Connecting multiple microenvironment proteomes uncovers the biology in head and neck cancer

Ariane F. Busso-Lopes, Leandro X. Neves, Guilherme A. Câmara, Daniela C. Granato, Marco Antônio M. Pretti, Henry Heberle, Fábio M.S. Patroni, Jamile Sá, Sami Yokoo, César Rivera, Romênia R. Domingues, Ana Gabriela C. Normando, Tatiane De Rossi, Barbara P. Mello, Nayane A.L. Galdino, Bianca A. Pauletti, Pammela A. Lacerda, André Afonso N. Rodrigues, André Luis M. Casarim, Reydson A. de Lima-SouzaIngrid I. Damas, Fernanda V. Mariano, Kenneth J. Gollob, Tiago S. 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 F. Paes Leme*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

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.

Original languageEnglish
Article number6725
Pages (from-to)1-24
Number of pages24
JournalNature Communications
Volume13
Issue number1
Early online date7 Nov 2022
DOIs
StatePublished - Dec 2022

Bibliographical note

Publisher Copyright:
© 2022, The Author(s).

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