ABSTRACT
A method was developed to isolate extracellular matrix from the human placenta (pECM). The isolated material is composed primarily of collagen, in addition to, elastin, fibronectin, laminin, and glycosaminoglycans (GAGs). The pECM is isolated as a water insoluble paste. This paste can be molded into sheets, tubes, and other 3-D structures that are stable at room temperature. This report describes the interaction of the pluripotent progenitor cells (PDACs) with the isolated pECM. The stem cells used in this study are of human placental origin (placenta derived adherent cells or PDACs) and have a phenotype described as CD200+, CD105+, CD10+, CD34-, and CD45-. The PDACs bind to and proliferate on the pECM, and are stimulated to secrete soluble fibronectin. They actively assemble the soluble fibronectin into a complex network of detergent-insoluble extracellular matrix fibrils. While proliferating on the pECM, PDACs secrete key cytokines at levels well above that observed on tissue-treated tissue culture plates. These cytokines included monocyte chemoattractant protein (MCP-1), IL-6, and IL-8, all of which are important participants in wound healing processes. These results suggest the feasibility of designing a combination product of pECM with PDACs to augment repair processes in nonhealing deep wounds and in diabetic ulcers.
ABSTRACT
ACELAGRAFT™ (Celgene Cellular Therapeutics, Cedar Knolls, NJ) was developed as a decellularized and dehydrated human amniotic membrane product (DDHAM). The product has demonstrated potential as a wound healing product with several ongoing preclinical and clinical studies in the area of acute and chronic ulcers. Although the mechanism of action of such a decellularized product has not been examined, a detailed study of the ability of fibroblasts to interact with DDHAM and subsequent cellular responses are presented. These studies indicate that the composition of DDHAM is that of an extracellular matrix (ECM)-like material with high collagen content, retaining key bioactive molecules, such as fibronectin, laminin, glycosaminoglycans (GAGs), and elastin. No cytokines or growth factors were identified as one might expect in a nondecellularized amniotic membrane product. Cell assays show that fibroblasts can recognize fibronectin in DDHAM and bind to it via typical integrin-fibronectin interactions. Fibroblasts secrete fibronectin and can actively assemble the soluble fibronectin into a complex extracellular matrix on DDHAM. Fibroblasts are also stimulated by DDHAM to secrete key proinflammatory(IL-1 and IL-6) and chemotactic cytokines or chemokines (proand IL-8) involved in regulating and enhancing wound repair processes. Microarray gene expression studies on fibroblasts bound to DDHAM show increased expression of key wound healing cytokines. Together, these studies provide insight into the mechanisms by which DDHAM may augment the wound healing process.
ABSTRACT
A predictive model that can correlate the chemical composition of a biomaterial with the biological response of cells that are in contact with that biomaterial would represent a major advance and would facilitate the rational design of new biomaterials. As a first step toward this goal, we report here on the use of Logical Analysis of Data (LAD) to model the effect of selected polymer properties on the growth of two different cell types, rat lung fibroblasts (RLF, a transformed cell line), and normal foreskin fibroblasts (NFF, nontransformed human cells), on 112 surfaces obtained from a combinatorially designed library of polymers. LAD is a knowledge extraction methodology, based on using combinatorics, optimization, and Boolean logic. LAD was trained on a subset of 62 polymers and was then used to predict cell growth on 50 previously untested polymers. Experimental validation indicated that LAD correctly predicted the high and low cell growth polymers and found optimal ranges for polymer chemical composition, surface chemistry, and bulk properties. Particularly noteworthy is that LAD correctly identified high-performing polymer surfaces, which surpassed commercial tissue culture polystyrene as growth substratum for normal foreskin fibroblasts. Our results establish the feasibility of using computational modeling of cell growth on flat polymeric surfaces to identify promising "lead" polymers for applications that require either high or low cell growth.
