Ovarian cancer serum biomarker discovery using proteomics.
Doctoral thesis, UCL (University College London).
Ovarian cancer is a lethal gynaecological malignancy which is known as the silent killer. It has a poor prognosis due to the lack of major symptoms in early stage disease and hence its late detection. Cancer antigen-125, the most widely used biomarker for ovarian cancer detection, lacks appropriate sensitivity and specificity. Thus, early biomarkers of the disease are urgently required. Proteomic analysis of human serum promises to be a valuable approach for the discovery of putative biomarkers for human malignancies like ovarian cancer, which could be developed into non-invasive blood tests. In this study, serum samples from a pilot study for ovarian cancer screening which were collected prior to diagnosis were processed at Memorial Sloan Kettering Cancer Research Centre, in collaboration with Prof. Tempst’s group, who had developed a novel mass spectrometry (MS)-based technology platform for the high-throughput extraction and measurement of serum peptides. Several marker peaks were identified, which when used in combination with the ovarian cancer biomarker CA-125, assisted in the discrimination of case versus healthy samples at an earlier point prior to diagnosis. Work then involved the establishment and optimisation of a similar serum profiling platform at UCL. This involved the optimisation of a liquid-handling robot to provide semi-automated high- throughput sample purification and spotting, and optimisation of spectral acquisition and processing. The reproducibility of the platform was tested and the effects of different sample handling conditions on peptide profiles examined. The method was then used to search for putative markers of ovarian cancer, using identically processed samples from women diagnosed with malignant or benign ovarian cancer and healthy controls. Finally, as a complementary approach to discover protein biomarkers, the same samples were profiled using 2D Difference Gel Electrophoresis, employing different fractionation strategies to overcome the very large dynamic range of protein expression in serum. Mass spectrometry was used to identify several previously reported and some novel putative biomarkers of ovarian cancer, which warrant further validation.
|Title:||Ovarian cancer serum biomarker discovery using proteomics|
|Open access status:||An open access version is available from UCL Discovery|
|UCL classification:||UCL > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute for Women's Health|
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