Biomedical subjects

George Bonney

Publications and source records attributed to George Bonney.

3 recordsLinked to original sources

PubMed2006

Expression of carcinoembryonic antigen cell adhesion molecule 6 oncoprotein in atypical ductal hyperplastic tissues is associated with the development of invasive breast cancer.

BACKGROUND: Epidemiologic studies have established that women with prior atypical ductal hyperplastic (ADH) lesions have a 5-fold increased risk of developing invasive breast cancer (IBC). However, there is currently no means of identifying a subclass of ADH from women who will most likely develop cancer. The purpose of this study is to investigate whether elevated expression of carcinoembryonic antigen cell adhesion molecule 6 (CEACAM6) in ADH tissues is associated with the development of IBC. METHODS: A retrospective study was conducted with archival ADH tissues and clinical information on the development/nondevelopment of IBC. The control group was ADH from patients who had no prior history of IBC and did not develop cancer within 5 years after the diagnosis of ADH (n = 44). The test group was ADH from patients who either developed cancer concurrently or subsequently after diagnosis (ADHC; n = 44). The expression of CEACAM6 was studied by immunohistochemistry and the results were statistically analyzed for significant association to develop cancer (P value), specificity, sensitivity, positive predictive value, and negative predictive value. RESULTS: Of the 44 control ADH tissues from patients with no history of cancer, 9 were positive for CEACAM6. Among the ADHC tissues, 40 of 44 samples were positive. Statistical analysis of CEACAM6 expression data showed a significant association between its expression and cancer development, high sensitivity, specificity, positive predictive value, and negative predictive value. CONCLUSIONS: The expression of CEACAM6 in ADH lesions is strongly associated with the development of IBC, therefore, it can be applied as a diagnostic marker either singly or in combination with other marker(s) to predict IBC development in women with ADH lesions. It could also be a potential molecular therapeutic target for preventing IBC.

Adult↗

PubMed2006

Detecting disease gene in DNA haplotype sequences by nonparametric dissimilarity test.

Association studies for complex diseases based on haplotype data have received increasing attention in the last few years. A commonly used nonparametric method, which takes haplotype structure into consideration, is to use the U-statistic to compare the similarities between genetic compositions in the case and control populations. Although the method and its variants are convenient to use in practice, there are some areas where the tests cannot detect even large differences between cases and controls. To overcome this problem and enhance the power, we propose a new form of the weighted U-statistic, which directly compares the dissimilarity between the haplotype structures in the case and control populations. We show that this test statistic is asymptotically a linear combination of the absolute values of normal random variables under the null hypothesis, and shifts strictly toward the right under the alternative, and therefore has no blind areas of detection. Simulation studies indicate that our test statistic overcomes the weakness of the existing ones and is robust and powerful as well.

Base Sequence↗

PubMed2006

Variance components model with disequilibria.

The variance components (VC) model has been popular for genetic analysis. It has received wide applications in a variety of genetic practices, and been extended to various forms for different settings. However, most of the existing VC models are, explicitly or implicitly, under the assumption of the Hardy-Weinberg and/or linkage equilibria, which is impractical in some realistic settings since more or less deviations from this assumption are common. We propose a new VC model that incorporates both these disequilibria, and includes the existing models as special cases. The corresponding variance components are computed for some commonly used relative pairs conditional on the observed marker identity-by-descent data. Parameters can be estimated by the traditional methods such as the maximum likelihood estimate. Simulation studies suggest that this extended model improves inference significantly over the existing models when deviations of these disequilibria are present.

Analysis of Variance↗