Accurate identification of prostate cancer in frozen sections at the time of surgery can be challenging, limiting the surgeon's ability to best determine resection margins during prostatectomy. We performed desorption electrospray ionization mass spectrometry imaging (DESI-MSI) on 54 banked human cancerous and normal prostate tissue specimens to investigate the spatial distribution of a wide variety of small metabolites, carbohydrates, and lipids. In contrast to several previous studies, our method included Krebs cycle intermediates (m/z <200), which we found to be highly informative in distinguishing cancer from benign tissue. Malignant prostate cells showed marked metabolic derangements compared with their benign counterparts. Using the "Least absolute shrinkage and selection operator" (Lasso), we analyzed all metabolites from the DESI-MS data and identified parsimonious sets of metabolic profiles for distinguishing between cancer and normal tissue. In an independent set of samples, we could use these models to classify prostate cancer from benign specimens with nearly 90% accuracy per patient. Based on previous work in prostate cancer showing that glucose levels are high while citrate is low, we found that measurement of the glucose/citrate ion signal ratio accurately predicted cancer when this ratio exceeds 1.0 and normal prostate when the ratio is less than 0.5. After brief tissue preparation, the glucose/citrate ratio can be recorded on a tissue sample in 1 min or less, which is in sharp contrast to the 20 min or more required by histopathological examination of frozen tissue specimens. prostate cancer | Krebs cycle | metabolism | desorption electrospray ionization | mass spectrometry P rostate cancer (PCa) is the most commonly diagnosed solidorgan cancer and the second leading cause of cancer death in men in the United States (1). Because of prostate-specific antigen (PSA) screening in the United States, most PCas are discovered when they are confined to the prostate (2). Many of these localized PCas are treated by surgical removal of the entire prostate (radical prostatectomy). The presence of cancer cells at the edge of the surgical resection, or positive surgical margins, is associated with higher rates of recurrence and death from PCa (3, 4). Therefore, an important clinical challenge in PCa management is to devise a rapid and highly accurate method to detect cancerous cells in real time to allow resection of additional periprostatic tissues and reduce cancer recurrence after surgery. Over the last decade, several innovative analytical techniques (5-12) have been developed to distinguish cancer from benign tissue in various organs. However, none has achieved wide clinical adoption for various reasons including inconvenience, narrow information content, unavailability, poor sensitivity, slowness of adoption, and operating room workflow incompatibility. In PCa, intraoperative frozen sections have been used to attempt to identify PCa at the margin based on analysis of histology. However, frozen sections have been shown to have poor sensitivity and specificity for the detection of PCa and currently are not recommended Recently, a label-free molecular imaging method called desorption electrospray ionization mass spectrometric imaging (DESI-MSI) has been developed (15-17). DESI-MSI can rapidly evaluate the tissue metabolome in situ by simultaneously characterizing hundreds of lipids and metabolites. In the last 5 y, reports from our group Given the known alterations in metabolic pathways in PCa, we tested whether DESI-MSI of metabolites and lipids could have utility in discriminating cancer from normal tissue obtained from radical prostatectomy. Using tandem and high-resolution mass spectrometry we have characterized the distinct metabolite and lipid profiles of normal and malignant prostate. Although many earlier DESI-MSI studies considered only lipid profiles in identification of cancer, here we report imaging small metabolite Significance Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is a label-free molecular imaging technique that provides a window into the biochemical processes present in benign and malignant prostate tissue. This is important both in improving the understanding of tissue biology and in achieving rapid cancer diagnosis. We applied DESI-MSI to record lipid, carbohydrate, and most importantly, small metabolite images from 54 normal and malignant prostate tissue specimens. Several Krebs cycle intermediates were present at different concentrations in prostate cancer compared with normal tissue. Statistical calculations identified panels of metabolites that could readily distinguish prostate cancer from normal tissue with nearly 90% accuracy in a validation set. The results also indicated that the ratio of glucose to citrate ion signals could be used to accurately identify prostate cancer
