Please use this identifier to cite or link to this item:
http://doi.org/10.25358/openscience-290
Authors: | Goesswein, Dorothee Habtemichael, Negusse Gerhold-Ay, Aslihan Mazur, Johanna Wünsch, Désirée Knauer, Shirley K. Künzel, Julian Matthias, Christoph Strieth, Sebastian Stauber, Roland |
Title: | Expressional analysis of disease-relevant signalling-pathways in primary tumours and metastasis of head and neck cancers |
Online publication date: | 17-Oct-2018 |
Year of first publication: | 2018 |
Language: | english |
Abstract: | Head and neck squamous cell carcinoma (HNSCC) often metastasize to lymph nodes resulting in poor prognosis for patients. Unfortunately, the underlying molecular mechanisms contributing to tumour aggressiveness, recurrences, and metastasis are still not fully understood. However, such knowledge is key to identify biomarkers and drug targets to improve prognosis and treatments. Consequently, we performed genome-wide expression profiling of 15 primary HNSSCs compared to corresponding lymph node metastases and non-malignant tissue of the same patient. Differentially expressed genes were bioinformatically exploited applying stringent filter criteria, allowing the discrimination between normal mucosa, primary tumours, and metastases. Signalling networks involved in invasion contain remodelling of the extracellular matrix, hypoxia-induced transcriptional modulation, and the recruitment of cancer associated fibroblasts, ultimately converging into a broad activation of PI3K/AKT-signalling pathway in lymph node metastasis. Notably, when we compared the diagnostic and prognostic value of sequencing data with our expression analysis significant differences were uncovered concerning the expression of the receptor tyrosine kinases EGFR and ERBB2, as well as other oncogenic regulators. Particularly, upregulated receptor tyrosine kinase combinations for individual patients varied, implying potential compensatory and resistance mechanisms against specific targeted therapies. Collectively, we here provide unique transcriptional profiles for disease predictions and comprehensively analyse involved signalling pathways in advanced HNSCC. |
DDC: | 610 Medizin 610 Medical sciences |
Institution: | Johannes Gutenberg-Universität Mainz |
Department: | FB 04 Medizin |
Place: | Mainz |
ROR: | https://ror.org/023b0x485 |
DOI: | http://doi.org/10.25358/openscience-290 |
URN: | urn:nbn:de:hebis:77-publ-585078 |
Version: | Published version |
Publication type: | Zeitschriftenaufsatz |
License: | CC BY |
Information on rights of use: | https://creativecommons.org/licenses/by/4.0/ |
Journal: | Scientific reports 8 |
Pages or article number: | Art. 7326 |
Publisher: | Macmillan Publishers Limited, part of Springer Nature |
Publisher place: | London |
Issue date: | 2018 |
ISSN: | 2045-2322 |
Publisher URL: | http://dx.doi.org/10.1038/s41598-018-25512-7 |
Publisher DOI: | 10.1038/s41598-018-25512-7 |
Appears in collections: | JGU-Publikationen |