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

Abstract

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.

Keywords: Krebs cycle; desorption electrospray ionization; mass spectrometry; metabolism; prostate cancer.

Fig. 1.

(A) Negative ion mode DESI mass spectrum in the m/z range 50–200 from a typical prostate tissue specimen showing ion signals of various small metabolites. (B) Spatial distribution of 14 different small metabolites in a prostate tissue specimen (Upper Left, the corresponding H&E staining of the tissue sample) that contains both normal (black outline) and cancer (red outline). In B some individual small metabolite distributions are mapped throughout the tissue, whereas in A the abundance of all small metabolites is displayed by averaging all pixels over a typical line scan. See SI Appendix, Tables S1 and S2 for identification of species with different m/z values. The abundance of the given ion in the corresponding ion image is normalized to 100%.

Fig. 2.

Schematic overview of the metabolic flux in the Krebs cycle. DESI-MSI study (e.g., Fig. 1B) shows that the abundances of metabolites labeled in red are up-regulated and blue are down-regulated in cancer compared with normal tissue.

Fig. 3.

Distribution of glucose/citrate ratio of some representative prostate tissue specimens showing significant elevation of the glucose/citrate ratio in cancer. The Top of each panel (A–O) shows the histopathological evaluation (H&E) of the corresponding tissue, where cancer areas have been demarcated by red, benign areas by black, stroma areas by green, and inflammation areas by blue.

Fig. 4.

Extracted ion chronogram of glucose and citrate over a line scan of a typical prostate tissue specimen that contains both benign (black outline) and cancer (red outline) areas. (Inset) H&E staining of the tissue and the position of the line scan (blue).

Fig. 5.

Negative ion mode DESI-MS ion signal intensity ratios for glucose/citrate are plotted for (A) the training set (18 benign and 18 cancer specimens), and (B) the validation set (10 benign and 8 cancer specimens) by averaging the ion signals of glucose and citrate from all pixels acquired from the individual tissue sample. From these plots, a tissue can be classified as cancer when glucose/citrate signal ratio is >1, and benign when the ratio is <0.5.