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

Bohnenberger, H.; Kaderali, L.; Ströbel, P.; Yepes, D.; Pleßmann, U.; Dharia, N. Y.; Yao, S.; Heydt, C.; Merkelbach‐Bruse, S.; Emmert, A.; Hoffmann, J.; Bodemeyer, J.; Reuter‐Jessen, K.; Lois, A. M.; Dröge, L. H.; Baumeister, P.; Walz, C.; Biggemann, L.; Walter, R.; Häupl, B.; Comoglio, F.; Pan, K. T.; Scheich, S.; Lenz, C.; Küffer, S.; Bremmer, F.; Kitz, J.; Sitte, M.; Beißbarth, T.; Hinterthaner, M.; Sebastian, M.; Lotz, J.; Schildhaus, H. U.; Wolff, H.; Danner, B. C; Brandts, C.; Büttner, R.; Canis, M.; Stegmaier, K.; Serve, H.; Urlaub, H.; Oellerich, T.

doi:10.15252/emmm.201708428

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

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Pleßmann, U.
Research Group of Bioanalytical Mass Spectrometry, MPI for biophysical chemistry, Max Planck Society;

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Pan, K. T.
Research Group of Bioanalytical Mass Spectrometry, MPI for biophysical chemistry, Max Planck Society;

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Urlaub, H.
Research Group of Bioanalytical Mass Spectrometry, MPI for biophysical chemistry, Max Planck Society;

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Zitation

Bohnenberger, H., Kaderali, L., Ströbel, P., Yepes, D., Pleßmann, U., Dharia, N. Y., et al. (2018). Comparative proteomics reveals a diagnostic signature for pulmonary head-and-neck cancer metastasis. EMBO Molecular Medicine, 10(9): e8428. doi:10.15252/emmm.201708428.

Zitierlink: https://hdl.handle.net/21.11116/0000-0001-EC10-3

Zusammenfassung

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.