Mining for osteogenic surface topographies: In silico design to in vivo osseo-integration

Frits F. B. Hulshof; Bernke Papenburg; Aliaksei Vasilevich; Marc Hulsman; Yiping Zhao; Marloes Levers; Natalie Fekete; Meint de Boer; Huipin Yuan; Shantanu Singh; Nick Beijer; Mark-Anthony Bray; Marcel Reinders; Anne E. Carpenter; Clemens van Blitterswijk; Dimitrios Stamatialis; Jan de Boer; David J. Logan

doi:10.1016/j.biomaterials.2017.05.020

Mining for osteogenic surface topographies: In silico design to in vivo osseo-integration

Frits F. B. Hulshof, Bernke Papenburg, Aliaksei Vasilevich, Marc Hulsman, Yiping Zhao, Marloes Levers, Natalie Fekete, Meint de Boer, Huipin Yuan, Shantanu Singh, Nick Beijer, Mark-Anthony Bray, Marcel Reinders, Anne E. Carpenter, Clemens van Blitterswijk, Dimitrios Stamatialis, Jan de Boer^*, David J. Logan

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

Stem cells respond to the physicochemical parameters of the substrate on which they grow. Quantitative material activity relationships - the relationships between substrate parameters and the phenotypes they induce - have so far poorly predicted the success of bioactive implant surfaces. In this report, we screened a library of randomly selected designed surface topographies for those inducing osteogenic differentiation of bone marrow-derived mesenchymal stem cells. Cell shape features, surface design parameters, and osteogenic marker expression were strongly correlated in vitro. Furthermore, the surfaces with the highest osteogenic potential in vitro also demonstrated their osteogenic effect in vivo: these indeed strongly enhanced bone bonding in a rabbit femur model. Our work shows that by giving stem cells specific physicochemical parameters through designed surface topographies, differentiation of these cells can be dictated. (C) 2017 Elsevier Ltd. All rights reserved.

Original language	English
Pages (from-to)	49-60
Number of pages	12
Journal	Biomaterials
Volume	137
DOIs	https://doi.org/10.1016/j.biomaterials.2017.05.020
Publication status	Published - Aug 2017

Keywords

Surface topography
High-throughput screening
Bone implants
Differentiation
Micro-fabrication
Computational modeling
MESENCHYMAL STEM-CELLS
HIGH-THROUGHPUT
HISTONE ACETYLATION
BIOMATERIALS
IMPLANTS
DIFFERENTIATION
MINERALIZATION
MECHANISMS
ATTACHMENT
EXPRESSION

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10.1016/j.biomaterials.2017.05.020

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Cite this

Hulshof, F. F. B., Papenburg, B., Vasilevich, A., Hulsman, M., Zhao, Y., Levers, M., Fekete, N., de Boer, M., Yuan, H., Singh, S., Beijer, N., Bray, M.-A., Reinders, M., Carpenter, A. E., van Blitterswijk, C., Stamatialis, D., de Boer, J., & Logan, D. J. (2017). Mining for osteogenic surface topographies: In silico design to in vivo osseo-integration. Biomaterials, 137, 49-60. https://doi.org/10.1016/j.biomaterials.2017.05.020

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title = "Mining for osteogenic surface topographies: In silico design to in vivo osseo-integration",

abstract = "Stem cells respond to the physicochemical parameters of the substrate on which they grow. Quantitative material activity relationships - the relationships between substrate parameters and the phenotypes they induce - have so far poorly predicted the success of bioactive implant surfaces. In this report, we screened a library of randomly selected designed surface topographies for those inducing osteogenic differentiation of bone marrow-derived mesenchymal stem cells. Cell shape features, surface design parameters, and osteogenic marker expression were strongly correlated in vitro. Furthermore, the surfaces with the highest osteogenic potential in vitro also demonstrated their osteogenic effect in vivo: these indeed strongly enhanced bone bonding in a rabbit femur model. Our work shows that by giving stem cells specific physicochemical parameters through designed surface topographies, differentiation of these cells can be dictated. (C) 2017 Elsevier Ltd. All rights reserved.",

keywords = "Surface topography, High-throughput screening, Bone implants, Differentiation, Micro-fabrication, Computational modeling, MESENCHYMAL STEM-CELLS, HIGH-THROUGHPUT, HISTONE ACETYLATION, BIOMATERIALS, IMPLANTS, DIFFERENTIATION, MINERALIZATION, MECHANISMS, ATTACHMENT, EXPRESSION",

author = "Hulshof, {Frits F. B.} and Bernke Papenburg and Aliaksei Vasilevich and Marc Hulsman and Yiping Zhao and Marloes Levers and Natalie Fekete and {de Boer}, Meint and Huipin Yuan and Shantanu Singh and Nick Beijer and Mark-Anthony Bray and Marcel Reinders and Carpenter, {Anne E.} and {van Blitterswijk}, Clemens and Dimitrios Stamatialis and {de Boer}, Jan and Logan, {David J.}",

year = "2017",

month = aug,

doi = "10.1016/j.biomaterials.2017.05.020",

language = "English",

volume = "137",

pages = "49--60",

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issn = "0142-9612",

publisher = "Elsevier",

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Hulshof, FFB, Papenburg, B, Vasilevich, A, Hulsman, M, Zhao, Y, Levers, M, Fekete, N, de Boer, M, Yuan, H, Singh, S, Beijer, N, Bray, M-A, Reinders, M, Carpenter, AE, van Blitterswijk, C, Stamatialis, D, de Boer, J & Logan, DJ 2017, 'Mining for osteogenic surface topographies: In silico design to in vivo osseo-integration', Biomaterials, vol. 137, pp. 49-60. https://doi.org/10.1016/j.biomaterials.2017.05.020

TY - JOUR

T1 - Mining for osteogenic surface topographies

T2 - In silico design to in vivo osseo-integration

AU - Hulshof, Frits F. B.

AU - Papenburg, Bernke

AU - Vasilevich, Aliaksei

AU - Hulsman, Marc

AU - Zhao, Yiping

AU - Levers, Marloes

AU - Fekete, Natalie

AU - de Boer, Meint

AU - Yuan, Huipin

AU - Singh, Shantanu

AU - Beijer, Nick

AU - Bray, Mark-Anthony

AU - Reinders, Marcel

AU - Carpenter, Anne E.

AU - van Blitterswijk, Clemens

AU - Stamatialis, Dimitrios

AU - de Boer, Jan

AU - Logan, David J.

PY - 2017/8

Y1 - 2017/8

N2 - Stem cells respond to the physicochemical parameters of the substrate on which they grow. Quantitative material activity relationships - the relationships between substrate parameters and the phenotypes they induce - have so far poorly predicted the success of bioactive implant surfaces. In this report, we screened a library of randomly selected designed surface topographies for those inducing osteogenic differentiation of bone marrow-derived mesenchymal stem cells. Cell shape features, surface design parameters, and osteogenic marker expression were strongly correlated in vitro. Furthermore, the surfaces with the highest osteogenic potential in vitro also demonstrated their osteogenic effect in vivo: these indeed strongly enhanced bone bonding in a rabbit femur model. Our work shows that by giving stem cells specific physicochemical parameters through designed surface topographies, differentiation of these cells can be dictated. (C) 2017 Elsevier Ltd. All rights reserved.

AB - Stem cells respond to the physicochemical parameters of the substrate on which they grow. Quantitative material activity relationships - the relationships between substrate parameters and the phenotypes they induce - have so far poorly predicted the success of bioactive implant surfaces. In this report, we screened a library of randomly selected designed surface topographies for those inducing osteogenic differentiation of bone marrow-derived mesenchymal stem cells. Cell shape features, surface design parameters, and osteogenic marker expression were strongly correlated in vitro. Furthermore, the surfaces with the highest osteogenic potential in vitro also demonstrated their osteogenic effect in vivo: these indeed strongly enhanced bone bonding in a rabbit femur model. Our work shows that by giving stem cells specific physicochemical parameters through designed surface topographies, differentiation of these cells can be dictated. (C) 2017 Elsevier Ltd. All rights reserved.

KW - Surface topography

KW - High-throughput screening

KW - Bone implants

KW - Differentiation

KW - Micro-fabrication

KW - Computational modeling

KW - MESENCHYMAL STEM-CELLS

KW - HIGH-THROUGHPUT

KW - HISTONE ACETYLATION

KW - BIOMATERIALS

KW - IMPLANTS

KW - DIFFERENTIATION

KW - MINERALIZATION

KW - MECHANISMS

KW - ATTACHMENT

KW - EXPRESSION

U2 - 10.1016/j.biomaterials.2017.05.020

DO - 10.1016/j.biomaterials.2017.05.020

M3 - Article

C2 - 28535442

SN - 0142-9612

VL - 137

SP - 49

EP - 60

JO - Biomaterials

JF - Biomaterials

ER -