Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery
Graphical abstract
Introduction
Oral cancer is the most common neoplasm of the head and neck. It may emerge as a primary lesion originating from any of the oral tissues, and can be of varied histologic types. About 90% of these malignancies are oral squamous cell carcinomas (OSCC). Approximately, 42,000 Americans are diagnosed each year with this largely preventable cancer [1], [2], [3]. Oral cancer is a major and growing problem in many parts of the globe where tobacco and alcohol are established major etiologic agents of these cancers. In addition, micronutrient deficiencies and poor oral hygiene have also been linked to increased risk [3]. In recent years, human papilloma virus (HPV) has been increasingly associated with tonsilla and pharyngeal cancers where the affected individuals are often younger and have very different risk factors [4].
Patients with oral cancer often present with symptoms at a late stage, and there is a high recurrence rate after treatment, especially in those with neck lymph node metastasis [1], [2]. The delayed detection is likely a primary reason for the high morbidity and mortality rate of oral cancer patients. Meanwhile, diagnosing oral cancer at an early stage could significantly increase the 5-year survival rates [3]. Because oral cancer can spread quickly, screening of high-risk populations represents a promising way to reduce cancer incidence and mortality. As the occurrence of oral cancer rise (due to increased tobacco and alcohol abuse, and increased longevity), the need for effective early detection technologies and discriminatory biomarkers becomes more urgent [3], [5]. The ideal approach for early detection should be easily performed in an out-patient set-up, which is practical and non-invasive, such as brush biopsy, tissue autofluorescence, and salivary diagnostics [6].
Serum and biopsy tissue samples have long been applied to develop mRNA, microRNA and protein biomarkers [7] for the detection of oral cancer. Different quantitative proteomics technologies have been successfully engaged in oral cancer biomarker discovery, like two-dimensional gel electrophoresis [8] and isobaric tags for relative and absolute quantitation (iTRAQ) [9]. Although some work has been done in oral cancer biomarker discovery, however, it is still very challenging to predict which oral diseases (such as erythroplakia, leukoplakia, lichenoid and other potentially malignant mucosal) will progress to neoplasia – notably OSCC [10]. Especially, it is of profound significance to discover unique biomarkers that allow identification of high-risk oral lesions [11]. The capability to differentiate epithelial dysplasia from normal and malignant epithelial might also improve the specificity of early detection [12].
The objective of this study was to discover specific biomarkers for the detection of oral cancer. Through coupling cutting edge technologies with our unique study design, we have comprehensively analyzed the proteomics changes among morphologically malignant, epithelial dysplasia, and adjacent normal oral epithelial cells. LCM was utilized to accurately procure the specific oral epithelial cell types. Quantitative proteomics engaging iTRAQ technology were used for the biomarker discovery by comparing all the samples, simultaneously. Through quantitative analysis of oral epithelium at different stages, the progression of oral cancer was systematically discovered by analyzing the identified proteins. Potential biomarkers were selected and further pre-validated in tissue microarray and human saliva. Their utility for the detection of oral cancer was also evaluated.
Section snippets
Analytical strategy for proteomic biomarker discovery
This study consisted of two phases. In the discovery phase, adjacent normal, epithelial dysplasia and malignant oral epithelium tissues from 19 oral cancer patients were procured by LCM (Table S1A and B). The proteins in these tissue cell samples were extracted and then digested with trypsin. The extracted peptides were labelled with iTRAQ 8-plex reagents. Follow the schematic of experimental design (Fig. 1), these labelled peptides from each sample were mixed, and fractionated into 20
Identification of differentially expressed proteins in malignant, dysplasia and adjacent normal oral epithelium
We used iTRAQ 8-plex to delineate the profiles of differentially expressed proteins in oral epithelium. In total, 500 proteins were identified from 2118 unique peptide sequences and 425 of them were quantified (Supplementary Table S2).
The distribution of quantified proteins in different types of oral epithelium is presented in Supplemental Fig. S1. Based on the criteria of minimum 20% change, 173 and 119 proteins were up-regulated in the malignant group and epithelial dysplasia group,
Discussion
Through utilizing iTRAQ, 425 proteins were quantitatively identified from the oral epithelium in the present study. We found that 17 proteins were consistently down-regulated in epithelial dysplasia and oral cancer, respectively, while 15 proteins were consistently up-regulated. It is worth mentioning that these consistently changed proteins in epithelial dysplasia and cancer pertain to the mechanisms that behind the progression of oral cancer. Excitingly, half of these proteins (Table 1
Conflict of Interest Statement
D.T.W.W. is the co-founder of RNAmeTRIX. However RNAmeTRIX is a virtual company and currently has no income nor employs anyone. It does not fund the research at all. If pertinent, this does not alter our adherence to all the Oral Oncology policies on sharing data and materials. Other authors disclosed no potential conflict of interests.
Acknowledgements
We thank David Akin for assistance in the clinical sample collection, processing, and storage. This work is supported by the University of California Tobacco Research Related Research Program (TRDRP, 20PT-0032) and DOD Lung Cancer Research Program (LC110207). D.T.W.W. is also supported by the Felix & Mildred Yip Endowed Professorship. H.X. is supported by The Recruitment Program of Global Youth Experts of China, NSFC (No. 21305087), National High-tech R&D Program of China (863 Program, No.
References (32)
- et al.
Molecular screening of oral precancer
Oral Oncol
(2013) - et al.
Angiogenic heterogeneity in head and neck squamous cell carcinoma: biological and therapeutic implications
Lab Invest
(2008) - et al.
2D-DIGE proteomic characterization of head and neck squamous cell carcinoma
Otolaryngol Head Neck Surg
(2009) - et al.
Expression and functional regulation of myoglobin in epithelial cancers
Am J Pathol
(2009) - et al.
Tenascin and beta 6 integrin are overexpressed in floor of mouth in situ carcinomas and invasive squamous cell carcinomas
Oral Oncol
(2002) - et al.
Epistasis of oxidative stress-related enzyme genes on modulating the risks in oral cavity cancer
Clin Chim Acta
(2010) - et al.
Tissue expression of gelsolin in oral carcinogenesis progression and its clinicopathological implications
Oral Oncol
(2006) - et al.
Cancer Statistics, 2015
CA Cancer J Clin
(2015) - et al.
Molecular markers of the risk of oral cancer
N Engl J Med
(2001) - et al.
Salivary proteomics for oral cancer biomarker discovery
Clin Cancer Res
(2008)
Screening for oral premalignancy and cancer: what platform and which biomarkers?
Cancer Prev Res (Phila Pa)
Human body fluid proteome analysis
Proteomics
Evaluating the potential of a novel oral lesion exudate collection method coupled with mass spectrometry-based proteomics for oral cancer biomarker discovery
Clin Proteomics
Proteomic analysis of laser-captured paraffin-embedded tissues: a molecular portrait of head and neck cancer progression
Clin Cancer Res
Proteomic analysis of human papillomavirus-related oral squamous cell carcinoma: identification of thioredoxin and epidermal-fatty acid binding protein as upregulated protein markers in microdissected tumor tissue
Proteomics
ITRAQ-multidimensional liquid chromatography and tandem mass spectrometry-based identification of potential biomarkers of oral epithelial dysplasia and novel networks between inflammation and premalignancy
J Proteome Res
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These authors contributed equally as first authors to this work.