Role of IkappaB kinase beta in inflammation-mediated breast cancer development

Breast cancer is the second most common farm of cancers and the second leading cause of cancer death for American women. Clinical studies indicate inflammation is a risk factor for breast cancer development. Among the cytokines and chemokines secreted by the infiltrating inflammatory cells, tumor necrosis factor a (TNFα) is considered one of the most important inflammatory factors involved in inflammation-mediated tumorigenesis. ^ Here we found that TNFα/IKKβ signaling pathway is able to increase tumor angiogenesis through activation of mTOR pathway. While investigating which molecule in the mTOR pathway involved in TNFα/IKKβ-mediated mTOR activation, our results showed that IKKβ physically interacts with and phosphorylates TSC1 at Ser487 and Ser511 in vitro and in vivo. Phosphorylation of TSC1 by IKKβ inhibits its association with TSC2, alters TSC2 membrane localization, and thereby activates mTOR. In vitro angiogenesis assays and orthotopic breast cancer model reveals that phosphorylation of TSC1 by IKKβ enhances VEGF expression, angiogenesis and culminates in tumorigenesis. Furthermore, expression of activated IKKβ is associated with TSC1 Ser511 phosphorylation and VEGF production in multiple tumor types and correlates with poor clinical outcome of breast cancer patients. ^ Furthermore, dysregulation of tumor suppressor FOXO3a contributes to the development of breast cancer. We found that overexpression of IKKβ led to inhibition of FOXO3a-mediated transactivation activity. While investigating the underlying mechanisms of IKKβ-mediated dysregulation of FOXO3a, our results showed that IKKβ physically associated with FOXO3a and phosphorylated FOXO3a at Ser644 in vitro and in vivo. The phosphorylation of FOXO3a by IKKβ altered its subcellular localization from nucleus to cytoplasm and promoted its degradation through ubiquitin-proteasome pathway. Mutation of FOXO3a at Ser644 prevented IKKβ-induced ubiquitination and degradation. In vitro cell proliferation assay and orthotopic breast cancer model revealed that phosphorylation of FOXO3a by IKKβ overrode FOXO3a-mediated repression of tumor progression. ^ In conclusion, our findings identify IKKβ-mediated suppressions of both TSC1 and FOXO3a are critical for inflammation-mediated breast cancer development through increasing tumor angiogenesis and evading apoptosis, respectively. Understanding the role of IKKβ in both FOXO3a and TSC/mTOR signaling pathways provides a critical insight of inflammation-mediated diseases and may provide a target for clinical intervention in human breast cancer. ^

Cardiovascular diseases risk factors during the first year of life

The pattern of change in cardiovascular risk factors, blood pressure (SBP and DBP) and plasma total cholesterol (TC), over time, their tracking and their relation to anthropometric measurements during the first year of life were investigated. Also, the effect of breast feeding on TC and the relationship of blood pressure measurements and family history of CVD risk factors were examined. One hundred five newborn term, healthy infants who were seen at a pediatric clinic in The Woodlands, Texas were followed longitudinally from 2 weeks to 1 year of age. TC, blood pressure, weight and length of the infants were measured at age 2 weeks, and again at 2, 4, 6, 9 and 12 months. In addition, family history, maternal and paternal, of CVD risk factors was obtained. Data analyses included only 40 infants who completed one year of follow up.^ At 2 weeks of age, the median value for TC was 23 mg/dl higher for females than for males. This difference disappeared as infants got older. For males, most of the increase in TC median levels, from 114 to 137 mg/dl, occurred between the ages of 2 weeks and 2 months, whereas for the female group, TC levels increased moderately, about 10 mg/dl, between 9 and 12 months of age. Tracking of TC was examined by using Spearman's correlation analysis. There were strong correlations between measurements taken as early as 2 weeks of age with later measurements. These correlations were stronger and more significant for males than for females (for males, r varied between 0.51 to 0.70, whereas for females, r varied between 0.11 to 0.70). The association of body measurements with TC is no more than modest and is closer for female infants than for male infants. Analysis, also, showed that infants who received breast milk had a TC mean value 47 mg/dl higher than that for infants who received formula milk only during the period of breast feeding and this difference disappeared by age 12 months.^ In both genders, most of the increase in blood pressure (about 10-15 mmHg in both SBP and DBP) occurred during the first 4 months of life. Most of the increase for male infants occurred during the first 2 months of life, while for females, the increase in SBP and DBP was between the age of 2 and 4 months. Neither SBP nor DBP track well during the first year of life and most of the correlations between measurements at different ages were not significant for either gender. The cross-sectional relationship of blood pressure measurements and selected body measurements was assessed. For females, only at age of 12 months did DBP have positive and significant correlations with weight, length and Quetelet index (r = 0.57, 0.60 and 0.57, respectively). There were no significant correlations between blood pressure and body measurements for males. Finally, analysis showed that maternal history of CV risk factors was significantly related to SBP in the female infant group, but not for males. For DBP, neither maternal nor paternal history was related. ^

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.