The aim of this thesis is to investigate the role of inflammatory infiltrates and chemokines in metastasis of high-grade serous ovarian cancer, HGSC, to the omentum using human tissue biopsies and a 3- dimensional (3D) cell culture model. In ten patients with metastatic HGSC, omental tumour deposits contained a prominent leukocyte infiltrate of CD3+ T cells (9% of total cells) and CD68+ macrophages (11% of total cells). The presence of CD68+ macrophages showed a significant positive correlation with tumour cell proliferation analysed by Ki67 expression. Four ovarian cancer cell lines were co-cultured on a 3D model mimicking the microenvironment of the omentum for two weeks. The model was composed of collagen embedded human fibroblasts covered in a confluent layer of human primary mesothelial cells. The mesothelial cells in the 3D model significantly increased the growth (p = 0.002) and invasion (p = 0.0004) of the ovarian cancer cells. CXCL12 is the macrophage chemoattractant and ligand for the major chemokine receptor expressed on ovarian cancer cells. An association between CXCL12 and extracellular matrix remodelling was identified in two independent gene expression microarrays of ovarian cancer biopsies. The expression of CXCL12 in the HGSC omental metastases measured by quantitative Real Time-PCR positively correlated with decorin expression. Antibody mediated neutralisation of CXCL12 reduced growth (p = 0.012) and invasion (p = 0.029) in the 3D model. Mimicking an infiltrate of CD68+ macrophages in this multicellular 3D in vitro system also produced measurable changes in inflammatory cytokine and chemokine expression. There is currently a demand for more accurate models of HGSC and a necessity to study its metastasis that presents itself as the major clinical problem in patients. Therefore the development of this 3D model to mimic tumour-promoting inflammation in HGSC metastasis will provide researchers with an essential tool for testing novel therapeutic strategies.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:658696 |
| Date | January 2014 |
| Creators | Everitt, Gemma Louise Ann |
| Publisher | Queen Mary, University of London |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://qmro.qmul.ac.uk/xmlui/handle/123456789/8038 |
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