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Gerger, A; Langsenlehner, U; Renner, W; Weitzer, W; Eder, T; Yazdani-Biuki, B; Hofmann, G; Samonigg, H; Krippl, P.
A multigenic approach to predict breast cancer risk.
Breast Cancer Res Treat. 2007; 104(2):159-164 Doi: 10.1007/s10549-006-9408-4
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Führende Autor*innen der Med Uni Graz
Gerger Armin
Co-Autor*innen der Med Uni Graz
Hofmann Guenter
Krippl Peter
Langsenlehner Tanja
Langsenlehner Uwe
Renner Wilfried
Samonigg Hellmut
Weitzer Werner
Yazdani-Biuki Babak

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In the biology of complex disorders, such as breast cancer, interactions among genetic factors may play an important role and theoretical considerations suggest that gene-gene interactions are quite common in such diseases. In this case-control study with 500 breast cancer patients and 500 population-based healthy sex- and age-matched control subjects, we applied a multigenic approach to examine the associations with breast cancer risk of a comprehensive panel of 16 selected polymorphisms in a variety of pathways using classification tree analysis (CART). Overall, 79.6% of all breast cancer patients and 80.6% of all control subjects were correctly classified on the basis of their individual genetic profile by the classification procedure. CART analysis of the data identified the heterozygous vascular endothelial growth factor (VEGF) and matrix metalloproteinase 3 (MMP3) genotype and homozygous cyclooxygenase-2 (PTGS2) mutant as the initial splits, indicating that these genotypes exert the greatest impact on the classification process. Breast cancer patients were primarily indicated by 30 distinct genetic profiles. The odds ratio of these genetic risk profiles for breast cancer was 16.12 (95% confidence interval 11.09-23.49). Five genetic profiles formed homogenous breast cancer subgroups and represented highest risk genetic profiles. This is the first comprehensive study to use a multigenic analysis for breast cancer and the data suggest that individuals with distinct genetic profiles are at an increased risk for breast cancer, confirming the importance of taking a multigenic approach for risk assessment.
Find related publications in this database (using NLM MeSH Indexing)
Breast - metabolism
Breast Neoplasms - genetics
Case-Control Studies - genetics
Female - genetics
Genetic Predisposition to Disease - genetics
Genotype - genetics
Humans - genetics
Polymorphism, Genetic - genetics
Risk Factors - genetics
Tumor Markers, Biological - genetics

Find related publications in this database (Keywords)
breast cancer
classification tree
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