Raman microspectroscopy and multivariate analysis in radiobiology: Study of the effects of X-ray irradiation on neuroblastoma cells

Raman micro-spectroscopy is becoming very popular in the field of radiobiology and radiation oncology for its ability to assess the cellular damage at the molecular level. It can be used to monitor the minimum doses required to lethally damage tumor cells, as well as to reduce the risk of excess dose being delivered to healthy surrounding cells. These results can be achieved also thanks to the development of specific data analysis methods enabling the extraction of information embedded in the Raman spectra of complex samples, such as human cells. Among different data analysis procedures, multivariate analysis has been proven to be particularly effective. The principal component analysis (PCA) method has been largely used for analyzing Raman spectra from cells and tissues. In some cases, the PCA can be performed on selected wavenumber ranges of Raman spectra to get information embedded in those specific ranges (interval-PCA). In the present work, the application of these methods to the analysis of Raman spectra from single SH-SY5Y neuroblastoma cells following the exposure to graded doses of X-rays is reported and specific details from X-ray effects on nucleus and cytoplasm regions are obtained. In addition, the biochemical changes occurring in these cells are also discussed by using an alternative approach, namely the analysis of difference spectra, obtained by subtracting the cytoplasm-related spectrum from the corresponding one detected at the nucleus. It’s worth to note that multivariate analysis has allowed us to unravel the subtle modifications, due to X-ray irradiation, of Raman features related to specific components. These results pave the way to develop proper data analysis methods allowing to manage, on one hand, the complexity of the Raman spectra of cells and tissues and, on the other hand, the high number of spectra needed to consider the intrinsic variability of biological samples.