52 research outputs found

    HER3 and downstream pathways are involved in colonization of brain metastases from breast cancer

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    Introduction: Metastases to the brain from breast cancer have a high mortality, and basal-like breast cancers have a propensity for brain metastases. However, the mechanisms that allow cells to colonize the brain are unclear.Methods: We used morphology, immunohistochemistry, gene expression and somatic mutation profiling to analyze 39 matched pairs of primary breast cancers and brain metastases, 22 unmatched brain metastases of breast cancer, 11 non-breast brain metastases and 6 autopsy cases of patients with breast cancer metastases to multiple sites, including the brain.Results: Most brain metastases were triple negative and basal-like. the brain metastases over-expressed one or more members of the HER family and in particular HER3 was significantly over-expressed relative to matched primary tumors. Brain metastases from breast and other primary sites, and metastases to multiple organs in the autopsied cases, also contained somatic mutations in EGFR, HRAS, KRAS, NRAS or PIK3CA. This paralleled the frequent activation of AKT and MAPK pathways. in particular, activation of the MAPK pathway was increased in the brain metastases compared to the primary tumors.Conclusions: Deregulated HER family receptors, particularly HER3, and their downstream pathways are implicated in colonization of brain metastasis. the need for HER family receptors to dimerize for activation suggests that tumors may be susceptible to combinations of anti-HER family inhibitors, and may even be effective in the absence of HER2 amplification (that is, in triple negative/basal cancers). However, the presence of activating mutations in PIK3CA, HRAS, KRAS and NRAS suggests the necessity for also specifically targeting downstream molecules.Ludwig Institute of Cancer ResearchNational Breast Cancer FoundationUniv Queensland, Clin Res Ctr, Brisbane, Qld 4029, AustraliaQueensland Inst Med Res, Brisbane, Qld 4006, AustraliaUniversidade Federal de São Paulo, EPM, Dept Anat Patol, BR-04024000 São Paulo, BrazilGriffith Univ, Brisbane, Qld 4011, AustraliaUniv Queensland, Ctr Magnet Resonance, Brisbane, Qld 4072, AustraliaEijkman Inst, Jakarta 10430, IndonesiaInst Nacl Canc, Dept Patol, BR-20230130 Rio de Janeiro, BrazilLab Salomao & Zoppi, Dept Patol, BR-04104000 São Paulo, BrazilCharles Univ Prague, Fac Med, Dept Pathol, Plzen 30605, Czech RepublicUniv Sydney, Inst Clin Pathol & Med Res, Sydney W Area Hlth Serv, Sydney, NSW 2145, AustraliaUniv Sydney, Westmead Millennium Inst, Sydney W Area Hlth Serv, Sydney, NSW 2145, AustraliaPeter MacCallum Canc Ctr, Dept Pathol, Melbourne, Vic 3002, AustraliaUniv Queensland, Queensland Brain Inst, Brisbane, Qld 4072, AustraliaRoyal Brisbane & Womens Hosp, Brisbane, Qld 4029, AustraliaUniversidade Federal de São Paulo, EPM, Dept Anat Patol, BR-04024000 São Paulo, BrazilWeb of Scienc

    Analysis of cancer risk and BRCA1 and BRCA2 mutation prevalence in the kConFab familial breast cancer resource

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    INTRODUCTION: The Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer (kConFab) is a multidisciplinary, collaborative framework for the investigation of familial breast cancer. Based in Australia, the primary aim of kConFab is to facilitate high-quality research by amassing a large and comprehensive resource of epidemiological and clinical data with biospecimens from individuals at high risk of breast and/or ovarian cancer, and from their close relatives. METHODS: Epidemiological, family history and lifestyle data, as well as biospecimens, are collected from multiple-case breast cancer families ascertained through family cancer clinics in Australia and New Zealand. We used the Tyrer-Cuzick algorithms to assess the prospective risk of breast cancer in women in the kConFab cohort who were unaffected with breast cancer at the time of enrolment in the study. RESULTS: Of kConFab's first 822 families, 518 families had multiple cases of female breast cancer alone, 239 had cases of female breast and ovarian cancer, 37 had cases of female and male breast cancer, and 14 had both ovarian cancer as well as male and female breast cancer. Data are currently held for 11,422 people and germline DNAs for 7,389. Among the 812 families with at least one germline sample collected, the mean number of germline DNA samples collected per family is nine. Of the 747 families that have undergone some form of mutation screening, 229 (31%) carry a pathogenic or splice-site mutation in BRCA1 or BRCA2. Germline DNAs and data are stored from 773 proven carriers of BRCA1 or BRCA1 mutations. kConFab's fresh tissue bank includes 253 specimens of breast or ovarian tissue – both normal and malignant – including 126 from carriers of BRCA1 or BRCA2 mutations. CONCLUSION: These kConFab resources are available to researchers anywhere in the world, who may apply to kConFab for biospecimens and data for use in ethically approved, peer-reviewed projects. A high calculated risk from the Tyrer-Cuzick algorithms correlated closely with the subsequent occurrence of breast cancer in BRCA1 and BRCA2 mutation positive families, but this was less evident in families in which no pathogenic BRCA1 or BRCA2 mutation has been detected

    Refined histopathological predictors of BRCA1 and BRCA2 mutation status: A large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia

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    Introduction: The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling. Methods: Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the

    Refined histopathological predictors of BRCA1 and BRCA2 mutation status : a large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia

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    Abstract Introduction The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling. Methods Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the likelihood of mutation status by histopathological markers were derived using a Mantel-Haenszel approach. Results ER-positive phenotype negatively predicted BRCA1 mutation status, irrespective of grade (LRs from 0.08 to 0.90). ER-negative grade 3 histopathology was more predictive of positive BRCA1 mutation status in women 50 years or older (LR = 4.13 (3.70 to 4.62)) versus younger than 50 years (LR = 3.16 (2.96 to 3.37)). For BRCA2, ER-positive grade 3 phenotype modestly predicted positive mutation status irrespective of age (LR = 1.7-fold), whereas ER-negative grade 3 features modestly predicted positive mutation status at 50 years or older (LR = 1.54 (1.27 to 1.88)). Triple-negative tumor status was highly predictive of BRCA1 mutation status for women younger than 50 years (LR = 3.73 (3.43 to 4.05)) and 50 years or older (LR = 4.41 (3.86 to 5.04)), and modestly predictive of positive BRCA2 mutation status in women 50 years or older (LR = 1.79 (1.42 to 2.24)). Conclusions These results refine likelihood-ratio estimates for predicting BRCA1 and BRCA2 mutation status by using commonly measured histopathological features. Age at diagnosis is an important variable for most analyses, and grade is more informative than ER status for BRCA2 mutation carrier prediction. The estimates will improve BRCA1 and BRCA2 variant classification and inform patient mutation testing and clinical management

    Common germline polymorphisms associated with breast cancer-specific survival

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    Abstract Introduction Previous studies have identified common germline variants nominally associated with breast cancer survival. These associations have not been widely replicated in further studies. The purpose of this study was to evaluate the association of previously reported SNPs with breast cancer-specific survival using data from a pooled analysis of eight breast cancer survival genome-wide association studies (GWAS) from the Breast Cancer Association Consortium. Methods A literature review was conducted of all previously published associations between common germline variants and three survival outcomes: breast cancer-specific survival, overall survival and disease-free survival. All associations that reached the nominal significance level of P value <0.05 were included. Single nucleotide polymorphisms that had been previously reported as nominally associated with at least one survival outcome were evaluated in the pooled analysis of over 37,000 breast cancer cases for association with breast cancer-specific survival. Previous associations were evaluated using a one-sided test based on the reported direction of effect. Results Fifty-six variants from 45 previous publications were evaluated in the meta-analysis. Fifty-four of these were evaluated in the full set of 37,954 breast cancer cases with 2,900 events and the two additional variants were evaluated in a reduced sample size of 30,000 samples in order to ensure independence from the previously published studies. Five variants reached nominal significance (P <0.05) in the pooled GWAS data compared to 2.8 expected under the null hypothesis. Seven additional variants were associated (P <0.05) with ER-positive disease. Conclusions Although no variants reached genome-wide significance (P <5 x 10−8), these results suggest that there is some evidence of association between candidate common germline variants and breast cancer prognosis. Larger studies from multinational collaborations are necessary to increase the power to detect associations, between common variants and prognosis, at more stringent significance levels
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