Introduction: Early diagnosis of breast cancer can result in less radical therapy and improved survival. Current screening and diagnostic tools have limitations, as do serum marker antigens due to their low sensitivity. We hypothesised that an immune response is an early event in cancer evolution. Autoantibodies, which are the amplified signals of cancer-derived antigens, can be detected in the peripheral blood of women with early breast cancer. This thesis is a continuation of previous work at the Nottingham Breast Unit aimed at developing new panel of assays for the detection of autoantibodies in breast cancer. The goal of this thesis was to investigate the use of a potentially more reproducible ELISA assay to measure serum autoantibodies to MUC1, p53 and c-myc either singly or in combination within a panel to further clarify a role of AAbs in screening, diagnosis or prognosis of primary breast cancer. Methods: Newly expressed, biotinylated and reconfigured p53 and c-myc antigens and purified MUC1 antigen were used to establish novel in-house ELISA. These were used to measure autoantibodies to the above 3 antigens in the serum of various populations which were collected over a two year period. These populations included an at-risk population (e.g. family history and atypical ductal hyperplasia) and a population of women who had just been diagnosed with primary breast cancer, either non-invasive ductal carcinoma in situ (DCIS) or invasive cancers. Cut-off values were established for each of the autoantibodies based on 2 or 3 standard deviations from the mean of a population of control samples. The control samples were obtained from a population of women who were either deemed ‘normal’ or who had a histological diagnosis of benign breast disease. The assay was validated by assessing effect of sample age as samples were of varying age, reproducibility using Bland Altman coefficient of reproducibility and reliability by establishing the assays ability to distinguish cancer from non-cancer. Results: Eight hundred and ninety eight samples were analysed in the study. One hundred and ten were Control samples. The remaining samples included 381 that were from an at-risk population and 407 that were from a primary breast cancer population. Mean ages of Control, at-risk and primary breast cancer populations were 58.8, 50 and 62.9 years respectively. Data establishing validity of assay confirmed that sample age did not affect signal strength for MUC1 and c-myc autoantibodies. Older samples for the p53 autoantibody had lower signal than recent ones. Reproducibility data was satisfactory and was best in the samples from the group of women with benign breast disease. Using either a 2 or 3 standard deviation cut-off value the assay was also able to distinguish cancer from non-cancer for both MUC1 and p53 autoantibodies. For the c-myc autoantibody, cancer samples showed increased signal compared to non-cancer although this did not reach significance. The at-risk population were routinely followed up in an outpatient clinic dedicated for women at increased risk of breast cancer. An individual positive marker was noted in up to 10% of at-risk patients. The panel of 3 assays showed a raised marker in 18.4%. This was significantly higher than that for the Control population whose panel detection was 9.1% whilst an individual marker was noted in up to 4.5% of samples. Only the c-myc autoantibody had similar prevalence in both Control and at-risk populations. There was no correlation between risk category and autoantibody detection. The specificity for MUC1, p53 and c-myc autoantibody serum tumour markers were 92.4%, 95.2% and 95% respectively. Specificity of the assay can be further increased if two or more markers were needed to be positive before a positive result is deemed for the assay. Thirteen women in the at-risk group developed breast cancer. The panel had a higher sensitivity to detect occult tumours compared to individual markers but at reduced specificity. Two of 13 at-risk patients (15.4%) who developed breast cancer had a raised marker (MUC1 & p53 autoantibodies) within the panel with a mean lead-time of 43.5 months. Further increasing the cut-off value to Mean + 4 standard deviation of Control population increased the specificity of the panel assay to 97.2% without altering the sensitivity to detect occult tumour (15.4%). Primary breast cancer population consisted of patients who were known to have DCIS or invasive breast cancer. The latter group was further subdivided into those who were detected via screening mammogram (screen-detected) and those who presented with a lump (symptomatic). Two of the 3 markers (p53 and c-myc autoantibodies) were significantly raised in the primary breast cancer population compared to the at-risk population as well as the Control group as detailed in earlier paragraph. Individual markers were detected in up to 20.9%, 10.3% and 9.8% for p53, c-myc and MUC1 autoantibodies respectively. The panel detection rate was 35.1%. The tumour markers showed limited use as a prognostic factor. Only the c-myc autoantibody correlated with a poorer survival due to distant metastasis in symptomatic breast cancers. Data for the screen-detected breast cancer cases showed that there were no correlation between any of the 3 serum marker detection and prognosis. Conclusion: Our data demonstrated the three autoantibody assays whether singly or in combination as a panel showed differences not only between cancer and non-cancer but also between Control and at-risk, as well as between at-risk and cancer. The panel showed that one or more assays were positive in 35% of breast cancers with a specificity of 83.6%. The specificity of the assay can be altered to meet clinical needs by either increasing the cut-off value or altering the markers within the panel. Current data in the literature suggests a number of markers that may be added or substituted into the panel to enhance the specificity and sensitivity. However a sensitivity of 15.4% for detection of occult tumour in the at-risk group makes any clinical application for screening in this group less cost effective using the version of the assays described in this thesis. The lead-time in the two patients who did show elevation of an autoantibody suggests that if the sensitivity and specificity can be improved that there is an in-vivo amplification signal, which might allow earlier identification of some breast cancers. Detection of c-myc autoantibodies indicates a poorer prognosis in the symptomatic group. The value of this information needs to be further determined in larger studies and within multivariate analysis. If the current results remain then there may be clinical implication to this early data. Comparison with previous data from the unit revealed that detection of cancer-associated autoantibodies in primary breast cancer and at-risk groups using this methodology appeared to be less sensitive. This may indicate that the current method has been successful in reducing background signal and hence reduce false positive results. It therefore appears that we have established a more reliable and reproducible assay compared to previous study to detect autoantibodies to tumour-associated antigens. However it is noted that this thesis reports single batches of antigens (MUC1, p53 and c-myc) used in the autoantibody assays. Investigation of differences in protein structure and immunogenicity between batches, which might also affect the sensitivity and specificity of these assays, was outside the scope of this thesis but is the subject of ongoing research by other members of the research group.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:559518 |
Date | January 2009 |
Creators | Khan, Hamed N. |
Publisher | University of Nottingham |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://eprints.nottingham.ac.uk/10876/ |
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