Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/30243
Title: Molecular and computational approaches to understanding Keloid scarring
Authors: OOI NICK SERN, BRANDON
Keywords: keloid, fibroblast, hepatoma-derived growth factor, microarray, reverse engineering, gene networks
Issue Date: 13-Dec-2010
Source: OOI NICK SERN, BRANDON (2010-12-13). Molecular and computational approaches to understanding Keloid scarring. ScholarBank@NUS Repository.
Abstract: Keloid scars are aberrations in the wound healing process, resulting in the appearance of protrusive crab like extensions growing into normal tissue. They do not subside with time, and may develop over the most minor of skin wounds, such as insect bites or acne. Aside from being an aesthetic impediment, keloids are frequently associated with itchiness, pain and, when involving the skin overlying a joint, restricted range of motion. To date, none of the known treatment modalities have proven optimal. In recent years, a systems approach to understanding biology has gained eminence, in part due to the limitations of a purely reductionist approach in explaining biological phenomena. However, there are merits to the reductionist approach; much of what we know of biology today can be attributed to the work of molecular biologists of the past. In this dissertation, we will adopt both these approaches to tackling the keloid problem. In the first part of this thesis, we examined the role played by a novel growth factor, the hepatoma-derived growth factor (HDGF), in keloid pathogenesis. Using a combination of immunohistochemical staining and Western blots, we found that secreted HDGF is increased in the keloid condition and its secretion is modulated by epithelial?mesenchymal interactions. Furthermore, exogenous HDGF exerts a proliferative effect on keloid fibroblasts and increases the production of the angiogenic factor VEGF, indicating that it plays some role in the process of angiogenesis. With the advent of high throughput technology, researchers are no longer confined to the study of individual molecules. In the second part of this dissertation, we utilized the microarray platform to assess the global transcriptional differences between keloid and normal fibroblasts under serum free conditions. Many of the genes that have been found to be differentially expressed in previous studies were reconfirmed in this study. In addition, some interesting and novel genes not previously reported were also discovered. Gene Ontology terms that were found to be significantly enriched include those relating to immune response, antigen processing and presentation, chemokine and cytokine activity, extracellular matrix and ribosomal proteins. In the third part of this thesis, we attempted to reverse engineer gene networks from microarray expression profiles of keloid and normal fibroblasts. Using a physical approach to model transcription factor interactions, we discovered some of the binding motifs that were active in the keloid condition. Furthermore, we used the influence approach to reverse engineer some of the networks that were found to be significantly enriched from the second part of this dissertation. Our results indicate that transcriptional networks were better suited for this process compared to cytokine receptor interactions and intracellular signaling networks. We also found that the NFKB transcriptional network that was inferred from normal fibroblast data was more accurate compared to that inferred from keloid data, suggesting a more robust network in the keloid condition. This would mean that targeting NFKB alone may not be sufficient to reduce its transcriptional products in keloid fibroblasts. The work done in this thesis, utilizing both molecular and computational approaches, has advanced our understanding by shedding light on some of the important players and key networks in keloid scarring. In addition, the results from this study has generated new and promising future areas of research, and is a small step forward to finding a solution to this condition.
URI: http://scholarbank.nus.edu.sg/handle/10635/30243
Appears in Collections:Ph.D Theses (Open)

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