E Calciolari1,2, S Hamlet3,4, S Ivanovski5, N Donos1,2. 1. Centre for Oral Immunobiology and Regenerative Medicine, Institute of Dentistry, Barts and The London School of Medicine and Dentistry, Queen Mary University of London (QMUL), London, UK. 2. Centre for Oral Clinical Research, Institute of Dentistry, Barts and The London School of Medicine and Dentistry, Queen Mary University of London (QMUL), London, UK. 3. School of Dentistry and Oral Health, Gold Coast Campus, Griffith University, Southport, QLD, Australia. 4. Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia. 5. School of Dentistry, University of Queensland, Brisbane, QLD, Australia.
Abstract
BACKGROUND: It is now generally accepted that the response to a particular signal, such as the surgical trauma following implant placement, is not the result of a single linear signalling pathway, but rather reflects pathway integration, which can occur at multiple levels. Although it is well documented that both SLA and SLActive surfaces are able to promote bone formation and osseointegration, it is still unclear which are the key signalling pathways involved and how surface hydrophilicity/hydrophobicity might affect pathway integration. OBJECTIVE: To combine gene and protein data from in vivo studies applying titanium hydrophobic (Sandblasting, Large-grit, Acid-etching, SLA) and hydrophilic (SLActive) surfaces to understand the molecular mechanisms responsible for the pro-osteogenic properties of these surfaces. METHODS: The Kyoto Encyclopedia of Genes and Genomes (KEGG® ) pathway database and the Ingenuity® Pathway Analysis (IPA® ) software were applied to the genomic and proteomic data of previous in vivo studies applying SLA and SLActive surfaces, with the specific aim to focus on bone formation-related signalling pathways. While gene data were derived from a human study on osseointegration, protein data originated from a preclinical study in rabbits. Data were available for the 4, 7 and 14 days of healing periods. RESULTS: Both genomic and proteomic data showed that the osteogenesis process takes place mainly at 7 and 14 days of healing on both SLA and SLActive surfaces. Surface hydrophilicity enhances bone formation at multiple levels, by directly promoting an earlier expression of pathways involved in cell proliferation and osteoblast precursor differentiation (eg, mitogen-activated protein kinase, phosphoinositide-3 kinase-AKT, Wnt, Notch, transforming growth factor-β), but also by positively regulating angiogenesis, bone mineralization and bone remodelling. CONCLUSION: This study combined, for the first time, different 'omics' outputs to get new insights on the molecular mechanisms behind the influence of surface hydrophilicity on osseointegration/bone formation. Specific signalling pathways, such as Wnt, vascular endothelial growth factor and mitogen-activated protein kinase, were identified as differentially modulated by titanium surface hydrophilicity both at a genomic and proteomic level. These findings may be used in the future to monitor/predict the bone formation/osseointegration process, or as a screening tool towards the manufacture of new pro-osteogenic implant surfaces. In order to take into account the full complexity and interplay of cell signalling during bone formation, powerful bioinformatics tools integrating different 'omics' data and predicting signalling pathways trends should be applied by future studies.
BACKGROUND: It is now generally accepted that the response to a particular signal, such as the surgical trauma following implant placement, is not the result of a single linear signalling pathway, but rather reflects pathway integration, which can occur at multiple levels. Although it is well documented that both SLA and SLActive surfaces are able to promote bone formation and osseointegration, it is still unclear which are the key signalling pathways involved and how surface hydrophilicity/hydrophobicity might affect pathway integration. OBJECTIVE: To combine gene and protein data from in vivo studies applying titanium hydrophobic (Sandblasting, Large-grit, Acid-etching, SLA) and hydrophilic (SLActive) surfaces to understand the molecular mechanisms responsible for the pro-osteogenic properties of these surfaces. METHODS: The Kyoto Encyclopedia of Genes and Genomes (KEGG® ) pathway database and the Ingenuity® Pathway Analysis (IPA® ) software were applied to the genomic and proteomic data of previous in vivo studies applying SLA and SLActive surfaces, with the specific aim to focus on bone formation-related signalling pathways. While gene data were derived from a human study on osseointegration, protein data originated from a preclinical study in rabbits. Data were available for the 4, 7 and 14 days of healing periods. RESULTS: Both genomic and proteomic data showed that the osteogenesis process takes place mainly at 7 and 14 days of healing on both SLA and SLActive surfaces. Surface hydrophilicity enhances bone formation at multiple levels, by directly promoting an earlier expression of pathways involved in cell proliferation and osteoblast precursor differentiation (eg, mitogen-activated protein kinase, phosphoinositide-3 kinase-AKT, Wnt, Notch, transforming growth factor-β), but also by positively regulating angiogenesis, bone mineralization and bone remodelling. CONCLUSION: This study combined, for the first time, different 'omics' outputs to get new insights on the molecular mechanisms behind the influence of surface hydrophilicity on osseointegration/bone formation. Specific signalling pathways, such as Wnt, vascular endothelial growth factor and mitogen-activated protein kinase, were identified as differentially modulated by titanium surface hydrophilicity both at a genomic and proteomic level. These findings may be used in the future to monitor/predict the bone formation/osseointegration process, or as a screening tool towards the manufacture of new pro-osteogenic implant surfaces. In order to take into account the full complexity and interplay of cell signalling during bone formation, powerful bioinformatics tools integrating different 'omics' data and predicting signalling pathways trends should be applied by future studies.
Authors: Andrew L Raines; Michael B Berger; Nehal Patel; Sharon L Hyzy; Barbara D Boyan; Zvi Schwartz Journal: J Biomed Mater Res A Date: 2018-11-21 Impact factor: 4.396
Authors: Coralee E Tye; Prachi N Ghule; Jonathan A R Gordon; Fleur S Kabala; Natalie A Page; Michelle M Falcone; Kirsten M Tracy; Andre J van Wijnen; Janet L Stein; Jane B Lian; Gary S Stein Journal: Sci Rep Date: 2022-05-11 Impact factor: 4.996
Authors: Scott Dillon; Karla Suchacki; Shun-Neng Hsu; Louise A Stephen; Rongling Wang; William P Cawthorn; Alan J Stewart; Fabio Nudelman; Nicholas M Morton; Colin Farquharson Journal: JBMR Plus Date: 2020-12-08