Characterization of colorectal mucus using infrared spectroscopy: a potential target for bowel cancer screening and diagnosis
Jayakrupakar Nallala, Charles Jeynes, Sarah Saunders, Neil Smart, Gavin R. Lloyd, Leah Riley, Debbie Salmon, Nicholas Stone
Abstract
Biological materials presenting early signs of cancer would be beneficial for cancer screening/diagnosis. In this respect, the suitability of potentially exploiting mucus in colorectal cancer was tested using infrared spectroscopy in combination with statistical modeling. Twenty-six paraffinized colon tissue biopsy sections containing mucus regions from 20 individuals (10 normal and 16 cancerous) were measured using mid-infrared spectroscopic imaging. A digital de-paraffinization, followed by cluster analysis driven digital color-coded multi-staining segmented the infrared images into various histopathological features such as epithelium, connective tissue, stroma, and mucus regions within the tissue sections. Principal component analysis followed by supervised linear discriminant analysis was carried out on pure mucus and epithelial spectra from normal and cancerous regions of the tissue. For the mucus-based classification, a sensitivity of 96%, a specificity of 83%, and an area under the curve performance of 95% was obtained. For the epithelial tissue-based classification, a sensitivity of 72%, a specificity of 88%, and an area under the curve performance of 89% was obtained. The mucus spectral profiles further showed contributions indicative of glycans including that of sialic acid changes between these pathology groups. The study demonstrates that infrared spectroscopic analysis of mucus discriminates colorectal cancers with high sensitivity. This concept could be exploited to develop screening/diagnostic approaches complementary to histopathology. Mucus was tested as a potential biological material for screening/early diagnosis of colorectal cancer using infrared spectroscopy. Based on a digital histopathology and statistical modeling approach, cancerous and non-cancerous samples were classified with an area under the curve performance of 95% based on mucus spectral profiles, indicating changes in the glycan component of mucins.