English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse
  1. View item / 
  2. Item Summary

Item

ITEM ACTIONSEXPORT
Add to Basket
  Local TagsRelease HistoryDetailsSummary

Released
Journal Article

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

MPS-Authors
/persons/resource/persons15649

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

/persons/resource/persons185577

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

/persons/resource/persons15947

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

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

2632281.pdf
(Publisher version), 2MB

Supplementary Material (public)

2632281_Suppl_1.pdf
(Supplementary material), 2MB

Citation

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.


Cite as: https://hdl.handle.net/21.11116/0000-0001-EC10-3
Abstract
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.