Evaluating the performance of the breast cancer genetic risk models BOADICEA, IBIS, BRCAPRO and Claus for predicting<i>BRCA1/2</i>mutation carrier probabilities: a study based on 7352 families from the German Hereditary Breast and Ovarian Cancer Consortium

Fischer, Christine; Kuchenbäcker, Karoline; Engel, Christoph; Zachariae, Silke; Rhiem, Kerstin; Meindl, Alfons; Rahner, Nils; Dikow, Nicola; Plendl, Hansjörg; Debatin, Irmgard; Grimm, Tiemo; Gadzicki, Dorothea; Flöttmann, Ricarda; Horváth, Judit; Schröck, Evelin; Stock, Friedrich; Schäfer, Dieter; Schwaab, Ira; Kartsonaki, Christiana; Mavaddat, Nasim; Schlegelberger, Brigitte; Antoniou, Antonis C.; Schmutzler, Rita K.

doi:10.1136/jmedgenet-2012-101415

Cited by 84 publications

(74 citation statements)

References 36 publications

(36 reference statements)

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“…Mutation analysis was described by Fischer et al [13] and was performed at a German center for BRCA1 mutation testing (Technical University of Munich, Munich, Germany) according to a standardized protocol. Briefly, high performance liquid chromatography (dHPLC) and sequencing of conspicuous amplicons was employed thus to analyze PCR products comprising all coding exons of BRCA1 .…”

Section: Methodsmentioning

confidence: 99%

Vitamin D receptor, Retinoid X receptor and peroxisome proliferator-activated receptor γ are overexpressed in BRCA1 mutated breast cancer and predict prognosis

Heublein

Mayr

Meindl

et al. 2017

J Exp Clin Cancer Res

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Background BRCA1 mutated breast cancers are commonly diagnosed as negative for classical hormone receptors i.e. estrogen receptor, progesterone receptor and/or Her2. Due to these common targets being absent the application of anti-endocrine therapies is rather limited and a certain focus has been set on discovering alternative target molecules. We recently highlighted thyroid hormone receptors (TRs) to predict prognosis in breast cancer patients that had been diagnosed a BRCA1 germline mutation. Vitamin D Receptor (VDR), Retinoid X Receptor (RXR) and Peroxisome Proliferator-activated Receptor γ (PPARγ) are known to interact with TRs by forming functional heterodimers. Whether VDR, RXR or PPARγ are expressed in BRCA1 mutated breast cancer or may even be present in case of triple negativity is not known. Hence the current study aimed to investigate VDR, RXR and PPARγ in BRCA1 mut breast cancer and to test whether any of the three may be associated with clinico-pathological criteria including overall survival.MethodsThis study analyzed VDR, RXR and PPARγ by immunohistochemistry in BRCA1 associated (n = 38) and sporadic breast cancer (n = 79). Receptors were quantified by applying an established scoring system (IR-score) and were tested for association with clinico-pathological variables.ResultsVDR, RXR and PPARγ were detected in over 90% of triple negative BRCA1 mut breast cancer and were significantly (VDR: p < 0.001, RXR: p = 0.010, PPARγ: p < 0.001) overexpressed in BRCA1 mutated as compared to sporadic cancer cases. VDR and RXR positivity predicted prolonged overall survival only in BRCA1 mutated cases while such association was not observed in sporadic breast cancer.ConclusionsIn conclusion, this is the first study to describe VDR, RXR and PPARγ in BRCA1 mutated breast cancer. Based on the data presented here these receptors may be hypothesized to potentially evolve as interesting markers or even targets in hereditary breast cancer. However, independent studies are indispensable thus to confirm this hypothesis.Electronic supplementary materialThe online version of this article (doi:10.1186/s13046-017-0517-1) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

Vitamin D receptor, Retinoid X receptor and peroxisome proliferator-activated receptor γ are overexpressed in BRCA1 mutated breast cancer and predict prognosis

Heublein

Mayr

Meindl

et al. 2017

J Exp Clin Cancer Res

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“…More importantly, for those individuals testing negative for a BRCA1/2 mutation screen who do not have cancer, and are from a family without testing of an affected member, it is not possible to assess the degree of reassurance of a negative test without knowledge of the likelihood that their affected relative was a BRCA1 or BRCA2 mutation carrier. Attempts have been made to incorporate breast pathology into risk algorithms such as the Manchester scoring system [10] and BOADICEA [11, 12] and these improve the accuracy of likelihood estimates and risk thresholds [10, 13]. Periodic revisions of these scoring systems are useful, as most ‘classical’ high penetrance BRCA mutation carrier families will have been identified, leaving less classical phenotypes to be uncovered.…”

Section: Introductionmentioning

confidence: 99%

Risk algorithms that include pathology adjustment for HER2 amplification need to make further downward adjustments in likelihood scores

et al. 2016

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To assess the need for adjustment in the likelihood of germline BRCA1/2 mutations in women with HER2+ breast cancers. We analysed primary mutation screens on women with breast cancer with unequivocal HER2 overexpression and assessed the likelihood of BRCA1/BRCA2 mutations by age, oestrogen receptor status and Manchester score. Of 1111 primary BRCA screens with confirmed HER2 status only 4/161 (2.5%) of women with HER2 amplification had a BRCA1 mutation identified and 5/161 (3.1%) a BRCA2 mutation. The pathology adjusted Manchester score between 10 and 19% and 20%+ thresholds resulted in a detection rate of only 6.5 and 15% respectively. BOADICEA examples appeared to make even less downward adjustment. There is a very low detection rate of BRCA1 and BRCA2 mutations in women with HER2 amplified breast cancers. The Manchester score and BOADICEA do not make sufficient downward adjustment for HER2 amplification. For unaffected women, assessment of breast cancer risk and BRCA1/2 probability should take into account the pathology of the most relevant close relative. Unaffected women undergoing mutation testing for BRCA1/2 should be advised that there is limited reassurance from a negative test result if their close relative had a HER2+ breast cancer.

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“…Using data from CIMBA and BCAC, we were able to include age-specific distributions of ER and TN status for mutation carriers and the general population. A recent evaluation of BOADICEA for its ability to predict BRCA1 and BRCA2 carrier status showed that the updated BOADICEA model incorporating tumour pathology information, based on the CIMBA/BCAC data distributions, provided a significant improvement in discrimination and re-classification over the previous BOADICEA model without pathology, and that the updated BOADICEA model also performed better than the previous BOADICEA model that incorporated tumour pathology information based primarily on the BCLC data (Fischer et al , 2013). These results suggest that the updated BOADICEA model is a valid tool for use in genetic counselling.…”

Section: Discussionmentioning

confidence: 99%

BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface

et al. 2013

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Background:The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) is a risk prediction model that is used to compute probabilities of carrying mutations in the high-risk breast and ovarian cancer susceptibility genes BRCA1 and BRCA2, and to estimate the future risks of developing breast or ovarian cancer. In this paper, we describe updates to the BOADICEA model that extend its capabilities, make it easier to use in a clinical setting and yield more accurate predictions.Methods:We describe: (1) updates to the statistical model to include cancer incidences from multiple populations; (2) updates to the distributions of tumour pathology characteristics using new data on BRCA1 and BRCA2 mutation carriers and women with breast cancer from the general population; (3) improvements to the computational efficiency of the algorithm so that risk calculations now run substantially faster; and (4) updates to the model's web interface to accommodate these new features and to make it easier to use in a clinical setting.Results:We present results derived using the updated model, and demonstrate that the changes have a significant impact on risk predictions.Conclusion:All updates have been implemented in a new version of the BOADICEA web interface that is now available for general use: http://ccge.medschl.cam.ac.uk/boadicea/.

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Evaluating the performance of the breast cancer genetic risk models BOADICEA, IBIS, BRCAPRO and Claus for predictingBRCA1/2mutation carrier probabilities: a study based on 7352 families from the German Hereditary Breast and Ovarian Cancer Consortium

Cited by 84 publications

References 36 publications

Vitamin D receptor, Retinoid X receptor and peroxisome proliferator-activated receptor γ are overexpressed in BRCA1 mutated breast cancer and predict prognosis

Vitamin D receptor, Retinoid X receptor and peroxisome proliferator-activated receptor γ are overexpressed in BRCA1 mutated breast cancer and predict prognosis

Risk algorithms that include pathology adjustment for HER2 amplification need to make further downward adjustments in likelihood scores

BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface

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