Pathology - Research Publications
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ItemNo Preview AvailableHeterogeneity of breast cancer associations with five susceptibility loci by clinical and pathological characteristics(PUBLIC LIBRARY SCIENCE, 2008-04)A three-stage genome-wide association study recently identified single nucleotide polymorphisms (SNPs) in five loci (fibroblast growth receptor 2 (FGFR2), trinucleotide repeat containing 9 (TNRC9), mitogen-activated protein kinase 3 K1 (MAP3K1), 8q24, and lymphocyte-specific protein 1 (LSP1)) associated with breast cancer risk. We investigated whether the associations between these SNPs and breast cancer risk varied by clinically important tumor characteristics in up to 23,039 invasive breast cancer cases and 26,273 controls from 20 studies. We also evaluated their influence on overall survival in 13,527 cases from 13 studies. All participants were of European or Asian origin. rs2981582 in FGFR2 was more strongly related to ER-positive (per-allele OR (95%CI) = 1.31 (1.27-1.36)) than ER-negative (1.08 (1.03-1.14)) disease (P for heterogeneity = 10(-13)). This SNP was also more strongly related to PR-positive, low grade and node positive tumors (P = 10(-5), 10(-8), 0.013, respectively). The association for rs13281615 in 8q24 was stronger for ER-positive, PR-positive, and low grade tumors (P = 0.001, 0.011 and 10(-4), respectively). The differences in the associations between SNPs in FGFR2 and 8q24 and risk by ER and grade remained significant after permutation adjustment for multiple comparisons and after adjustment for other tumor characteristics. Three SNPs (rs2981582, rs3803662, and rs889312) showed weak but significant associations with ER-negative disease, the strongest association being for rs3803662 in TNRC9 (1.14 (1.09-1.21)). rs13281615 in 8q24 was associated with an improvement in survival after diagnosis (per-allele HR = 0.90 (0.83-0.97). The association was attenuated and non-significant after adjusting for known prognostic factors. Our findings show that common genetic variants influence the pathological subtype of breast cancer and provide further support for the hypothesis that ER-positive and ER-negative disease are biologically distinct. Understanding the etiologic heterogeneity of breast cancer may ultimately result in improvements in prevention, early detection, and treatment.
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ItemNo Preview AvailableThe Breast Cancer Family Registry: an infrastructure for cooperative multinational, interdisciplinary and translational studies of the genetic epidemiology of breast cancer(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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ItemRisk factors for breast cancer in young women by oestrogen receptor and progesterone receptor status(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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ItemNo Preview AvailableThe intronic G13964C variant in p53 is not a high-risk mutation in familial breast cancer in Australia(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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ItemLog odds of carrying an Ancestral Mutation in BRCA1 or BRCA2 for a defined personal and family history in an Ashkenazi Jewish woman (LAMBDA)(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.
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ItemSNP selection for genes of iron metabolism in a study of genetic modifiers of hemochromatosis(BMC, 2008-03-20)BACKGROUND: We report our experience of selecting tag SNPs in 35 genes involved in iron metabolism in a cohort study seeking to discover genetic modifiers of hereditary hemochromatosis. METHODS: We combined our own and publicly available resequencing data with HapMap to maximise our coverage to select 384 SNPs in candidate genes suitable for typing on the Illumina platform. RESULTS: Validation/design scores above 0.6 were not strongly correlated with SNP performance as estimated by Gentrain score. We contrasted results from two tag SNP selection algorithms, LDselect and Tagger. Varying r2 from 0.5 to 1.0 produced a near linear correlation with the number of tag SNPs required. We examined the pattern of linkage disequilibrium of three levels of resequencing coverage for the transferrin gene and found HapMap phase 1 tag SNPs capture 45% of the > or = 3% MAF SNPs found in SeattleSNPs where there is nearly complete resequencing. Resequencing can reveal adjacent SNPs (within 60 bp) which may affect assay performance. We report the number of SNPs present within the region of six of our larger candidate genes, for different versions of stock genotyping assays. CONCLUSION: A candidate gene approach should seek to maximise coverage, and this can be improved by adding to HapMap data any available sequencing data. Tag SNP software must be fast and flexible to data changes, since tag SNP selection involves iteration as investigators seek to satisfy the competing demands of coverage within and between populations, and typability on the technology platform chosen.