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Distinctive lipid profiles of human breast cancer and adjacent normal tissues by desorption electrospray ionization mass spectrometry imaging.
Abstracts that were granted an exception in accordance with ASCO's Conflict of Interest Policy are designated with a caret symbol (^).
Background: Routine intra-operative distinction between normal breast tissue and tumor is currently not possible in breast conserving surgery (BCS). This limitation affects the success of surgery, resulting in up to 40% requiring more than one operative procedure. Desorption electrospray ionization mass spectrometry (DESI MS) has been successfully used to discriminate between normal and cancerous human tissues from anatomical sites such as the liver and brain. The aim of this proof of concept study was to determine the feasibility of using DESI MS imaging for tissue identification and differentiation of breast cancer versus normal tissue. Methods: DESI MS imaging was carried out on 14 human invasive breast cancer samples. Breast cancer and adjacent normal paired human tissue sections (margin of tumor, 2cm and 5 cm from tumor) from 14 patients undergoing mastectomy were flash frozen in liquid nitrogen, sectioned, and thaw mounted to glass slides. All samples were imaged using DESI MS at 200 μm imaging resolution. DESI MS images were overlaid and compared with hematoxylin and eosin (H&E) images of the same sections. Results: Discrimination between cancer and adjacent normal tissue was achieved on the basis of the spatial distribution and varying intensities of particular fatty acids and lipid species. Several fatty acids such as oleic acid (m/z 281) and arachidonic acid (m/z 303) displayed much greater signal intensities in the cancer specimen compared to low or undetectable intensities in normal tissue. The cancer margins delineated by the DESI MS images of these molecules were consistent with H and E images of the tumor edge. Cancerous tissue was distinguished from normal tissue based on the qualitative assessment of molecular signatures and the distinction was in agreement with expert histopathology evaluation in 85% of samples. Conclusions: Our findings offer proof of concept that examination and classification of breast normal and cancer tissue by mass spectrometry imaging is highly accurate. The results are encouraging for development of a MS-based method that could be utilized intra-operatively for rapid detection of residual cancer tissue in the lumpectomy bed in BCS.