A recent study introduces a new development in cancer research using Raman spectroscopy.
In a recent study published in Talanta, a research team presented and tested out a new aluminum-based microwell platform that was designed to improve the performance of single-cell Raman spectroscopy (1). This study, led by Bei Li, who is affiliated with several institutions, including the Changchun Institute of Optics, the University of Chinese Academy of Sciences, the State Key Laboratory of Applied Optics, and the Key Laboratory of Advanced Manufacturing for Optical Systems, and Jiabao Xu from the University of Glasgow, demonstrates how single-cell Raman spectroscopy can improve personalized medicine, cancer diagnostics, and biomedical research (1).
Single cell Raman spectroscopy (SCRS) is a non-invasive, label-free technique (2). It is often used to conduct in vivo analysis of individual living cells (2). Each cell's Raman spectrum contains over 1000 bands, offering detailed molecular information about components like nucleic acids, proteins, carbohydrates, and lipids (2). Single-cell analysis is important in precision medicine because it allows scientists to learn more about cellular heterogeneity that conventional bulk analysis often overlooks (1).
In this study, the research team proposed a new platform that was built on microwell-assembled aluminum substrates. By using this platform, the researchers attempted to address a major limitation in single-cell Raman spectroscopy, which is the instability of cells in liquid suspension and the poor signal-to-noise (S/N) ratio caused by movement and background interference (1).
The aluminum microwell chip differentiates and improves upon traditional glass substrates in one major way. The microwell chip can isolate individual cells in structured wells, which helps prevent cell stacking and movement (1). This structural stability, combined with aluminum’s high reflectivity, amplifies the Raman signal significantly, resulting in much clearer and more reliable spectroscopic data (1).
Using this technology to two cell lines—PC-9 lung cancer cells and BEAS-2B normal bronchial epithelial cells—the research team was able to demonstrate their platform’s capabilities. The Raman spectra revealed notable biochemical differences between the cancerous and non-cancerous cells (1). The study showed that the cancer cells displayed higher levels of adenine, cytochromes, DNA/RNA, and unsaturated lipids, as well as increased protein content and unsaturation ratios (1). As a result, this observation indicates altered cancer metabolism.
In the second part of the study, the research team used machine learning (ML) algorithms to confirm the spectral distinctions. The k-Nearest Neighbor (kNN) algorithm achieved a strong classification accuracy of 97.8%, whereas the more advanced eXtreme Gradient Boosting (XGBoost) model achieved a perfect classification accuracy of 100% (1). These results underscore the platform’s robustness and its potential to contribute to accurate cancer diagnostics.
The researchers noted in their study that the high signal stability and enhanced signal-to-noise (S/N) ratio offered by the microwell-assembled aluminum chip opens new possibilities for non-invasive, label-free single-cell analysis in real-time (1).
The researchers also noted that the platform was built to conduct high-throughput analysis, featuring more than 120,000 microwells that can be customized for different cell sizes and experimental scales (1). This flexibility enables wide applicability across biomedical research areas, from cancer cell profiling to drug screening (1).
Importantly, the system is compatible with Raman-activated cell sorting (RACS), a non-invasive technique that allows researchers to identify and sort live cells based on their Raman spectra (1,3). This integration is particularly promising for isolating rare cell types, such as circulating tumor cells (CTCs), which are critical for early cancer detection and the monitoring of metastasis (1).
By allowing cells to be studied in native liquid environments without fixation or staining, the aluminum microwell chip preserves metabolic integrity, enabling researchers to obtain more biologically relevant data. This is a crucial advantage over dried or fixed samples, which can distort cellular chemistry (1).
By offering a robust, scalable, and highly sensitive method for single-cell analysis, this aluminum microwell technology could become more widely used in both clinical and research settings.
