Elucidation of dendritic cell response-material property relationships using high throughput methodologies

The objectives of this research were to elucidate the correlations between material properties and DC phenotype, develop predictive models for DC response based on material properties, and uncover the molecular basis for DC response to biomaterials. Well-defined biomaterial systems, including clinical titanium (Ti) substrates and two polymer libraries, were chosen to study induced DC phenotype.;Due to the time-consuming nature of conventional methods for assessing DC phenotype, a high-throughput (HTP) method was first developed to screen for DC maturation based on surface marker expression (CHAPTER 4). A 96-well filter plate-based HTP methodology was developed and validated for the assessment of DC response to biomaterials. A "maturation factor", defined as CD86/DC-SIGN and measured by immunostaining, was found to be a cell number-independent metric for DC maturation and could be adapted to screen for DC maturation in a microplate format. This methodology was shown to reproducibly yield similar results of DC maturation in response to biomaterial treatment as compared to the conventional flow cytometric method upon DC treatment in 6-well plates. In addition, the supernatants from each treatment could easily be collected for cytotoxicity assessment using glucose-6-phosphate dehydrogenase (G6PD)-based assay and cytokine profiling using multiplex technology.;To examine which material properties were critical in determining DC phenotype, a set of three clinical titanium (Ti) substrates with well-defined surfaces was used to treat DCs (CHAPTER 5). These Ti substrates included pretreatment (PT), sand-blasted and acid-etched (SLA), and modified SLA (modSLA), with different roughness and surface energy. DCs responded differentially to these substrates. Specifically, PT and SLA induced a mature DC (mDC) phenotype, while modSLA-treated DCs remained immature based on surface marker expression, cytokine production profiles and cell morphology. Both PT and SLA induced higher CD86 expression as compared to iDC control, while modSLA maintained CD86 expression at a level similar to iDC. PT- or SLA-treated DCs exhibited dendritic processes associated with a mDC phenotype, while modSLA-treated DCs were rounded, a morphology associated with an iDC phenotype. Furthermore, PT induced increased secretion of MCP-1 by DCs compared to iDCs, indicating that PT promoted a pro-inflammatory environment.;DC response-material property relationships were also derived using more complex materials from a combinatorial library of polymethacrylates (pMAs) (CHAPTER 6). Twelve pMAs were selected and were found to induce differential DC response using the HTP method described in CHAPTER 4. These pMAs resulted in a trend of increasing DC maturation represented by the metric CD86/DC-SIGN, which was consistent with the trends of the production of pro-inflammatory cytokine, TNF-alpha, and chemokine, IL-8. Interestingly, this set of pMAs induced an opposite trend of IL-16 production, which is most likely released as an anti-inflammatory cytokine in this situation. These polymers were characterized extensively for a number of material properties, including surface chemical composition, glass transition temperature (Tg), air-water contact angle, line roughness (Ra), surface roughness (Sa), and surface area. Similar to the results from the Ti study, PCA determined that surface carbon correlated with enhanced DC maturation, while surface oxygen was associated with an iDC phenotype. In addition, Tg, R a, and surface area were unimportant in determining DC response.;From the pMA library, pMAs that induced the two extremes of DC phenotype (mature or immature) were identified for elucidating the mechanistic basis of biomaterial-induced DC responses (CHAPTER 7). Two pMAs, polyhydroxyethylmethacrylate (pHEMA) and poly(isobutyl-co-benzyl-co-terahydrofurfuryl)methacrylate (pIBTMA), were selected because they induced the least and the most mature DC phenotype, respectively. These pMAs were used to elucidate the activation profiles of transcription factors in DCs after biomaterial treatment and were compared to the iDC and mDC controls. In addition, a combined treatment of pHEMA and LPS was also included to determine if pHEMA could maintain an iDC phenotype in the presence of LPS. Interestingly, pIBTMA induced DC maturation primarily through the activation of NF-kappaB, while pHEMA mediated suppression of DC maturation through multiple TFs, including the activation of ISRE, E2F-1, GR-PR, NFAT, and HSF. (Abstract shortened by UMI.).