile), a bioinformatic tool that predicts drug response to 450 compounds for scRNAseq dataset. Multiple compounds were predicted to be effective in combination with ET, including vandetanib, an inhibitor of VEGFR2, which is now in a clinical study as an additional treatment to fulvestrant for metastatic breast cancer. We also found several novel therapeutic compounds that can be used to eradicate ET-resistant cell populations. Taken together, these findings indicate that stratifying breast cancer cell populations based on response to ET, rather than ER expression or activity, can lead to the identification of new cell populations, as well as therapeutic strategies to target these populations, thereby improving outcomes for women with breast tumors. Citation Format: Svetlana E. Semina, Rosemary Huggins J. Huggins, Debra Tonetti, Kent Hoskins, Geoffrey L. Greene, Jonna Frasor, Jonathan Coloff. Single-cell and spatial approaches of identifying targets in endocrine therapy-resistant breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5539.