MALDI-TOF-MS analysis in discovery and identification of serum proteomic patterns of ovarian cancer

BMC Cancer

Research Article

Agata Swiatly¹  Joanna Hajduk¹  Jan Matysiak¹  Zenon J. Kokot¹  Agnieszka Horala²  Ewa Nowak-Markwitz² 

[1] Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, ul. Grunwaldzka 6, 60-780, Poznań, Poland;Gynecologic Oncology Department, Poznan University of Medical Sciences, ul. Polna 33, 60-535, Poznań, Poland;

关键词: Epithelial ovarian cancer;    Ovarian cancer;    Biomarkers;    MALDI-TOF;    Protein-peptide profiling;   

DOI  :  10.1186/s12885-017-3467-2

 received in 2016-10-26, accepted in 2017-06-30,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundDue to high mortality and lack of efficient screening, new tools for ovarian cancer (OC) diagnosis are urgently needed. To broaden the knowledge on the pathological processes that occur during ovarian cancer tumorigenesis, protein-peptide profiling was proposed.MethodsSerum proteomic patterns in samples from OC patients were obtained using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF). Eighty nine serum samples (44 ovarian cancer and 45 healthy controls) were pretreated using solid-phase extraction method. Next, a classification model with the most discriminative factors was identified using chemometric algorithms. Finally, the results were verified by external validation on an independent test set of samples.ResultsMain outcome of this study was an identification of potential OC biomarkers by applying liquid chromatography coupled with tandem mass spectrometry. Application of this novel strategy enabled the identification of four potential OC serum biomarkers (complement C3, kininogen-1, inter-alpha-trypsin inhibitor heavy chain H4, and transthyretin). The role of these proteins was discussed in relation to OC pathomechanism.ConclusionsThe study results may contribute to the development of clinically useful multi-component diagnostic tools in OC. In addition, identifying a novel panel of discriminative proteins could provide a new insight into complex signaling and functional networks associated with this multifactorial disease.

【 授权许可】

CC BY   
© The Author(s). 2017