Characterisation of estrogen receptor alpha (ERα) expression in breast cancer cells and effect of drug treatment using targeted nanoparticles and SERS.

The detection and identification of estrogen receptor alpha (ERα), one of the main biomarkers in breast cancer, is crucial for the clinical diagnosis and therapy of the disease. Here, we use a non-destructive approach for detecting and localising ERα expression at the single cell level using surface enhanced Raman spectroscopy (SERS) combined with functionalised gold nanoparticles (AuNPs). Antibody functionalised nanotags (ERα-AuNPs) showed excellent biocompatibility and enabled the spatial and temporal understanding of ERα location in breast cancer cell lines with different ERα expression status. Additionally, we developed an approach based on the percentage area of SERS response to qualitatively measure expression level in ERα positive (ERα+) breast cancer cells. Specifically, the calculation of relative SERS response demonstrated that MCF-7 cells (ERα+) exhibited higher nanotag accumulation resulting in a 4.2-times increase in SERS signal area in comparison to SKBR-3 cells (ERα-). These results confirmed the strong targeting effect of ERα-AuNPs towards the ERα receptor. The functionalised ERα-AuNP nanotags were also used to investigate the activity of fulvestrant, the first-in-class approved selective estrogen receptor degrader (SERD). SERS mapping confirmed that ERα degradation occurred after fulvestrant treatment since a weaker SERS signal, and hence accumulation of nanotags, was observed in MCF-7 cells treated with fulvestrant. Most importantly, a correlation coefficient of 0.9 between the SERS response and the ERα expression level, obtained by western blot, was calculated. These results confirmed the strong relationship between the two approaches and open up the possibilities of using SERS as a tool for the estimation of ERα expression levels, without the requirement of destructive and time-consuming techniques. Therefore, the potential of using SERS as a rapid and sensitive method to understand the activity of SERDs in breast cancer is demonstrated.