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Analysis of differential protein expression in large and small neoplastic islands by mass spectrometry-based proteomics and its relationship with prognosis

Grant number: 14/02288-4
Support type:Scholarships in Brazil - Master
Effective date (Start): May 01, 2014
Effective date (End): July 31, 2015
Field of knowledge:Health Sciences - Dentistry
Principal Investigator:Adriana Franco Paes Leme
Grantee:Carolina Carneiro Soares Macedo
Home Institution: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM). Ministério da Ciência, Tecnologia, Inovações e Comunicações (Brasil). Campinas , SP, Brazil

Abstract

Oral squamous cell carcinoma (OSCC) is the most common type of malignancy in the head and neck, with high prevalence and morbidity. The treatment is based on classification systems not very accurate and prognosis remains poor in many cases. Different clinical and histological patterns have been described in an attempt to better understand the disease course. For example, different areas of the tumor show morphological and molecular distinct characteristics, and recent studies point to the region of tumor invasion, the English tumor invasion front, as an area of interest for analysis of molecular profiling and identification of potential prognostic markers. The objective of this study is to analyze and compare the differential composition of total proteins of large and small neoplastic islands of front and inside of the tumor, and these proteins correlate with prognosis. Proteomics will be used for the study purpose associated with laser microdissection (LM), considered together as high robustness tools to identify proteins in neoplastic tissues in specific regions of interest. Surgical specimens of oral SCC fixed paraffin will undergo ML to obtain the samples composed of the following areas of tissue: 1) large and small neoplastic islands of the frontal region and 2) large and small neoplastic islands of the inside the tumor, followed by extraction of proteins, and the analysis by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Data will be analyzed by bioinformatics to functional annotation of proteins with correlation to clinic pathological data of the patients. Validation of differentially expressed proteins will be performed by tissue microarray (TMA), as functional migration and invasion assays are also performed. Thus, it is expected that the combination of ML, MS, bioinformatics and functional assays to identify a panel of proteins that help to unravel the course of oral SCC, predicting aggressiveness and prognosis. This approach may also help to understand the mechanisms of interaction between the tumor and normal tissue and create new therapeutic targets. (AU)

Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
MACEDO, Carolina Carneiro Soares. . 2015. Master's Dissertation - Universidade Estadual de Campinas. Faculdade de Odontologia de Piracicaba.

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