Biochemical Alterations from Normal Mucosa to Gastric Cancer by Ex vivo Magnetic Resonance Spectroscopy

Background and Aims: The metabolic profile and morphologic aspects of normal and pathologic human gastric mucosa were studied. The aim of the present research was the application of ex vivo high-resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) to the human gastric tissue to get information on the molecular steps involved in gastric carcinogenesis and the identification of biochemical markers useful for the development of in vivo MRS methodologies to diagnose gastric pathologies in clinical situations. Methods: Twelve normal subjects, five with autoimmune atrophic gastritis, five with Helicobacter pylori infection, and five with adenocarcinoma were examined. Ten biopsies were taken during endoscopy from each patient. Specimens from carcinoma were also obtained during gastrectomy. Of the 10 biopsies, 4 were used for histologic evaluation, 4 were fixed in glutaraldehyde and processed for transmission and scanning electron microscopy, and 2 were immersed in liquid nitrogen and stored at −85°C for monodimensional and bidimensional ex vivo HR-MAS MRS analysis. Results: Ex vivo HR-MAS MRS identified glycine, alanine, free choline, and triglycerides as possible molecular markers related to the human gastric mucosa differentiation toward preneoplastic and neoplastic conditions. Ultrastructural studies of autoimmune atrophic gastritis and gastric adenocarcinoma revealed lipid accumulations intracellularly and extracellularly associated with a severe prenecrotic hypoxia and mitochondria degeneration. Conclusions: This is the first report of synergic applications of ex vivo HR-MAS MRS and electron microscopy in studying the human gastric mucosa differentiation. This research provides useful information about some molecular steps involved in gastric carcinogenesis. The biochemical data obtained on gastric pathologic tissue could represent the basis for clinical applications of in vivo MRS. (Cancer Epidemiol Biomarkers Prev 2008;17(6):1386–95)

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