Abstract
Introduction. Early diagnosis of Oral Squamous Cell Carcinoma (OSCC) increases the survival rate of oral cancer. For early diagnosis, molecular biomarkers contained in samples collected non-invasively and directly from at-risk oral premalignant lesions (OPMLs) would be ideal. Methods. In this pilot study we evaluated the potential of a novel method using commercial PerioPaper absorbent strips for non-invasive collection of oral lesion exudate material coupled with mass spectrometry-based proteomics for oral cancer biomarker discovery. Results: Our evaluation focused on three core issues. First, using an "on-strip" processing method, we found that protein can be isolated from exudate samples in amounts compatible with large-scale mass spectrometry-based proteomic analysis. Second, we found that the OPML exudate proteome was distinct from that of whole saliva, while being similar to the OPML epithelial cell proteome, demonstrating the fidelity of our exudate collection method. Third, in a proof-of-principle study, we identified numerous, inflammation-associated proteins showing an expected increase in abundance in OPML exudates compared to healthy oral tissue exudates. These results demonstrate the feasibility of identifying differentially abundant proteins from exudate samples, which is essential for biomarker discovery studies. Conclusions: Collectively, our findings demonstrate that our exudate collection method coupled with mass spectrometry-based proteomics has great potential for transforming OSCC biomarker discovery and clinical diagnostics assay development.
Original language | English (US) |
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Article number | 13 |
Journal | Clinical Proteomics |
Volume | 8 |
Issue number | 1 |
DOIs | |
State | Published - 2011 |
Bibliographical note
Funding Information:This work was supported in part by NIH grant R01DE017734 and through an NIH Training Grant Fellowship T32GM008347 to J.A.K. We also thank the Center for Mass Spectrometry and Proteomics at the University of Minnesota for instrumental resources and the Minnesota Supercomputing Institute for computational support.
Keywords
- Oral Pre-Malignant Lesion (OPML)
- Oral Squamous Cell Carcinoma (OSCC)
- biomarker
- exudate
- mass spectrometry-based proteomics