Engineering a Single-Cell Platform to Study Estrogen Receptor-α Regulation of the Genome in Breast Cancer Microenvironments.

Approximately 70% of breast cancers are estrogen receptor (ER) positive, and endocrine therapies targeting ERα remain the cornerstone of treatment. Despite their efficacy, nearly one-third of patients relapse due to acquired resistance, often accompanied by metastasis and poor prognosis. Tumour hypoxia, a hallmark of the breast cancer microenvironment, exacerbates intra-tumour heterogeneity, reshaping transcriptional programmes and contributing to therapy resistance. Hypoxia-inducible factors (HIFs) alter chromatin accessibility and transcription factor (TF) activity, yet the mechanisms by which hypoxia influences ERα binding heterogeneity remain unresolved.
Traditional methods, such as chromatin immunoprecipitation followed by sequencing (ChIP-Seq), have defined ERα binding landscapes but cannot capture heterogeneity in single-cell resolution. Recent advances in single-cell calling card (scCC) assays, in which engineered TF-transposase fusion proteins deposit genomic tags at binding sites, make scCC an attractive method to study ERα binding and transcriptomic heterogeneity across tumours. Self-reporting transposons are recoverable from mRNA, allowing direct linkage of TF binding events to cell identity. When integrated with single-cell RNA sequencing, Calling Cards uniquely provide simultaneous readouts of TF binding and cell fate.
In this thesis, we present the engineering and validation of a novel HyPB-ERα transposase fusion protein that reproduces ERα binding patterns across the genome. Bulk and long-read Calling Card assays demonstrate strong concordance with gold-standard ChIP-Seq and ChIA-PET datasets, confirming specificity and biological relevance. Building on this, we establish a three-dimensional MCF7 spheroid model that recapitulates hypoxia gradients observed in vivo, enabling interrogation of ERα binding heterogeneity under physiologically relevant conditions.
Together, these advances culminate in the development of a scCC ERα platform, integrating TF binding, transcriptomic identity, and microenvironmental context, working towards the aim of enabling investigations into the heterogeneity of ERα binding and gene expression across cancer models. Future applications of this work will enable mechanistic insight into how hypoxia drives ERα heterogeneity and therapy resistance.