Pathology - Research Publications

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    The Breast Cancer Family Registry: an infrastructure for cooperative multinational, interdisciplinary and translational studies of the genetic epidemiology of breast cancer
    John, EM ; Hopper, JL ; Beck, JC ; Knight, JA ; Neuhausen, SL ; Senie, RT ; Ziogas, A ; Andrulis, IL ; Anton-Culver, H ; Boyd, N ; Buys, SS ; Daly, MB ; O'Malley, FP ; Santella, RM ; Southey, MC ; Venne, VL ; Venter, DJ ; West, DW ; Whittemore, AS ; Seminara, D (BMC, 2004)
    INTRODUCTION: The etiology of familial breast cancer is complex and involves genetic and environmental factors such as hormonal and lifestyle factors. Understanding familial aggregation is a key to understanding the causes of breast cancer and to facilitating the development of effective prevention and therapy. To address urgent research questions and to expedite the translation of research results to the clinical setting, the National Cancer Institute (USA) supported in 1995 the establishment of a novel research infrastructure, the Breast Cancer Family Registry, a collaboration of six academic and research institutions and their medical affiliates in the USA, Canada, and Australia. METHODS: The sites have developed core family history and epidemiology questionnaires, data dictionaries, and common protocols for biospecimen collection and processing and pathology review. An Informatics Center has been established to collate, manage, and distribute core data. RESULTS: As of September 2003, 9116 population-based and 2834 clinic-based families have been enrolled, including 2346 families from minority populations. Epidemiology questionnaire data are available for 6779 affected probands (with a personal history of breast cancer), 4116 unaffected probands, and 16,526 relatives with or without a personal history of breast or ovarian cancer. The biospecimen repository contains blood or mouthwash samples for 6316 affected probands, 2966 unaffected probands, and 10,763 relatives, and tumor tissue samples for 4293 individuals. CONCLUSION: This resource is available to internal and external researchers for collaborative, interdisciplinary, and translational studies of the genetic epidemiology of breast cancer. Detailed information can be found at the URL http://www.cfr.epi.uci.edu/.
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    Risk factors for breast cancer in young women by oestrogen receptor and progesterone receptor status
    McCredie, MRE ; Dite, GS ; Southey, MC ; Venter, DJ ; Giles, GG ; Hopper, JL (NATURE PUBLISHING GROUP, 2003-11-03)
    We used data from 765 cases and 564 controls in the population-based Australian Breast Cancer Family Study to investigate whether, in women under the age of 40, the profile of risk factors differed between breast cancer subtypes defined by joint oestrogen and progesterone receptor status. As hypothesised, no significant differences were found.
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    The intronic G13964C variant in p53 is not a high-risk mutation in familial breast cancer in Australia
    Marsh, A ; Spurdle, AB ; Turner, BC ; Fereday, S ; Thorne, H ; Pupo, GM ; Mann, GJ ; Hopper, JL ; Sambrook, JF ; Chenevix-Trench, G (BIOMED CENTRAL LTD, 2001)
    BACKGROUND: Mutations in BRCA1 and BRCA2 account for approximately 50% of breast cancer families with more than four affected cases, whereas exonic mutations in p53, PTEN, CHK2 and ATM may account for a very small proportion. It was recently reported that an intronic variant of p53--G13964C--occurred in three out of 42 (7.1%) 'hereditary' breast cancer patients, but not in any of 171 'sporadic' breast cancer control individuals (P = 0.0003). If this relatively frequent occurrence of G13964C in familial breast cancer and absence in control individuals were confirmed, then this would suggest that the G13964C variant plays a role in breast cancer susceptibility. METHOD: We genotyped 71 familial breast cancer patients and 143 control individuals for the G13964C variant using polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) analysis. RESULTS: Three (4.2%; 95% confidence interval [CI] 0-8.9%) G13964C heterozygotes were identified. The variant was also identified in 5 out of 143 (3.5%; 95% CI 0.6-6.4%) control individuals without breast cancer or a family history of breast cancer, however, which is no different to the proportion found in familial cases (P = 0.9). CONCLUSION: The present study would have had 80% power to detect an odds ratio of 4.4, and we therefore conclude that the G13946C polymorphism is not a 'high-risk' mutation for familial breast cancer.
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    Log odds of carrying an Ancestral Mutation in BRCA1 or BRCA2 for a defined personal and family history in an Ashkenazi Jewish woman (LAMBDA)
    Apicella, C ; Andrews, L ; Hodgson, SV ; Fisher, SA ; Lewis, CM ; Solomon, E ; Tucker, K ; Friedlander, M ; Bankier, A ; Southey, MC ; Venter, DJ ; Hopper, JL (BIOMED CENTRAL LTD, 2003)
    INTRODUCTION: Ancestral mutations in BRCA1 and BRCA2 are common in people of Ashkenazi Jewish descent and are associated with a substantially increased risk of breast and ovarian cancer. Women considering mutation testing usually have several personal and family cancer characteristics, so predicting mutation status from one factor alone could be misleading. The aim of this study was to develop a simple algorithm to estimate the probability that an Ashkenazi Jewish woman carries an ancestral mutation, based on multiple predictive factors. METHODS: We studied Ashkenazi Jewish women with a personal or family history of breast or ovarian cancer and living in Melbourne or Sydney, Australia, or with a previous diagnosis of breast or ovarian cancer and living in the UK. DNA samples were tested for the germline mutations 185delAG and 5382insC in BRCA1, and 6174delT in BRCA2. Logistic regression was used to identify, and to estimate the predictive strength of, major determinants. RESULTS: A mutation was detected in 64 of 424 women. An algorithm was developed by combining our findings with those from similar analyses of a large study of unaffected Jewish women in Washington. Starting with a baseline score, a multiple of 0.5 (based on the logistic regression estimates) is added for each predictive feature. The sum is the estimated log odds ratio that a woman is a carrier, and is converted to a probability by using a table. There was good internal consistency. CONCLUSIONS: This simple algorithm might be useful in the clinical and genetic counselling setting. Comparison and validation in other settings should be sought.