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

• Published in: Nature communications Vol. 9; no. 1; pp. 3598 - 17
• Main Authors: Carnielli, Carolina Moretto, Macedo, Carolina Carneiro Soares, De Rossi, Tatiane, Granato, Daniela Campos, Rivera, César, Domingues, Romênia Ramos, Pauletti, Bianca Alves, Yokoo, Sami, Heberle, Henry, Busso-Lopes, Ariane Fidelis, Cervigne, Nilva Karla, Sawazaki-Calone, Iris, Meirelles, Gabriela Vaz, Marchi, Fábio Albuquerque, Telles, Guilherme Pimentel, Minghim, Rosane, Ribeiro, Ana Carolina Prado, Brandão, Thaís Bianca, de Castro, Jr, Gilberto, González-Arriagada, Wilfredo Alejandro, Gomes, Alexandre, Penteado, Fabio, Santos-Silva, Alan Roger, Lopes, Márcio Ajudarte, Rodrigues, Priscila Campioni, Sundquist, Elias, Salo, Tuula, da Silva, Sabrina Daniela, Alaoui-Jamali, Moulay A, Graner, Edgard, Fox, Jay W, Coletta, Ricardo Della, Paes Leme, Adriana Franco
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 05.09.2018; Nature Publishing Group UK; Nature Portfolio
• Subjects: Biomarkers; Biomarkers, Tumor - analysis; Cancer; Carcinoma, Squamous Cell - diagnosis; Carcinoma, Squamous Cell - mortality; Carcinoma, Squamous Cell - pathology; Classification; Clinical Decision-Making; Cystatins; Female; Follow-Up Studies; Histopathology; Humans; Immunohistochemistry; Invasiveness; Islands; Learning algorithms; Lymph nodes; Lymphatic Metastasis; Lymphatic system; Machine Learning; Male; Medical prognosis; Metastases; Metastasis; Middle Aged; Mouth Neoplasms - diagnosis; Mouth Neoplasms - mortality; Mouth Neoplasms - pathology; Neoplasm Recurrence, Local - diagnosis; Neoplasm Recurrence, Local - prevention & control; Nodes; Oral cancer; Oral squamous cell carcinoma; Patients; Peptides; Peptides - analysis; Predictive Value of Tests; Prognosis; Proteins; Proteomics; Proteomics - methods; Retrospective Studies; Saliva; Saliva - chemistry; Squamous cell carcinoma; Stroma; Survival Rate; Tumors
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-018-05696-2

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.