Diagnosis of prostate cancer by desorption electrospray ionization mass spectrometric imaging of small metabolites and lipids

Abstract

<p id="d6932720e251">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. </p><p class="first" id="d6932720e254">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 ( <i>m/z</i> &lt;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. </p>