title: Quantification of Serum Proteins of Metastatic Oral Cancer Patients Using LC-MS/MS and iTRAQ Labeling.
abstract: Metastasis is a critical event in oral squamous cell carcinoma (OSCC) progression. In this study, we have performed quantitative analysis of serum proteins from non-metastatic (lymph-node metastasis free) and metastatic OSCC patients using liquid chromatography-tandem mass spectrometry (LC-MS/MS) with iTRAQ labeling (isobaric tagging for relative and absolute quantitation). To eliminate highly abundant proteins, the serum samples were initially separated by SDS-PAGE and only low abundant protein bands were excised for subsequent in-gel tryptic digestion. The resulting peptides were then extracted from each sample gels and labeled with iTRAQ reagent 114 (control), 116 (non-metastatic) and 117 (metastatic), respectively. Afterwards, the labeled samples were combined and subjected to LC-MS/MS analysis using linear ion trap (LIT) MS with pulsed Q collision induced dissociation (PQD). A total of 64 proteins were identified and quantified by this approach. Our study showed that iTRAQ labeling and LIT-MS with PQD is a valuable approach to quantification of serum proteins. We also demonstrated the presence of differentially expressed serum proteins between non-metastatic and metastatic OSCCs that may be further validated as biomarkers for metastatic OSCC. However, in order to comprehensively quantify low abundant serum proteins, a more efficient approach is needed to deplete highly abundant proteins prior to quantitative serum proteome analysis of OSCC.
authors.affiliation: School of Dentistry and Dental Research Institute, University of California, Los Angeles CA 90095, USA.
authors.forename: Lifeng
authors.initials: L
authors.lastname: Zhang
authors.forename: Jiang
authors.initials: J
authors.lastname: Jiang
authors.forename: Martha
authors.initials: M
authors.lastname: Arellano
authors.forename: Lei
authors.initials: L
authors.lastname: Zhang
authors.forename: Xinmin
authors.initials: X
authors.lastname: Yan
authors.forename: David T
authors.initials: DT
authors.lastname: Wong
authors.forename: Shen
authors.initials: S
authors.lastname: Hu