BackgroundNanomaterials (NMs) can be fine-tuned in their properties resulting in a high number of variants, each requiring a thorough safety assessment. Grouping and categorization approaches that would reduce the amount of testing are in principle existing for NMs but are still mostly conceptual. One drawback is the limited mechanistic understanding of NM toxicity. Thus, we conducted a multi-omics in vitro study in RLE-6TN rat alveolar epithelial cells involving 12 NMs covering different materials and including a systematic variation of particle size, surface charge and hydrophobicity for SiO2 NMs. Cellular responses were analyzed by global proteomics, targeted metabolomics and SH2 profiling. Results were integrated using Weighted Gene Correlation Network Analysis (WGCNA).ResultsCluster analyses involving all data sets separated Graphene Oxide, TiO2_NM105, SiO2_40 and Phthalocyanine Blue from the other NMs as their cellular responses showed a high degree of similarities, although apical in vivo results may differ. SiO2_7 behaved differently but still induced significant changes. In contrast, the remaining NMs were more similar to untreated controls. WGCNA revealed correlations of specific physico-chemical properties such as agglomerate size and redox potential to cellular responses. A key driver analysis could identify biomolecules being highly correlated to the observed effects, which might be representative biomarker candidates. Key drivers in our study were mainly related to oxidative stress responses and apoptosis.ConclusionsOur multi-omics approach involving proteomics, metabolomics and SH2 profiling proved useful to obtain insights into NMs Mode of Actions. Integrating results allowed for a more robust NM categorization. Moreover, key physico-chemical properties strongly correlating with NM toxicity were identified. Finally, we suggest several key drivers of toxicity that bear the potential to improve future testing and assessment approaches.

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Overexpression of the epidermal growth factor receptor (EGFR) in head and neck squamous cell carcinomas (HNSCC) is considered to cause increased EGFR activity, which adds to tumorigenicity and therapy resistance. Since it is still unclear, whether EGFR expression is indeed associated with increased activity in HNSCC, we analyzed the relationship between EGFR expression and auto-phosphorylation as a surrogate marker for activity. We used a tissue micro array, fresh frozen HNSCC tumor and corresponding normal tissue samples and a large panel of HNSCC cell lines. While we observed substantial overexpression only in approximately 20% of HNSCC, we also observed strong discrepancies between EGFR protein expression and auto-phosphorylation in HNSCC cell lines as well as in tumor specimens using Western blot and SH2-profiling; for the majority of HNSCC EGFR expression therefore seems not to be correlated with EGFR auto-phosphorylation. Blocking of EGFR activity by cetuximab and erlotinib points to increased EGFR activity in samples with increased basal auto-phosphorylation. However, we could also identify cells with low basal phosphorylation but relevant EGFR activity. In summary, our data demonstrate that EGFR expression and activity are not well correlated. Therefore EGFR positivity is no reliable surrogate marker for EGFR activity, arguing the need for alternative biomarkers or functional predictive tests.