High-Dimensional SERS Mapping of Single Circulating Tumor Cells Deciphers the Phenotypic Landscape and Stratifies Metastatic Risk in Pancreatic Cancer.
TL;DR
Applying PRISM to CTCs from pancreatic cancer patients, a novel data analysis framework is introduced, including a 'Metastasis Potential Score' (MPS), to translate high-dimensional spectral data into a clinically relevant metric for risk stratification.
Abstract
The profound phenotypic heterogeneity of circulating tumor cells (CTCs) presents a major analytical challenge, demanding technologies capable of high-plex, quantitative single-cell profiling. Here, we introduce PRISM (Phenotypic Resolution via Immuno-SERS Mapping), a biosensing platform engineered to meet this challenge. The platform integrates a high-efficiency dual-antibody (anti-EpCAM/anti-CSV) capture substrate with a suite of seven spectrally orthogonal SERS nanoprobes, enabling crosstalk-free, multiplexed quantification of epithelial, mesenchymal, and stem-like (E-M-S) markers. We demonstrate the platform's robust analytical performance, including high capture efficiency for heterogeneous cell lines and excellent linearity. Its superior phenotypic resolving power was validated by quantitatively distinguishing canonical cell line archetypes and tracking dynamic protein expression shifts during induced epithelial-mesenchymal transition. Applying PRISM to CTCs from pancreatic cancer patients, we introduce a novel data analysis framework, including a 'Metastasis Potential Score' (MPS), to translate high-dimensional spectral data into a clinically relevant metric for risk stratification. Furthermore, longitudinal analysis of patient samples demonstrates the platform's utility as a dynamic monitoring tool, capable of tracking therapy-induced phenotypic shifts. PRISM establishes a powerful analytical methodology for high-dimensional single-cell analysis, providing a robust tool for both fundamental cancer biology research and translational clinical applications.