Quantitative proteomic analysis for novel biomarkers of buccal squamous cell carcinoma arising in background of oral submucous fibrosis
Autor: | Ning Li, Shanshan Zhang, Lijuan Zeng, Changyun Fang, Canhua Jiang, Xinqun Chen, Feng Guo, Wen Liu, Chunjiao Xu, Fei Wang, Tong Su |
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Rok vydání: | 2015 |
Předmět: |
0301 basic medicine
Adult Male Proteomics Pathology medicine.medical_specialty Cancer Research Asia Filamins Quantitative proteomics Oral Submucous Fibrosis Southeast asian 03 medical and health sciences 0302 clinical medicine Buccal squamous cell carcinoma Tandem Mass Spectrometry medicine Genetics FLNA Humans Filamin-A Protein Interaction Maps Annexin A4 Proportional Hazards Models Mouth neoplasm business.industry Proportional hazards model Hazard ratio Middle Aged medicine.disease Prognosis Survival Analysis Up-Regulation Gene Expression Regulation Neoplastic 030104 developmental biology Oral submucous fibrosis Oncology Quantitative proteomic analysis 030220 oncology & carcinogenesis Carcinoma Squamous Cell Female Mouth Neoplasms business Biomarkers Research Article |
Zdroj: | BMC Cancer |
ISSN: | 1471-2407 |
Popis: | Background In South and Southeast Asian, the majority of buccal squamous cell carcinoma (BSCC) can arise from oral submucous fibrosis (OSF). BSCCs develop in OSF that are often not completely resected, causing local relapse. The aim of our study was to find candidate protein biomarkers to detect OSF and predict prognosis in BSCCs by quantitative proteomics approaches. Methods We compared normal oral mucosa (NBM) and paired biopsies of BSCC and OSF by quantitative proteomics using isobaric tags for relative and absolute quantification (iTRAQ) to discover proteins with differential expression. Gene Ontology and KEGG networks were analyzed. The prognostic value of biomarkers was evaluated in 94 BSCCs accompanied with OSF. Significant associations were assessed by Kaplan-Meier survival and Cox-proportional hazards analysis. Results In total 30 proteins were identified with significantly different expression (false discovery rate |
Databáze: | OpenAIRE |
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