Abstract
Histopathologic diagnosis of renal cell carcinoma (RCC) may sometimes be difficult with small biopsy samples. We applied histology-directed matrix-assisted laser desorption/ionization mass spectrometry to RCC samples to evaluate whether and how lipid profiles are different between RCC and normal tissue. We evaluated 59 RCC samples and 24 adjacent normal tissue samples collected from patients who underwent surgery. Five peaks were significantly differently expressed (p < 10−7) between RCCs and adjacent normal tissue samples. C24-OH sulfatide (ST-OH {18:1/24:0}[M-H]−; m/z 906.7 in the negative ion mode) and C22-OH sulfatide (ST-OH {18:1/22:0}[M-H]−; m/z 878.6 in the negative ion mode) were most significantly underexpressed in RCC samples, compared with adjacent normal tissue samples. With 100 random training-to-test partitions within these samples, the median prediction accuracy (RCC vs. normal) ranged from 96.3% to 100% at p cutoff values for feature selection ranging from 0.001 to 10−7. Two oncocytoma samples were predicted as normal tissue by five lipids that were differentially expressed between RCC and normal tissue at p < 10−7. Clear-cell, papillary, and chromophobe RCCs were different in lipid profiles. Permutation p- values for 0.632+ bootstrap cross-validated misclassification rates were less than 0.05 for all the classifiers. Thus, lipid profiles differentiate RCC from normal tissue and may possibly classify the histology of RCC. © 2014 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons, Ltd.
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