Squamous cell carcinoma of the head and neck (HNSCC) consist of two distinct biological entities. While the numbers of classical, tobacco-induced HNSCC are declining, tumors caused by human papillomavirus (HPV) infection are increasing in many countries. HPV-positive HNSCC mostly arise in the oropharynx and are characterized by an enhanced sensitivity towards radiotherapy and a favorable prognosis. To identify molecular differences between both entities on the protein level, we conducted a mass spectrometric comparison of eight HPV-positive and nine HPV-negative oropharyngeal tumors (OPSCC). Overall, we identified 2051 proteins, of which 31 were found to be differentially expressed. Seventeen of these can be assorted to three functional groups, namely DNA replication, nuclear architecture and cytoskeleton regulation, with the differences in the last group potentially reflecting an enhanced migratory and invasive capacity. Furthermore, a number of identified proteins have been described to directly impact on DNA double-strand break repair or radiation sensitivity (e.g., SLC3A2, cortactin, RBBP4, Numa1), offering explanations for the differential prognosis. The unequal expression of three proteins (SLC3A2, MCM2 and lamin B1) was confirmed by immunohistochemical staining using a tissue microarray containing 205 OPSCC samples. The expression levels of SLC3A2 and lamin B1 were found be of prognostic relevance in patients with HPV-positive and HPV-negative OPSCC, respectively.

Magnesium-based biomaterials belong to the third generation of biomaterials that are also bioactive. These smart materials combine bioactivity and biodegradability, and elicit specific cellular responses at the molecular level. In fact, osteoinductive properties have been observed in mesenchymal stem cells in the presence of Magnesium. The mechanistic understanding of the physiological effects however, remains a difficult task as Mg is involved in a multitude of biological reactions. The study of protein interactions may shed light on the molecular processes in Mg-stimulated cells, therefore, suitable data mining tools are required to analyze the large amount data generated via proteomics. Protein compositions over time between two conditions (human mesenchymal stem cells cultured with and without Mg degradation products) were analysed using Vester's Sensitivity Model. Proteins whose dynamics significantly change from one setup to the other were classified into four categories: passive, active, critical, and buffering according to their regulatory activity. In this work, we demonstrate the use of Vester’s Sensitivity Model as an appropriate data mining tool. Protein network analyses highlighted the primary role of Mg-based implant degradation on cell metabolism without deleterious effect on cell viability. Furthermore, key proteins involved in calcium-dependant cellular activities were emphasised leading to further studies.