The Use of Principal Component Analysis in MALDI-TOF MS - a Powerful Tool for Establishing a Mini-optimized Proteomic Profile

Abstract

BACKGROUND: Recently, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) technology has been applied to the exploration of biomarkers for early cancer diagnosis, but more effort is required to identify a single sensitive and specific biomarker. For early diagnosis, a proteomic profile is the gold standard, but inconvenient for clinical use since the profile peaks are quantitative. It would therefore be helpful to find a minimized profile, comprising fewer peaks than the original using an existing algorithm and compare it with other traditional statistical methods. METHODS: In the present study, principal component analysis (PCA) in the ClinProt-Tools of MALDI-TOF MS was used to establish a mini-optimized proteomic profile from gastric cancer patients and healthy controls, and the result was compared with t-test and Flexanalysis software. RESULTS: Eight peaks were selected as the mini-optimized proteomic profile to help differentiate between gastric cancer patients and healthy controls. The peaks at m/z 4212 were regarded as the most important peak by the PCA algorithm. The peaks at m/z 1866 and 2863 were identified as deriving from complement component C3 and apolipoprotein A1, respectively. CONCLUSIONS: PCA enabled us to identify a mini-optimized profile consisting of significantly differentiating peaks and offered the clue for further research.