Research article
Protein and lipid MALDI profiles classify breast cancers according to the intrinsic subtype
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* Corresponding authors: Jungsil Ro jungsro@ncc.re.kr - Hark K Kim hkim@ncc.re.kr
- † Equal contributors
1 National Cancer Center, Goyang, 410-769, Korea
2 Division of Mass Spectrometry Research, Korea Basic Science Institute, Ochang, 363-883, Korea
3 Center for Nano-Bio Convergence, Korea Research Institute of Standards and Science, Daejeon, 305-340, Korea
4 Department of Molecular Biotechnology, WCU Program, Konkuk University, Seoul, 143-701, Korea
5 Department of Biological Sciences, Sungkyunkwan University, Suwon, 440-746, Korea
6 Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764, Korea
BMC Cancer 2011, 11:465 doi:10.1186/1471-2407-11-465
Published: 27 October 2011Abstract
Background
Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) has been demonstrated to be useful for molecular profiling of common solid tumors. Using recently developed MALDI matrices for lipid profiling, we evaluated whether direct tissue MALDI MS analysis on proteins and lipids may classify human breast cancer samples according to the intrinsic subtype.
Methods
Thirty-four pairs of frozen, resected breast cancer and adjacent normal tissue samples were analyzed using histology-directed, MALDI MS analysis. Sinapinic acid and 2,5-dihydroxybenzoic acid/α-cyano-4-hydroxycinnamic acid were manually deposited on areas of each tissue section enriched in epithelial cells to identify lipid profiles, and mass spectra were acquired using a MALDI-time of flight instrument.
Results
Protein and lipid profiles distinguish cancer from adjacent normal tissue samples with the median prediction accuracy of 94.1%. Luminal, HER2+, and triple-negative tumors demonstrated different protein and lipid profiles, as evidenced by permutation P values less than 0.01 for 0.632+ bootstrap cross-validated misclassification rates with all classifiers tested. Discriminatory proteins and lipids were useful for classifying tumors according to the intrinsic subtype with median prediction accuracies of 80.0-81.3% in random test sets.
Conclusions
Protein and lipid profiles accurately distinguish tumor from adjacent normal tissue and classify breast cancers according to the intrinsic subtype.