Abstract
Ewing sarcoma is the second most common type of primary bone cancer and predominantly affects children and young people. Improved outcome prediction is key to delivering risk-adjusted, appropriate and effective care to cancer patients. Advances in the Fourier Transform Infrared (FTIR) spectroscopy of tissues enable it to be a non-invasive method to obtain information about the biochemical content of any biological sample. In this retrospective study, attenuated tissue reflection FTIR spectroscopy of biopsy samples from paediatric patients reveals spectral features that are diagnostic for Ewing Sarcoma. Furthermore, our results suggest that spectral features such as these may be of value for the prediction of treatment outcome independent to well-known, routinely used risk factors.
Highlights
Ewing sarcoma (ES) is a devastating, poorly differentiated, mesenchymal tumour of bones or soft tissues
The median wavenumber of maximum absorbance peak from 950–1100 cm−1 Fourier Transform Infrared (FTIR) spectrum from ES tumour biopsy before neo-CTx (Tb) was 1030 cm−1 for the whole analyzed group and it is significantly lower than the median for normal bone tissue (Tn) – 1036.5 cm−1 (p = 0.04)
The identification of clinically applicable methods that allow the adoption of risk-adapted therapeutic approaches is an unmet need in the treatment of bone cancers such as Ewing Sarcoma
Summary
Ewing sarcoma (ES) is a devastating, poorly differentiated, mesenchymal tumour of bones or soft tissues. FTIR has many advantages for analyzing of biological structures like the small sample size (a few micrograms) required for analysis, no need for pre-processing of tissue (e.g., demineralization, staining), no need for tissue dewaxing[14,15] and does not require the use of biological markers[16] Due to these advantages, FTIR can be applied to the very early stages of the disease, before the presence of changes is detectable by light microscopy[17], and may be suitable for the monitoring a disease course and therapeutic outcome[13]. Data analysis methods allow spectrum transformation, baseline correction, normalization and smoothing enable the quantitative analysis of FTIR spectra and have been applied to biology and medicine[13]
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