Zusammenfassung
Hintergrund
Nicht für alle Trägerinnen einer Mutation in den Genen BRCA1 und BRCA2 liegt das lebenslange Erkrankungsrisiko für Brust- oder Eierstockkrebs gleich hoch. Bislang werden bei der Indikationsstellung zur Teilnahme an intensivierten Früherkennungs- und Nachsorgeprogrammen oder zur Durchführung einer prophylaktischen Operation keine risikomodifizierenden Faktoren berücksichtigt.
Fragestellung
Welche genetischen und nichtgenetischen Einflussfaktoren beeinflussen das Mammakarzinomrisiko von Anlageträgerinnen, und welche davon werden in den gebräuchlichen Risikoberechnungsprogrammen bereits berücksichtigt?
Ergebnisse und Diskussion
In genomweiten Assoziationstudien wurden Niedrigrisikovarianten gefunden und validiert. Einige davon modulieren das Risiko beim sporadischen und beim BRCA-assoziierten Mammakarzinom, es gibt für jeden Typ aber auch spezifische Varianten. Es gibt erste Studien, die vermuten lassen, dass Lebensstilfaktoren und reproduktive Faktoren das Risiko für BRCA-assoziierte Tumoren modulieren. Den bisherigen Rechenmodellen zur Schätzung des individuellen Risikos liegen eine variable Zahl hoch penetranter Gene und die Erhebung des Stammbaumes über 3 Generationen zugrunde. Zum Teil werden auch klinische Daten, wie Voroperationen, Tumorhistologie, Reproduktionsfaktoren oder „body mass index“ berücksichtigt. Die Erforschung der modifizierenden genetischen und nichtgenetischen Faktoren führt zur Erstellung eines umfassenden Risikoberechnungsprogramms. Dieses hat zum einen die Vermeidung von Übertherapie im Hinblick auf präventive Maßnahmen zum Ziel. Zum anderen bereitet die Kenntnis der individuellen Trigger einer potenziellen Brust- oder Eierstockkrebserkrankung den Weg für eine gezieltere Prävention von der medikamentösen Therapie bis hin zur Lebensstilintervention.
Abstract
Background
The lifelong risk for breast cancer and ovarian cancer differs among carriers of mutations in the BRCA1 and BRCA2 genes. Cancer risk is modulated by a multitude of genetic and non-genetic factors. For the decision on intensified surveillance or prophylactic mastectomy no risk modifiers are so far taken into account.
Aims
This article examines whether genetic and non-genetic factors modify the risk of breast cancer for BRCA1 and BRCA2 gene mutation carriers and which are integrated into currently used risk calculation programs.
Results and discussion
A number of genetic low risk variants have been identified and validated in genome-wide association studies. Several of these modify the risk of sporadic and BRCA-associated breast cancer and others are specific for each type. The results of initial studies suggest that lifestyle factors and reproductive history can also modify the risk of breast cancer for BRCA-associated tumors. Current risk calculation programs estimate the individual cancer risk based on assumptions on major genes with high penetrance and on the family pedigree over three generations. Some of these also take clinical data, such as previous operations, histopathological features of tumors, reproductive factors and body mass index into account but no explicit low risk variants. Ongoing research on modifying genetic and non-genetic risk factors aims to establish a more differentiated and comprehensive risk prediction model in order to prevent overtreatment with respect to preventive strategies. Additionally, knowledge on individual trigger mechanisms of potential breast or ovarian cancer might lead to targeted prevention by medicinal therapy and lifestyle interventions.
Literatur
Amir E, Evans DG, Shenton A et al (2003) Evaluation of breast cancer risk assessment packages in the family history evaluation and screening programme. J Med Genet 40:807–814
Andrieu N, Goldgar DE, Easton DF et al (2006) Pregnancies, breast-feeding, and breast cancer risk in the International BRCA1/2 Carrier Cohort Study (IBCCS). J Natl Cancer Inst 98:535–544
Antoniou AC, Beesley J, Mcguffog L et al (2010) Common breast cancer susceptibility alleles and the risk of breast cancer for BRCA1 and BRCA2 mutation carriers: implications for risk prediction. Cancer Res 70:9742–9754
Lee AJ, Cunningham AP, Kuchenbaecker KB et al (2014) BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface. Br J Cancer 110:535–545
Atchley DP, Albarracin CT, Lopez A et al (2008) Clinical and pathologic characteristics of patients with BRCA-positive and BRCA-negative breast cancer. J Clin Oncol 26:4282–4288
Barnes DR, Antoniou AC (2012) Unravelling modifiers of breast and ovarian cancer risk for BRCA1 and BRCA2 mutation carriers: update on genetic modifiers. J Intern Med 271(4):331–343
Berg WA, Zhang Z, Lehrer D et al (2012) Detection of breast cancer with addition of annual screening ultrasound or a single screening MRI to mammography in women with elevated breast cancer risk. JAMA 307:1394–1404
Biswas S, Tankhiwale N, Blackford A et al (2012) Assessing the added value of breast tumor markers in genetic risk prediction model BRCAPRO. Breast Cancer Res Treat 133:347–355
Brohet RM, Goldgar DE, Easton DF et al (2007) Oral contraceptives and breast cancer risk in the international BRCA1/2 carrier cohort study: a report from EMBRACE, GENEPSO, GEO-HEBON, and the IBCCS Collaborating Group. J Clin Oncol 25:3831–3836
Chang-Claude J, Andrieu N, Rookus M et al (2007) Age at menarche and menopause and breast cancer risk in the International BRCA1/2 Carrier Cohort Study. Cancer Epidemiol Biomarkers Prev 16:740–746
Chen S, Wang W, Broman KW et al (2004) BayesMendel: an R environment for Mendelian risk prediction. Stat Appl Genet Mol Biol 3:Article21
Claus EB, Risch N, Thompson WD (1991) Genetic analysis of breast cancer in the cancer and steroid hormone study. Am J Hum Genet 48:232–242
Couch FJ, Gaudet MM, Antoniou AC et al (2012) Common variants at the 19p13.1 and ZNF365 loci are associated with ER subtypes of breast cancer and ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. Cancer Epidemiol Biomarkers Prev 21(4):645–657
Fischer C, Kuchenbacker K, Engel C et al (2013) Evaluating the performance of the breast cancer genetic risk models BOADICEA, IBIS, BRCAPRO and Claus for predicting BRCA1/2 mutation carrier probabilities: a study based on 7352 families from the German Hereditary Breast and Ovarian Cancer Consortium. J Med Genet 50(6):360–367
Friedenreich CM (2011) Physical activity and breast cancer: review of the epidemiologic evidence and biologic mechanisms. Recent Results Cancer Res 188:125–139
Gail MH (2009) Value of adding single-nucleotide polymorphism genotypes to a breast cancer risk model. J Natl Cancer Inst 101:959–963
Gaudet MM, Kirchhoff T, Green T et al (2010) Common genetic variants and modification of penetrance of BRCA2-associated breast cancer. PLoS Genet 6:e1001183
Gaudet MM, Kuchenbaecker KB, Vijai J et al (2013) Identification of a BRCA2-specific modifier locus at 6p24 related to breast cancer risk. PLoS Genet 9:e1003173
Irwin ML, Mctiernan A, Manson JE et al (2011) Physical activity and survival in postmenopausal women with breast cancer: results from the women’s health initiative. Cancer Prev Res (Phil) 4:522–529
Kast K, Schmutzler RK, Rhiem K et al (2014) Validation of the Manchester scoring system for predicting BRCA1/2 mutations in 9,390 families suspected of having hereditary breast and ovarian cancer. Int J Cancer
Key TJ, Verkasalo PK, Banks E (2001) Epidemiology of breast cancer. Lancet Oncol 2:133–140
King MC, Marks JH, Mandell JB (2003) Breast and ovarian cancer risks due to inherited mutations in BRCA1 and BRCA2. Science 302:643–646
Laitman Y, Simeonov M, Keinan-Boker L et al (2013) Breast cancer risk prediction accuracy in Jewish Israeli high-risk women using the BOADICEA and IBIS risk models. Genet Res 95:174–177
Lee AJ, Cunningham AP, Kuchenbaecker KB et al (2014) BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface. Br J Cancer 110:535–545
Leitzmann MF, Moore SC, Peters TM et al (2008) Prospective study of physical activity and risk of postmenopausal breast cancer. Breast Cancer Res 10:R92
Macinnis RJ, Antoniou AC, Eeles RA et al (2011) A risk prediction algorithm based on family history and common genetic variants: application to prostate cancer with potential clinical impact. Genet Epidemiol 35:549–556
Manders P, Pijpe A, Hooning MJ et al (2011) Body weight and risk of breast cancer in BRCA1/2 mutation carriers. Breast Cancer Res Treat 126:193–202
Matsuno RK, Costantino JP, Ziegler RG et al (2011) Projecting individualized absolute invasive breast cancer risk in Asian and Pacific Islander American women. J Natl Cancer Inst 103:951–961
Mavaddat N, Peock S, Frost D et al (2013) Cancer risks for BRCA1 and BRCA2 mutation carriers: results from prospective analysis of EMBRACE. J Natl Cancer Inst 105:812–822
Narod SA, Goldgar D, Cannon-Albright L et al (1995) Risk modifiers in carriers of BRCA1 mutations. Int J Cancer 64:394–398
Phillips KA, Milne RL, Rookus MA et al (2013) Tamoxifen and risk of contralateral breast cancer for BRCA1 and BRCA2 mutation carriers. J Clin Oncol 31:3091–3099
Quante AS, Whittemore AS, Shriver T et al (2012) Breast cancer risk assessment across the risk continuum: genetic and nongenetic risk factors contributing to differential model performance. Breast Cancer Res 14:R144
Rhiem K, Engel C, Graeser M et al (2012) The risk of contralateral breast cancer in patients from BRCA1/2 negative high risk families as compared to patients from BRCA1 or BRCA2 positive families: a retrospective cohort study. Breast Cancer Res 14:R156
Russo J, Lynch H, Russo IH (2001) Mammary gland architecture as a determining factor in the susceptibility of the human breast to cancer. Breast J 7:278–291
Tyrer J, Duffy SW, Cuzick J (2004) A breast cancer prediction model incorporating familial and personal risk factors. Stat Med 23:1111–1130
Wooster R, Neuhausen SL, Mangion J et al (1994) Localization of a breast cancer susceptibility gene, BRCA2, to chromosome 13q12-13. Science 265:2088–2090
Ferlay J, Soerjomataram I, Ervik M et al (2013) GLOBOCAN 2012 v1.0, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 11. International Agency for Research on Cancer, Lyon. http://globocan.iarc.fr. Zugegriffen: 30. May 2014
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Interessenkonflikt. K. Kast und C. Fischer geben an, dass kein Interessenkonflikt besteht. Dieser Beitrag beinhaltet keine Studien an Menschen oder Tieren.
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Kast, K., Fischer, C. BRCA1 und BRCA2 − genetische und nichtgenetische Einflussfaktoren. Gynäkologe 47, 759–768 (2014). https://doi.org/10.1007/s00129-014-3350-z
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DOI: https://doi.org/10.1007/s00129-014-3350-z