がん細胞における遊走能の候補となるスペクトルバイオマーカーのマイクロFTIRおよびO‑PTIR分光法を用いた調査

Routine diagnostic practice for cancer and metastasis relies on a time-consuming staining process and the use of antibodies to detect selected molecular markers and is hence limited by a lack of real-time data and the availability of molecular information. Against this background, techniques based on rapid chemical analysis to identify migratory properties are highly desirable. Fourier-Transform Infrared (FTIR) microspectroscopy has a long history in the label-free identification of infrared marker bands for cancer detection. However, it requires extensive postprocessing of the acquired spectra, is of limited suitability for analysis in aqueous environments, and has poor spatial resolution. To overcome these challenges, we are using a new method termed Optical Photothermal Infrared (O-PTIR) spectroscopy to detect local absorption to establish potential IR tumor markers and classification models. We report on experimental outcomes using machine learning and FTIR microspectroscopy for the classification of cells and the analysis of spectral features reflecting cancer and migratory properties, comparing a commercial FTIR microspectrometer to a custom-built O-PTIR instrument dedicated to spectroscopic measurement and imaging in microfluidic channels.