A novel DESI MSI approach to the diagnosis and characterization of breast cancer tissue

摘要

Prediction of tissue type and tumor type can be made based on its metabonomic fingerprint and multivariate statistical analysis with an accuracy of >90%. Changes in the metabonomic fingerprint of the tissues due to cancer growth were found in the main three breast tissue types. Lipid PS(36:1) was more highly expressed in the morphologically normal breast tissue of cancer patients to a statistically significant degree. Prediction of tumor grade can be made based on the metabonomic fingerprint of the lesion and the morphogically normal breast tissue with high accuracy.