ArticleData in brief2018
Identification of potential biomarkers of head and neck squamous cell carcinoma using iTRAQ based quantitative proteomic approach.
Article in Data in brief, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Exploration of a predictive model based on genes associated with fatty acid metabolism and clinical treatment for head and neck squamous cell carcinoma.Journal of clinical laboratory analysis · 2022Article
- iTRAQ-Based Quantitative Proteomics Indicated Nrf2/OPTN-Mediated Mitophagy Inhibits NLRP3 Inflammasome Activation after Intracerebral Hemorrhage.Oxidative medicine and cellular longevity · 2021Article
- Quantitative proteomics identifies a plasma multi-protein model for detection of hepatocellular carcinoma.Scientific reports · 2020Article
- Secretome analysis of oral keratinocytes chronically exposed to shisha.Cancer biomarkers : section A of Disease markers · 2019Article
Corrections and comments
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Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers in India. Despite improvements in treatment strategy, the survival rates of HNSCC patients remain poor. Thus, it is necessary to identify biomarkers that can be used for early detection of disease. In this study, we employed iTRAQ-based quantitative mass spectrometry analysis to identify dysregulated proteins from a panel of head and neck squamous cell carcinoma (HNSCC) cell lines. We identified 2468 proteins, of which 496 proteins were found to be dysregulated in at least two out of three HNSCC cell lines compared to immortalized normal oral keratinocytes. We detected increased expression of replication protein A1 (RPA1) and heat shock protein family H (Hsp110) member 1 (HSPH1), in HNSCC cell lines compared to control. The differentially expressed proteins were further validated using parallel reaction monitoring (PRM) and western blot analysis in HNSCC cell lines. Immunohistochemistry-based validation using HNSCC tissue microarrays revealed overexpression of RPA1 and HSPH1 in 15.7% and 32.2% of the tested cases, respectively. Our study illustrates quantitative proteomics as a robust approach for identification of potential HNSCC biomarkers. The proteomic data has been submitted to ProteomeXchange Consortium (http://www.proteomecentral.proteomexchange.org) via the PRIDE public data repository accessible using the data identifier - PXD009241.
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