부산대학교 도서관

Ulcerative colitis (UC) is an inflammatory condition affecting the mucosa of the large bowel and the occurrence is linked to the increase of developing colitis associated cancer (CAC). The identification of biomarkers to predict those who are at risk of progressing to CAC is needed to assist in early decision making for restorative surgery and improved outcome following surgery. However, previous attempts at the identification of consistent genetic biomarkers have not been successful, due to non-reproducibility of the results. This could attribute partly to variability in tissues used and partly to the complex pathophysiology. The regenerative stress in UC mucosa resulting in multiple structural mutations in genes may also be a cause for the variability. Therefore, the first aim of this study was the identification of differentially methylated genes to be used as potential biomarkers of malignant transformation at a precancerous stage. Whole genome bisulphite sequencing was carried out on laser captured epithelial cells on a pilot cohort of 8 samples of normal, inflamed, dysplastic and malignant colonic mucosa. Each sample was matched with adjacent non-neoplastic mucosa or buffy coat from the same patient as controls. Sixty-three hypomethylated and six hypermethylated gene promoters were identified as differentially methylated in the samples compared to the normal epithelium. These methylation changes were unique to the diseased tissue and were consistently found in each stage of the disease, suggesting they could be used as biomarkers for CAC. Out of these genes, 7 hypomethylated and 4 hypermethylated genes were identified as strongly related to CRC pathways. Similarly, the analysis of gene body methylation allowed the identification of further 10 hypomethylated and 2 hypermethylated genes related to CRC pathways. Moreover the identified genes could be annotated to cell adhesion related molecular function and disease processes, including UC and epithelial cancers. Amongst proteins and pathways of clinical importance, TGFβ, a molecule with anti-inflammatory properties, is inhibited in UC-affected mucosa. Recently, SMAD7, the principal intracellular inhibitor of the TGFβ pathway, has been proposed as a therapeutic target in UC. However, SMAD7 is shown to influence CRC development and progression in a less understood manner. Furthermore, studies in breast cancer indicate that SMAD7 influences methylation patterns of cancer-associated genes. Therefore investigating the potential effect of SMAD7 on CAC and differential methylation of related genes would provide insight into its role in CAC. The second and third aims of this study were therefore was to observe the behaviour pattern of SMAD7 at different stages of CAC and analyse the methylation pattern of identified SMAD7-associated genes. Immunohistochemistry and in situ hybridisation was performed on 53 and 33 samples from non-inflamed, inflamed, dysplastic and cancer tissues, respectively. SMAD7 was biphasically expressed in different stages of CAC: high expression during the inflammation and cancer stages was associated with a lower expression in the non-inflamed UC and dysplastic tissues. On the other hand, the downstream molecule pSMAD3 did not show a reduction in expression suggesting an escape of TGFβ from the inhibitory effect of SMAD7 in UC. The evaluation of the methylation patterns in cancer-associated genes supposedly influenced by SMAD7 (CDH1, CLDN4, DNMT1, CGN) did not demonstrate a consistent pattern of differential methylation. This data has strong clinical implications, as the biphasic expression of SMAD7 during precancerous stages suggests further evaluation is needed prior to using an antisense to inhibit SMAD7 in the clinic. In conclusion, this pilot study identified 27 potential genes with differential methylation, of which the expression of some has already been validated with RT-qPCR. The consistency of the methylation pattern of these genes across all stages of CAC and their annotation to cancer and cancer related biological processes make them strong potential candidates for an early biomarker in CAC. An extension of the analysis in a wider samples cohort and complete validation of each target will be necessary to validate their efficacy and lead to developing a clinically useful gene panel to predict CAC.