Open Access Open Badges Research article

Protein and lipid MALDI profiles classify breast cancers according to the intrinsic subtype

Han Sung Kang1, Seok Cheol Lee15, Young Seung Park2, Young Eun Jeon3, Jeong Hwa Lee4, So-Youn Jung1, In Hae Park1, Seok Hoon Jang1, Hye Min Park1, Chong Woo Yoo1, Seok Hee Park5, Sang Yun Han3, Kwang Pyo Kim4, Young Hwan Kim26, Jungsil Ro1* and Hark Kyun Kim1*

Author Affiliations

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

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BMC Cancer 2011, 11:465  doi:10.1186/1471-2407-11-465

Published: 27 October 2011



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.


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.


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.


Protein and lipid profiles accurately distinguish tumor from adjacent normal tissue and classify breast cancers according to the intrinsic subtype.

protein; lipid; breast cancer; MALDI