Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer

Carolina Moretto Carnielli, Carolina Carneiro Soares Macedo, Tatiane De Rossi, Daniela Campos Granato, César Rivera, Romênia Ramos Domingues, Bianca Alves Pauletti, Sami Yokoo, Henry Heberle, Ariane Fidelis Busso-Lopes, Nilva Karla Cervigne, Iris Sawazaki-Calone, Gabriela Vaz Meirelles, Fábio Albuquerque Marchi, Guilherme Pimentel Telles, Rosane Minghim, Ana Carolina Prado Ribeiro, Thaís Bianca Brandão, Gilberto Castro, Wilfredo Alejandro González-Arriagada, Alexandre Gomes, Fabio Penteado, Alan Roger Santos-Silva, Márcio Ajudarte Lopes, Priscila Campioni Rodrigues, Elias Sundquist, Tuula Salo, Sabrina Daniela Silva, Moulay A. Alaoui-Jamali, Edgard Graner, Jay W. Fox, Ricardo Della Coletta and Adriana Franco Paes Leme ()
Additional contact information
Carolina Moretto Carnielli: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM)
Carolina Carneiro Soares Macedo: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM)
Tatiane De Rossi: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM)
Daniela Campos Granato: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM)
César Rivera: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM)
Romênia Ramos Domingues: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM)
Bianca Alves Pauletti: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM)
Sami Yokoo: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM)
Henry Heberle: Universidade de São Paulo (USP)
Ariane Fidelis Busso-Lopes: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM)
Nilva Karla Cervigne: Faculdade de Odontologia de Piracicaba Universidade Estadual de Campinas (UNICAMP)
Iris Sawazaki-Calone: Universidade Estadual do Oeste do Paraná
Gabriela Vaz Meirelles: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM)
Fábio Albuquerque Marchi: Centro Internacional de Pesquisa-CIPE - A.C.Camargo Cancer Center and Instituto Nacional de Ciência e Tecnologia em Oncogenômica (INCiTO)
Guilherme Pimentel Telles: Instituto de Computação, Universidade Estadual de Campinas (UNICAMP)
Rosane Minghim: Universidade de São Paulo (USP)
Ana Carolina Prado Ribeiro: Instituto do Câncer do Estado de São Paulo, ICESP-FMUSP
Thaís Bianca Brandão: Instituto do Câncer do Estado de São Paulo, ICESP-FMUSP
Gilberto Castro: Instituto do Câncer do Estado de São Paulo, Octavio Frias de Oliveira, ICESP
Wilfredo Alejandro González-Arriagada: Universidad de Valparaíso
Alexandre Gomes: Waters Corporation
Fabio Penteado: Waters Corporation
Alan Roger Santos-Silva: Faculdade de Odontologia de Piracicaba Universidade Estadual de Campinas (UNICAMP)
Márcio Ajudarte Lopes: Faculdade de Odontologia de Piracicaba Universidade Estadual de Campinas (UNICAMP)
Priscila Campioni Rodrigues: University of Oulu
Elias Sundquist: University of Oulu
Tuula Salo: University of Oulu
Sabrina Daniela Silva: McGill University
Moulay A. Alaoui-Jamali: McGill University
Edgard Graner: Faculdade de Odontologia de Piracicaba Universidade Estadual de Campinas (UNICAMP)
Jay W. Fox: University of Virginia
Ricardo Della Coletta: Faculdade de Odontologia de Piracicaba Universidade Estadual de Campinas (UNICAMP)
Adriana Franco Paes Leme: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM)

Nature Communications, 2018, vol. 9, issue 1, 1-17

Abstract: Abstract Different regions of oral squamous cell carcinoma (OSCC) have particular histopathological and molecular characteristics limiting the standard tumor−node−metastasis prognosis classification. Therefore, defining biological signatures that allow assessing the prognostic outcomes for OSCC patients would be of great clinical significance. Using histopathology-guided discovery proteomics, we analyze neoplastic islands and stroma from the invasive tumor front (ITF) and inner tumor to identify differentially expressed proteins. Potential signature proteins are prioritized and further investigated by immunohistochemistry (IHC) and targeted proteomics. IHC indicates low expression of cystatin-B in neoplastic islands from the ITF as an independent marker for local recurrence. Targeted proteomics analysis of the prioritized proteins in saliva, combined with machine-learning methods, highlights a peptide-based signature as the most powerful predictor to distinguish patients with and without lymph node metastasis. In summary, we identify a robust signature, which may enhance prognostic decisions in OSCC and better guide treatment to reduce tumor recurrence or lymph node metastasis.

Date: 2018
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DOI: 10.1038/s41467-018-05696-2

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