In silico identification of transcription based biomarkers for early diagnosis of inflammatory bowel disease and predicting progression to colorectal cancer
| dc.contributor.author | Khan, Farhat | |
| dc.date.accessioned | 2023-11-23T07:39:09Z | |
| dc.date.available | 2023-11-23T07:39:09Z | |
| dc.date.issued | 2022 | |
| dc.description | A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy to the Faculty of Science, University of the Witwatersrand, 2022 | |
| dc.description.abstract | Inflammatory Bowel Disease (IBD) is a complex intestinal inflammation disorder that negatively impacts the quality life of patients. Diagnosis is confirmed through colonoscopy and in paediatrics this procedure is traumatic which highlights the need of less-invasive screening methods for clinical use. Circumstances is additionally entangled by the way that IBD patients have 20-fold increased risk of developing colorectal cancer (CRC). Due to advancements in computer technologies and development of new methods, bioinformatics has become an essential component of biology research. We hypothesized that utilizing bioinformatics methods to identify transcription-based biomarkers can be used for early diagnosis and screening of IBD, and for predicting the danger of its development to CRC in these patients. Transcription factors (TFs) are regulatory proteins that bind primarily to the promoter region of the target genes and control some of the key fundamental processes in a cell. We aim to identify key transcriptional regulators of IBD, and CRC associated genes by generating and understanding the transcription regulatory networks through our proposed methodology. To our knowledge there is currently no IBD genes database created so far. We first aimed at developing manually curated database of 289 IBD genes that are experimentally validated. Furthermore, to achieve other aims, we used various computational tools. To identify TFs and mapping of transcription factor binding sites (TFBSs) to mammalian matrices were achieved by OPOSSUM and JASPAR respectively. Using Cytoscape, we constructed largest transcriptional regulatory networks of top ranked TFs that were mapped to CRC genes. The pathway analysis was done by KEGG, and gene ontology was conducted using DAVID. Majority of the pathways identified were involved in the processes, known to play potential role in IBD. The top upregulated pathways in IBD identified were cytokine, immune response, autophagy, WNT signalling, transmembrane signalling. Further testing of expression of these key regulators in using publicly available published data were done using ONCOMINE database. We identified serological biomarkers of CRC and combined them with transcription-based biomarkers of IBD (CEA + TIMP1 + CA724 + RUNX1) to predict early diagnosis of IBD progressing to CRC. This project will form the basis to develop a kit in future for use in pathology laboratories and clinical settings. | |
| dc.description.librarian | PC(2023) | |
| dc.faculty | Faculty of Science | |
| dc.identifier.uri | https://hdl.handle.net/10539/37133 | |
| dc.language.iso | en | |
| dc.phd.title | PhD | |
| dc.school | Molecular and Cell Biology | |
| dc.subject | Inflammatory Bowel Disease (IBD) | |
| dc.subject | Colorectal Cancer | |
| dc.subject | Intestinal inflammation | |
| dc.title | In silico identification of transcription based biomarkers for early diagnosis of inflammatory bowel disease and predicting progression to colorectal cancer | |
| dc.type | Thesis |