title: 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.
authors.affiliation: Department of Chemistry, Stanford University, Stanford, CA 94305.
authors.forename: Shibdas
authors.initials: S
authors.lastname: Banerjee
authors.affiliation: Department of Chemistry, Stanford University, Stanford, CA 94305; zare@stanford.edu.
authors.forename: Richard N
authors.initials: RN
authors.lastname: Zare
authors.affiliation: Department of Biomedical Data Sciences, Stanford University, Stanford, CA 94305.|Department of Statistics, Stanford University, Stanford, CA 94305.
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Tibshirani
authors.affiliation: Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305.
authors.forename: Christian A
authors.initials: CA
authors.lastname: Kunder
authors.affiliation: Department of Urology, Stanford University School of Medicine, Stanford, CA 94305.
authors.forename: Rosalie
authors.initials: R
authors.lastname: Nolley
authors.affiliation: Department of Urology, Stanford University School of Medicine, Stanford, CA 94305.
authors.forename: Richard
authors.initials: R
authors.lastname: Fan
authors.affiliation: Department of Urology, Stanford University School of Medicine, Stanford, CA 94305.
authors.forename: James D
authors.initials: JD
authors.lastname: Brooks
authors.affiliation: Department of Urology, Stanford University School of Medicine, Stanford, CA 94305.
authors.forename: Geoffrey A
authors.initials: GA
authors.lastname: Sonn
mesh_terms: D002952:Citric Acid Cycle; D006801:Humans; D050356:Lipid Metabolism; D008055:Lipids / Q000737:chemistry*; D008297:Male; D011471:Prostatic Neoplasms / Q000737:chemistry / Q000175:diagnosis* / Q000378:metabolism* / Q000473:pathology; D021241:Spectrometry, Mass, Electrospray Ionization / Q000379:methods*
chemical_list: D008055:Lipids
keywords: Krebs cycle; desorption electrospray ionization; mass spectrometry; metabolism; prostate cancer