Journal of Proteomics & Bioinformatics
Open Access

Abstract

Lipid MALDI MS Profiling Accurately Distinguishes Papillary Thyroid Carcinoma from Normal Tissue

Junsun Ryu, Geul Bang, Jeong Hwa Lee, Seung Ho Choi, Yuh–Seog Jung, Kwang Pyo Kim, Young Hwan Kim and Hark Kyun Kim

Background: Histology-directed tissue Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry (MALDI MS) has been used to identify lipid profiles that can distinguish cancerous epithelium from normal epithelium.

Methods: In order to evaluate if lipid profiles may assist with diagnosis, frozen resected tumor samples collected from papillary thyroid carcinoma patients were analyzed using Matrix (DHB/CHCA)-Assisted Laser Desorption/ Ionization (MALDI) Mass Spectrometry (MS), together with adjacent normal tissue samples.

Results: Lipid peaks differentially expressed between cancer and normal samples at a feature selection P<0.001 correctly predicted class labels of test set samples (7 pairs) in 100 random training-to-test partitions, at the median class prediction accuracy of 100%. In addition, lipid peaks differentially expressed between 14 pairs of cancer and adjacent normal samples correctly predicted 100% of validation set samples (8 out of 8 samples). Phosphatidylcholines (PC) 32:0 and PC 34:1, sphingomyelin 34:1, and several phosphatidylinositols were overexpressed, while lysophosphatidylcholine 18:3 and lysophosphatidylserine 18:1 were underexpressed in papillary thyroid carcinomas, compared with normal tissue.

Conclusions: Lipid MALDI MS profiles accurately distinguish papillary thyroid carcinoma epithelium from normal epithelium, and demonstrate the potential as a diagnostic aid.