Identifying individuals at high risk of cancer because of inherited genetic susceptibility is complex and increasingly important. Probabilistic prediction algorithms that exploit domain knowledge of Mendelian inheritance and other biological characteristics of susceptibility genes successfully contribute to improved screening, prevention, and genetic testing, and to the design and analysis of cancer studies. The investigators have developed, validated, applied and disseminated the widely used Mendelian model BRCAPRO. Based on their experience they have identified the need for a new generation of Mendelian prediction models in cancer genetics.
The first aim will develop statistical approaches that generalize Mendelian models currently used in clinical genetic counseling practice. Innovation will focus on five areas: A) accounting for errors in reported pedigrees; B) accounting for dependencies in time-to-event distributions for multiple cancer sites; C) accounting for familial correlations arising from shared environmental factors or other sources; D) accounting for multiallelic syndromes; and E) incorporating information on covariates and on biomarkers related to the genes' activity.
The second aim will introduce a novel class of multi-syndrome models to simultaneously identify cancer syndromes and predict mutation carrier status. These will enable clinicians and researchers to address the emerging challenges posed by the overlap in phenotype for cancer susceptibility genes, and by the high frequency of sporadic families with multiple sites.
The third aim will develop flexible user-friendly software for the application of the methods in both research and clinical settings.
The aims of this proposal will overcome pressing practical limitations of tools currently used in clinical genetic counseling, and thus contribute to improved screening, prevention and decision making about genetic testing.
| Wang, Wenyi; Niendorf, Kristin B; Patel, Devanshi et al. (2010) Estimating CDKN2A carrier probability and personalizing cancer risk assessments in hereditary melanoma using MelaPRO. Cancer Res 70:552-9 |
| Chen, Sining; Blackford, Amanda L; Parmigiani, Giovanni (2009) Tailoring BRCAPRO to Asian-Americans. J Clin Oncol 27:642-3; author reply 643-4 |
| Lin, Xue; Afsari, Bahman; Marchionni, Luigi et al. (2009) The ordering of expression among a few genes can provide simple cancer biomarkers and signal BRCA1 mutations. BMC Bioinformatics 10:256 |
| Wang, Wenyi; Carvalho, Benilton; Miller, Nathaniel D et al. (2008) Estimating genome-wide copy number using allele-specific mixture models. J Comput Biol 15:857-66 |
| Katki, Hormuzd A; Blackford, Amanda; Chen, Sining et al. (2008) Multiple diseases in carrier probability estimation: accounting for surviving all cancers other than breast and ovary in BRCAPRO. Stat Med 27:4532-48 |
| Lin, Jimmy; Gan, Christine M; Zhang, Xiaosong et al. (2007) A multidimensional analysis of genes mutated in breast and colorectal cancers. Genome Res 17:1304-18 |
| Tai, Yu Chuan; Domchek, Susan; Parmigiani, Giovanni et al. (2007) Breast cancer risk among male BRCA1 and BRCA2 mutation carriers. J Natl Cancer Inst 99:1811-4 |
| Iversen Jr, Edwin S; Katki, Hormuzd A; Chen, Sining et al. (2007) Limited family structure and breast cancer risk. JAMA 298:2007;author reply 2007-8 |
| Chen, Sining; Parmigiani, Giovanni (2007) Meta-analysis of BRCA1 and BRCA2 penetrance. J Clin Oncol 25:1329-33 |
| Katki, Hormuzd A (2007) Incorporating medical interventions into carrier probability estimation for genetic counseling. BMC Med Genet 8:13 |
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