Abstract
Noninvasive Raman imaging of non-fixed and unstained human colon tissues based on vibrational properties of noncancerous and cancerous samples can effectively enable the differentiation between noncancerous and tumor tissues. This work aimed to evaluate the biochemical characteristics of colon cancer and the clinical merits of multivariate Raman image and spectroscopy analysis. Tissue samples were collected during routine surgery. The non-fixed, fresh samples were used to prepare micrometer sections from the tumor mass and the tissue from the safety margins outside of the tumor mass. Adjacent sections were used for typical histological analysis. We have found that the chemical composition identified by Raman spectroscopy of the cancerous and the noncancerous colon samples is sufficiently different to distinguish pathologically changed tissue from noncancerous tissue. We present a detailed analysis of Raman spectra for the human noncancerous and cancerous colon tissue. The multivariate analysis of the intensities of lipids/proteins/carotenoids Raman peaks shows that these classes of compounds can statistically divide analyzed samples into noncancerous and pathological groups, reaffirming that Raman imaging is a powerful technique for the histochemical analysis of human tissues. Raman biomarkers based on ratios for lipids/proteins/carotenoids content were found to be the most useful biomarkers in spectroscopic diagnostics.
Highlights
Colon cancer ranks second with regard to the incidence of malignant tumors in women and men and is the third most common cause of death around the world
We will present the results for patients suffering from colon cancer—tubular carcinoma, cancer stage G2
Because it would be very inconvenient to analyze the whole Raman spectrum during surgery, the intensities of single peaks can vary in a broad range depending on the patient, and because some Raman peaks are observed in spectra of both the noncancerous and the cancerous tissues of human colon, we propose to calculate some ratios for Raman peaks to find parameters that credibly differentiate between the noncancerous and the cancerous tissues
Summary
Colon cancer ranks second with regard to the incidence of malignant tumors in women and men and is the third most common cause of death around the world. The mortality rate for this type of cancer is around 60% in the United States and Europe [1]. That’s why the colon mucosa is constantly exposed to diet- and bacterial-derived oxidants. Such chronic exposure to adverse conditions may lead to uncontrolled oxidative stress and DNA damage, which can cause colon homeostasis and cancer development. 95% of colon cancers are glandular cancers; the remaining 5% are squamous, mixed, or non-differentiated types [1]
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