Fourkala, E.-O.; (2011) Risk factors and novel biomarkers in breast cancer. Doctoral thesis , UCL (University College London).

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Abstract

Efforts continue to identify and validate novel risk factors / biomarkers for breast cancer and improve current risk prediction models in the general population due to ongoing issues with sensitivity and specificity. The overall goal of this PhD study is to add to this effort. Specific aims are to (1) examine which is the best source of getting notified for breast cancer diagnosis in the general population since accurate data is crucial for risk assessment studies (2) investigate the association of sex steroids, gonadotrophins and novel assays of sex steroid hormone receptor serum bioactivity (SB) in breast cancer (3) examine whether they can be combined to improve breast cancer risk assessment and (4) identify new DNA methylation markers that might add to such a strategy in the future. To achieve this, a nested case-control study was undertaken within UK Collaborative Trial of Ovarian Cancer Screening. 2629 trial participants were identified via cancer registry (CR) or self-reporting to have breast cancer. Diagnosis was confirmed by the treating clinician. The largest study was undertaken in England and Wales to examine completeness of breast cancer diagnosis within UKCTOCS. Analysis of complete data obtained in 1083 of these women showed CR to be more accurate than self-reporting but associated with time-delays. Serum samples from 200 eligible breast cancer cases identified through the process and 400 matched-controls were analysed for oestradiol, free-oestradiol, oestrone, androstenedione, testosterone, free-testosterone, progesterone, dehydroepiandrosterone sulphate (DHEAS), sex steroid hormone binding globulin (SHBG), luteinising hormone (LH), follicle stimulating hormone (FSH) and oestrogen receptor-α and -β and androgen receptor SB. Results showed that sex steroid receptor SB assays could add to breast cancer risk prediction. Additionally, the best oestrogen for breast cancer risk prediction is oestrone and the best androgen is testosterone. High testosterone and FSH levels up to 5 years prior to diagnosis predict breast cancer with high power and may have a synergistic effect. In a separate case control study of 189 paraffin-embedded breast tissue samples, 55 genes were investigated using MethyLight. DNA methylation alterations were found to be homogeneous in breast cancer with 13 genes being predictive of the disease, suggesting that such changes could be useful as future biomarkers. Further studies (already underway) involve using high-throughput technology to analyse serum DNA methylation changes and correlate these with the observed serum hormonal changes and build better breast cancer risk prediction models.

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