Differentially expressed proteins in positive versus negative HNSCC lymph nodes

Carregando...
Imagem de Miniatura

Data

2018-08-29

Autores

Vidotto, Alessandra
Polachini, Giovana M.
De Paula-Silva, Marina [UNESP]
Oliani, Sonia M. [UNESP]
Henrique, Tiago
López, Rossana V. M.
Cury, Patrícia M.
Nunes, Fabio D.
Góis-Filho, José F.
De Carvalho, Marcos B.

Título da Revista

ISSN da Revista

Título de Volume

Editor

Resumo

Background: Lymph node metastasis is one of the most important prognostic factors in head and neck squamous cell carcinomas (HNSCCs) and critical for delineating their treatment. However, clinical and histological criteria for the diagnosis of nodal status remain limited. In the present study, we aimed to characterize the proteomic profile of lymph node metastasis from HNSCC patients. Methods: In the present study, we used one- and two-dimensional electrophoresis and mass spectrometry analysis to characterize the proteomic profile of lymph node metastasis from HNSCC. Results: Comparison of metastatic and non-metastatic lymph nodes showed 52 differentially expressed proteins associated with neoplastic development and progression. The results reinforced the idea that tumors from different anatomical subsites have dissimilar behaviors, which may be influenced by micro-environmental factor including the lymphatic network. The expression pattern of heat shock proteins and glycolytic enzymes also suggested an effect of the lymph node environment in controlling tumor growth or in metabolic reprogramming of the metastatic cell. Our study, for the first time, provided direct evidence of annexin A1 overexpression in lymph node metastasis of head and neck cancer, adding information that may be useful for diagnosing aggressive disease. Conclusions: In brief, this study contributed to our understanding of the metastatic phenotype of HNSCC and provided potential targets for diagnostic in this group of carcinomas.

Descrição

Palavras-chave

Head and neck carcinoma, Lymph node, Metastasis, Proteomics

Como citar

BMC Medical Genomics, v. 11, n. 1, 2018.