Connecting multiple microenvironment proteomes uncovers the biology in head and neck cancer
Ariane F. Busso‐Lopes, Leandro Xavier Neves, Guilherme A. Câmara, Daniela C. Granato, Marco Antônio M. Pretti, Henry Heberle, Fábio Malta de Sá Patroni, JAMILE DE OLIVEIRA SÁ, Sami Yokoo, César Rivera, Romênia R. Domingues, Ana Gabriela Costa Normando, Tatiane De Rossi, Barbara P. Mello, Nayane A. L. Galdino, Bianca Alves Pauletti, Pammela A. Lacerda, André Afonso Nimtz Rodrigues, André Luís Maion Casarim, Reydson Alcides de Lima‐Souza, Ingrid Iara Damas, Fernanda Viviane Mariano, Kenneth J. Gollob, Tiago da Silva Medina, Nilva K. Cervigne, Ana Carolina Prado Ribeiro, Thaís Bianca Brandão, Luisa L. Villa, Miyuki Uno, Mariana Boroni, Luiz Paulo Kowalski, Wilfredo Alejandro González‐Arriagada, Adriana Franco Paes Leme
Abstract
The poor prognosis of head and neck cancer (HNC) is associated with metastasis within the lymph nodes (LNs). Herein, the proteome of 140 multisite samples from a 59-HNC patient cohort, including primary and matched LN-negative or -positive tissues, saliva, and blood cells, reveals insights into the biology and potential metastasis biomarkers that may assist in clinical decision-making. Protein profiles are strictly associated with immune modulation across datasets, and this provides the basis for investigating immune markers associated with metastasis. The proteome of LN metastatic cells recapitulates the proteome of the primary tumor sites. Conversely, the LN microenvironment proteome highlights the candidate prognostic markers. By integrating prioritized peptide, protein, and transcript levels with machine learning models, we identify nodal metastasis signatures in blood and saliva. We present a proteomic characterization wiring multiple sites in HNC, thus providing a promising basis for understanding tumoral biology and identifying metastasis-associated signatures.