# An Extracellular Matrix Overlay Model for Bioluminescence Microscopy to Measure Single-Cell Heterogeneous Responses to Antiandrogens in Prostate Cancer Cells

## TL;DR

The paper introduces a new cell culture model to track prostate cancer cells' responses to drugs at the single-cell level using bioluminescence imaging.

## Contribution

The novel extracellular matrix-Matrigel model improves single-cell tracking and viability for studying antiandrogen responses in prostate cancer cells.

## Key findings

- The ECM-M model triples the traceability of poorly adherent prostate cancer cells.
- Single-cell imaging reveals heterogeneous antiandrogen responses linked to drug IC50 values.
- The model enables precise monitoring of androgen receptor modulation in diverse prostate cancer cell lines.

## Abstract

Prostate cancer (PCa) displays diverse intra-tumoral traits, impacting its progression and treatment outcomes. This study aimed to refine PCa cell culture conditions for dynamic monitoring of androgen receptor (AR) activity at the single-cell level. We introduced an extracellular matrix-Matrigel (ECM-M) culture model, enhancing cellular tracking during bioluminescence single-cell imaging while improving cell viability. ECM-M notably tripled the traceability of poorly adherent PCa cells, facilitating robust single-cell tracking, without impeding substrate permeability or AR response. This model effectively monitored AR modulation by antiandrogens across various PCa cell lines. Single-cell imaging unveiled heterogeneous antiandrogen responses within populations, correlating non-responsive cell proportions with drug IC50 values. Integrating ECM-M culture with the PSEBC-TSTA biosensor enabled precise characterization of ARi responsiveness within diverse cell populations. Our ECM-M model stands as a promising tool to assess heterogeneous single-cell treatment responses in cancer, offering insights to link drug responses to intracellular signaling dynamics. This approach enhances our comprehension of the nuanced and dynamic nature of PCa treatment responses.