Journal Article

Comparative proteomics reveals a diagnostic signature for pulmonary head‐and‐neck cancer metastasis

Yepes, Diego, Baumeister, Philipp, Canis, Martin, Brandts, Christian, Bohnenberger, Hanibal, Häupl, Björn, Lenz, Christof, Urlaub, Henning, Bodemeyer, Julius, Oellerich, Thomas, Pan, Kuan‐Ting, Walz, Christoph, Stegmaier, Kimberly, Hinterthaner, Marc, Walter, Roland, Bremmer, Felix, Emmert, Alexander, Beißbarth, Tim, Lotz, Joachim, Yao, Sha, Danner, Bernhard C, Dröge, Leif Hendrik, Schildhaus, Hans‐Ulrich, Ströbel, Philipp, Dharia, Neekesh V, Hoffmann, Jonatan, Kaderali, Lars, Kitz, Julia, Plessmann, Uwe, Comoglio, Federico, Sebastian, Martin, Serve, Hubert, Büttner, Reinhard, Merkelbach‐Bruse, Sabine, Scheich, Sebastian, Sitte, Maren, Wolff, Hendrik, Biggemann, Lorenz, Lois, Anna‐Maria, Reuter‐Jessen, Kirsten, Heydt, Carina, Küffer, Stefan

2018

Overview

Patients with head‐and‐neck cancer can develop both lung metastasis and primary lung cancer during the course of their disease. Despite the clinical importance of discrimination, reliable diagnostic biomarkers are still lacking. Here, we have characterised a cohort of squamous cell lung (SQCLC) and head‐and‐neck (HNSCC) carcinomas by quantitative proteomics. In a training cohort, we quantified 4,957 proteins in 44 SQCLC and 30 HNSCC tumours. A total of 518 proteins were found to be differentially expressed between SQCLC and HNSCC, and some of these were identified as genetic dependencies in either of the two tumour types. Using supervised machine learning, we inferred a proteomic signature for the classification of squamous cell carcinomas as either SQCLC or HNSCC, with diagnostic accuracies of 90.5% and 86.8% in cross‐ and independent validations, respectively. Furthermore, application of this signature to a cohort of pulmonary squamous cell carcinomas of unknown origin leads to a significant prognostic separation. This study not only provides a diagnostic proteomic signature for classification of secondary lung tumours in HNSCC patients, but also represents a proteomic resource for HNSCC and SQCLC. Synopsis Differentiation between head‐and‐neck cancer metastasis and primary lung cancer is clinically important for therapy selection. A novel diagnostic proteomic signature allows differentiation between these tumour types, and a proteomic resource for squamous cell tumours is here provided. The protein expression profiles of 63 squamous cell lung and 49 head‐and‐neck tumours were analysed by quantitative mass spectrometry yielding a proteomic resource covering 6,214 quantified proteins. 518 proteins were found to be differentially expressed between squamous cell lung and head‐and‐neck cancers which are known to share genomic and morphological features. A diagnostic proteomic signature for differentiation between primary squamous cell lung cancers and head‐and‐neck cancer metastases was identified by quantitative mass‐spectrometry‐based proteomics and validated in independent patient cohorts. Graphical Abstract Differentiation between head‐and‐neck cancer metastasis and primary lung cancer is clinically important for therapy selection. A novel diagnostic proteomic signature allows differentiation between these tumour types, and a proteomic resource for squamous cell tumours is here provided.

• Publisher: Nature Publishing Group UK,EMBO Press,John Wiley and Sons Inc,Springer Nature
• Subject: Biomarker / Carcinoma, Squamous Cell - diagnosis / Carcinoma, Squamous Cell - pathology / Carcinoma, Squamous Cell - secondary / Diagnostic Tests, Routine - methods / EMBO03 / EMBO31 / Head / Head & neck cancer / Head and Neck Neoplasms - diagnosis / Head and Neck Neoplasms - pathology / Head and Neck Neoplasms - secondary / head‐and‐neck cancer / Humans / Learning algorithms / Lung cancer / Lung Neoplasms - diagnosis / Lung Neoplasms - pathology / Machine Learning / Mass spectroscopy / Metastases / Metastasis / Neck / Proteins / Proteome - analysis / Proteomics / Proteomics - methods / Research Article / Scientific imaging / Sensitivity and Specificity / Squamous cell carcinoma / Tumors