Metabolomics patterns of breast cancer tumors using mass spectrometry imaging.

Abstract

Intraoperative assessment of surgical margins is important for reducing the rate of revisions in breast conserving surgery for palpable malignant tumors. The hypothesis was that metabolomics methods, based on mass spectrometry, could find patterns of relative abundances of molecules that distinguish clusters of benign tissue and cancer in surgical resections. Excisions from 8 patients were used to acquire 112,317 mass spectrometry signals by desorption electrospray ionization. A process of nonnegative matrix factorization and graph decomposition produced clusters that were approximated as affine spaces. Each signal's distance to the affine space of a cluster was used to visualize the clustering. The distance maps were superior to binary clustering in identifying cancer regions. They were particularly effective at finding cancer regions that were discontinuously distributed within benign tissue. Desorption electrospray ionization mass spectrometry, which has been shown to be useful intraoperatively, can acquire signals that distinguish malignant from benign breast tissue in surgically excised tumors. The method may be suitable for real-time surgical decisions based on cancer margins.