Predicting biomaterial property-dendritic cell phenotype relationships from the multivariate analysis of responses to polymethacrylates

Peng Meng Kou, Narayanan Pallassana, Rebeca Bowden, Barry Cunningham, Abraham Joy, Joachim Kohn, Julia E. Babensee

Research output: Contribution to journalArticle

34 Scopus citations

Abstract

Dendritic cells (DCs) play a critical role in orchestrating the host responses to a wide variety of foreign antigens and are essential in maintaining immune tolerance. Distinct biomaterials have been shown to differentially affect the phenotype of DCs, which suggested that biomaterials may be used to modulate immune response toward the biologic component in combination products. The elucidation of biomaterial property-DC phenotype relationships is expected to inform rational design of immuno-modulatory biomaterials. In this study, DC response to a set of 12 polymethacrylates (pMAs) was assessed in terms of surface marker expression and cytokine profile. Principal component analysis (PCA) determined that surface carbon correlated with enhanced DC maturation, while surface oxygen was associated with an immature DC phenotype. Partial square linear regression, a multivariate modeling approach, was implemented and successfully predicted biomaterial-induced DC phenotype in terms of surface marker expression from biomaterial properties with R prediction 2 = 0.76. Furthermore, prediction of DC phenotype was effective based on only theoretical chemical composition of the bulk polymers with Rprediction2 = 0.80. These results demonstrated that immune cell response can be predicted from biomaterial properties, and computational models will expedite future biomaterial design and selection.

Original languageEnglish (US)
Pages (from-to)1699-1713
Number of pages15
JournalBiomaterials
Volume33
Issue number6
DOIs
StatePublished - Feb 1 2012

All Science Journal Classification (ASJC) codes

  • Bioengineering
  • Ceramics and Composites
  • Biophysics
  • Biomaterials
  • Mechanics of Materials

Keywords

  • Combinatorial library
  • Dendritic cells
  • Material properties
  • Partial linear squares regression
  • Polymethacrylate
  • Principal component analysis

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