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Developing Raman spectroscopy as a diagnostic tool for label‐free antigen detection
Authors:Aaran T Lewis  Riana Gaifulina  Naomi J Guppy  Martin Isabelle  Jennifer Dorney  Gavin R Lloyd  Manuel Rodriguez‐Justo  Catherine Kendall  Nicholas Stone  Geraint M Thomas
Institution:1. Department of Cell and Developmental Biology, University College London, London, UK;2. UCL‐Advanced Diagnostics, University College London, London, UK;3. Biophotonics Research Unit, Gloucester Royal Hospitals NHS Foundation Trust, Gloucestershire, UK;4. School of Physics and Astronomy, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
Abstract:For several decades, a multitude of studies have documented the ability of Raman spectroscopy (RS) to differentiate between tissue types and identify pathological changes to tissues in a range of diseases. Furthermore, spectroscopists have illustrated that the technique is capable of detecting disease‐specific alterations to tissue before morphological changes become apparent to the pathologist. This study draws comparisons between the information that is obtainable using RS alongside immunohistochemistry (IHC), since histological examination is the current GOLD standard for diagnosing a wide range of diseases. Here, Raman spectral maps were generated using formalin‐fixed, paraffin‐embedded colonic tissue sections from healthy patients and spectral signatures from principal components analysis (PCA) were compared with several IHC markers to confirm the validity of their localizations. PCA loadings identified a number of signatures that could be assigned to muscle, DNA and mucin glycoproteins and their distributions were confirmed with antibodies raised against anti‐Desmin, anti‐Ki67 and anti‐MUC2, respectively. The comparison confirms that there is excellent correlation between RS and the IHC markers used, demonstrating that the technique is capable of detecting compositional changes in tissue in a label‐free manner, eliminating the need for antibodies. image
Keywords:classification  diagnosis  immunohistochemistry  Raman spectroscopy  tissue
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