A Bayesian analysis for spatial processes with application to mapping

In geographical epidemiology, maps of disease rates and disease risk provide a spatial perspective for researching disease etiology. For rare diseases or when the population base is small, the rate and risk estimates may be unstable. Empirical Bayesian (EB) methods have been used to spatially smooth the estimates by permitting an area estimate to "borrow strength" from its neighbors. Such EB methods include the use of a Gamma model, of a James-Stein estimator, and of a conditional autoregressive (CAR) process. A fully Bayesian analysis of the CAR process is proposed. One advantage of this fully Bayesian analysis is that it can be implemented simply by using repeated sampling from the posterior densities. Use of a Markov chain Monte Carlo technique such as Gibbs sampler was not necessary. Direct resampling from the posterior densities provides exact small sample inferences instead of the approximate asymptotic analyses of maximum likelihood methods (Clayton & Kaldor, 1987). Further, the proposed CAR model provides for covariates to be included in the model. A simulation demonstrates the effect of sample size on the fully Bayesian analysis of the CAR process. The methods are applied to lip cancer data from Scotland, and the results are compared. ^

Using spatial linear models with SAR and CAR structure to examine Texas lung cancer incidence rates

Scholars have found that socioeconomic status was one of the key factors that influenced early-stage lung cancer incidence rates in a variety of regions. This thesis examined the association between median household income and lung cancer incidence rates in Texas counties. A total of 254 individual counties in Texas with corresponding lung cancer incidence rates from 2004 to 2008 and median household incomes in 2006 were collected from the National Cancer Institute Surveillance System. A simple linear model and spatial linear models with two structures, Simultaneous Autoregressive Structure (SAR) and Conditional Autoregressive Structure (CAR), were used to link median household income and lung cancer incidence rates in Texas. The residuals of the spatial linear models were analyzed with Moran's I and Geary's C statistics, and the statistical results were used to detect similar lung cancer incidence rate clusters and disease patterns in Texas.^

The INO80 chromatin remodeling complex is involved in the nucleotide excision repair pathway

The genomic DNA of eukaryotic cells is well organized into chromatin structures. However, these repressed structures present barriers that block the access of regulatory factors to the genome during various nuclear events. To overcome the obstacle, two major cellular processes, post-modification of histone tails and ATP-dependent chromatin remodeling, are involved in reconfiguring chromatin structure and creating accessible DNA. Despite the current research progress, much remains to be explored concerning the relationship between chromatin remodeling and DNA repair. Recently, one member of the ATP-dependent chromatin remodeling complexes, INO80, has been found to play a crucial role in DNA damage repair. However, the functions of this complex in higher eukaryotes have yet to be determined. The goal of my study is to generate a human somatic INO80 conditional knockout model and investigate the functions of Ino80 in damage repair.^ By homologous targeting of the INO80 locus in human HCT116 colon epithelial cells, I established a human somatic INO80 conditional knockout model. I have demonstrated that the conditional INO80 cells exhibited a sufficiently viable period when the INO80 protein is removed. Moreover, I found that loss of INO80 resulted in deficient UV lesion repair in response to UV while the protein levels of the NER factors such as XPC, XPA, XPD were not affected. And in vitro repair synthesis assay showed that the NER incision and repair synthesis activities were intact in the absence of INO80. Examination on the damage recognition factor XPC showed its recruitment to damage sites was impaired in the INO80 mutant cells. Loss of INO80 also led to reduced enrichment of XPA at the site of UV lesions. Despite the reduced recruitment of XPC and XPA observed in INO80 mutants, no direct interaction was detected. Meanwhile, direct interaction between INO80 and DDB1, the initial UV lesion detector, was detected by coimmunoprecipitation. UV-induced chromosome relaxation was reduced in cells devoid of INO80. These results demonstrate the INO80 complex may participates in the NER by interacting with DDB1 and having a critical role of in creating DNA accessibility for the nucleotide excision pathway. ^

Detection and sequence analysis of a nickel-induced mutation in a retroviral model system

We have developed a novel way to assess the mutagenicity of environmentally important metal carcinogens, such as nickel, by creating a positive selection system based upon the conditional expression of a retroviral transforming gene. The target gene is the v-mos gene in MuSVts110, a murine retrovirus possessing a growth temperature dependent defect in expression of the transforming gene due to viral RNA splicing. In normal rat kidney cells infected with MuSVts110 (6m2 cells), splicing of the MuSVts110 RNA to form the mRNA from which the transforming protein, p85$\sp{\rm gag-mos}$, is translated is growth-temperature dependent, occurring at 33 C and below but not at 39 C and above. This splicing "defect" is mediated by cis-acting viral sequences. Nickel chloride treatment of 6m2 cells followed by growth at 39 C, allowed the selection of "revertant" cells which constitutively express p85$\sp{\rm gag-mos}$ due to stable changes in the viral RNA splicing phenotype, suggesting that nickel, a carcinogen whose mutagenicity has not been well established, could induce mutations in mammalian genes. We also show by direct sequencing of PCR-amplified integrated MuSVts110 DNA from a 6m2 nickel-revertant cell line that the nickel-induced mutation affecting the splicing phenotype is a cis-acting 70-base duplication of a region of the viral DNA surrounding the 3$\sp\prime$ splice site. These findings provide the first example of the molecular basis for a nickel-induced DNA lesion and establish the mutagenicity of this potent carcinogen. ^

Temporal and spatial regulation of cell division by the nucleoid in Escherichia coli

Selection of division sites and coordination of cytokinesis with other cell cycle events are critical for every organism to proliferate. In E. coli, the nucleoid is proposed to exclude division from the site of the chromosome (nucleoid occlusion model). We studied the effect of the nucleoid on timing and placement of cell division. An early cell division protein, FtsZ, was used to follow development of the division septum. FtsZ forms a ring structure (Z ring) at potential division sites. The dynamics of Z ring was visualized in live cells by fusing FtsZ with a green fluorescent protein (GFP). Emanating FtsZ-GFP polymers from the constricted septum or aggregates in daughter cells were also observed, probably representing the FtsZ depolymerization and immature FtsZ nucleation processes. We next examined the nucleoid occlusion model. Mutants carrying abnormally positioned chromosomes were employed. In chromosomal partition mutants, replicated chromosomes cannot segregate. The Z ring was excluded from midcell to the edge of the nucleoid. This negative effect of nucleoids was further confirmed in replication deficient dnaA mutants, in which only a single chromosome is present in the cell center. These results suggest that the nucleoid, replicating or not, inhibits division in the area where the chromosome occupies. In addition, increasing the level of FtsZ does not overcome nucleoid inhibition. Interestingly in anucleate cells produced by both mutants, the Z ring was localized in the central part of the cell, which indicates that the nucleoid is not required for FtsZ assembly. Relaxation of chromosomes by reducing the gyrase activity or disruption of protein translation/translocation did not abolish the division inhibition capacity of the nucleoid. However, preventing transcription did compromise the nucleoid occlusion effect, leading to formation of multiple FtsZ rings above the nucleoid. In summary, we demonstrate that nucleoids negatively regulate the timing and position of division by inhibiting FtsZ assembly at unselected sites. Relief of this inhibition at midcell is coincident with the completion of DNA replication. On the other hand, FtsZ assembly does not require the nucleoid. ^

Characterization of healing tissue in a tooth extraction socket in a rabbit model

The histology of healing in a tooth extraction socket has been described in many studies. The focus of research in bone biology and healing is now centered on molecular events that regulate repair of injured tissue. Rapid progress in cellular and molecular biology has resulted in identification of many signaling molecules (growth factors and cytokines) associated with formation and repair of skeletal tissues. Some of these include members of the transforming growth factor-β superfamily (including the bone morphogenetic proteins), fibroblast growth factors, platelet derived growth factors and insulin like growth factors. ^ Healing of a tooth extraction socket is a complex process involving tissue repair and regeneration. It involves chemotaxis of appropriate cells into the wound, transformation of undifferentiated mesenchymal cells to osteoprogenitor cells, proliferation and differentiation of committed bone forming cells, extracellular matrix synthesis, mineralization of osteoid, maturation and remodeling of bone. Current data suggests that these cellular events are precisely controlled and regulated by specific signaling molecules. A plethora of cytokines; have been identified and studied in the past two decades. Some of these like transforming growth factor beta (TGF-β), vascular endothelial growth factor (VEGF), platelet derived growth factor (PDGF) and fibroblast growth factors (FGFs) are well conserved proteins involved in the initial response to injury and repair in soft and hard tissue. ^ The purpose of this study was to characterize the spatial and temporal localization of TGF-βl, VEGF, PDGF-A, FGF-2 and BMP-2, and secretory IgA in a tooth extraction socket model, and evaluate correlation of spatial and temporal changes of these growth factors to histological events. The results of this study showed positive correlation of histological events to spatial and temporal localization of TGF-β1, BMP-2, FGF-2, PDGF-A, and VEGF in a rabbit tooth extraction model. ^

An empirical model to estimate the demand for primary care in urban settings

Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^

Spatial analysis of water body distance and West Nile Virus human cases in Houston, TX

West Nile Virus (WNV) is an arboviral disease that has affected hundreds of residents in Harris County, Texas since its introduction in 2002. Persistent infection, lingering sequelae and other long-term symptoms of patients reaffirm the need for prevention of this important vector-borne disease. This study aimed to determine if living within 400m of a water body increases one’s odds of infection with WNV. Additionally, we wanted to determine if one’s proximity to a particular water type or water body source increased one’s odds of infection with WNV.^ 145 cases’ addresses were abstracted from the initial interview and consent records from a cohort of patients (Epidemiology of Arboviral Encephalitis in Houston study, HSC-SPH-03-039). After applying inclusion criteria, 140 cases were identified for analysis. 140 controls were selected for analysis using a population proportionate to size model and US Census Bureau data. MapMarker USA v14 was used to geocode the cases’ addresses. Both cases’ and controls’ coordinates were uploaded onto a Harris County water shapefile in MapInfo Professional v9.5.1. Distance in meters to the closest water source, closest water source type, and closest water source name were recorded.^ Analysis of Variance (p=0.329, R2 = 0.0034) indicated no association between water body distance and risk of WNV disease. Living near a creek (x2 = 11.79, p < 0.001), or the combined group of creek and gully (x 2 = 14.02, p < 0.001) were found to be strongly associated with infection of WNV. Living near Cypress Creek and its feeders (x2 = 15.2, p < 0.001) was found to be strongly associated with WNV infection. We found that creek and gully habitats, particularly Cypress Creek, were preferential for the local disease transmitting Culex quinquefasciatus and reservoir avian population.^

A novel method for evaluating an interaction effect of correlated continuous covariates in a linear model

Interaction effect is an important scientific interest for many areas of research. Common approach for investigating the interaction effect of two continuous covariates on a response variable is through a cross-product term in multiple linear regression. In epidemiological studies, the two-way analysis of variance (ANOVA) type of method has also been utilized to examine the interaction effect by replacing the continuous covariates with their discretized levels. However, the implications of model assumptions of either approach have not been examined and the statistical validation has only focused on the general method, not specifically for the interaction effect.^ In this dissertation, we investigated the validity of both approaches based on the mathematical assumptions for non-skewed data. We showed that linear regression may not be an appropriate model when the interaction effect exists because it implies a highly skewed distribution for the response variable. We also showed that the normality and constant variance assumptions required by ANOVA are not satisfied in the model where the continuous covariates are replaced with their discretized levels. Therefore, naïve application of ANOVA method may lead to an incorrect conclusion. ^ Given the problems identified above, we proposed a novel method modifying from the traditional ANOVA approach to rigorously evaluate the interaction effect. The analytical expression of the interaction effect was derived based on the conditional distribution of the response variable given the discretized continuous covariates. A testing procedure that combines the p-values from each level of the discretized covariates was developed to test the overall significance of the interaction effect. According to the simulation study, the proposed method is more powerful then the least squares regression and the ANOVA method in detecting the interaction effect when data comes from a trivariate normal distribution. The proposed method was applied to a dataset from the National Institute of Neurological Disorders and Stroke (NINDS) tissue plasminogen activator (t-PA) stroke trial, and baseline age-by-weight interaction effect was found significant in predicting the change from baseline in NIHSS at Month-3 among patients received t-PA therapy.^

Bayesian and survival model for tumor relapse status and disease-specific survival, with applications to breast cancer

Breast cancer is the most common non-skin cancer and the second leading cause of cancer-related death in women in the United States. Studies on ipsilateral breast tumor relapse (IBTR) status and disease-specific survival will help guide clinic treatment and predict patient prognosis.^ After breast conservation therapy, patients with breast cancer may experience breast tumor relapse. This relapse is classified into two distinct types: true local recurrence (TR) and new ipsilateral primary tumor (NP). However, the methods used to classify the relapse types are imperfect and are prone to misclassification. In addition, some observed survival data (e.g., time to relapse and time from relapse to death)are strongly correlated with relapse types. The first part of this dissertation presents a Bayesian approach to (1) modeling the potentially misclassified relapse status and the correlated survival information, (2) estimating the sensitivity and specificity of the diagnostic methods, and (3) quantify the covariate effects on event probabilities. A shared frailty was used to account for the within-subject correlation between survival times. The inference was conducted using a Bayesian framework via Markov Chain Monte Carlo simulation implemented in softwareWinBUGS. Simulation was used to validate the Bayesian method and assess its frequentist properties. The new model has two important innovations: (1) it utilizes the additional survival times correlated with the relapse status to improve the parameter estimation, and (2) it provides tools to address the correlation between the two diagnostic methods conditional to the true relapse types.^ Prediction of patients at highest risk for IBTR after local excision of ductal carcinoma in situ (DCIS) remains a clinical concern. The goals of the second part of this dissertation were to evaluate a published nomogram from Memorial Sloan-Kettering Cancer Center, to determine the risk of IBTR in patients with DCIS treated with local excision, and to determine whether there is a subset of patients at low risk of IBTR. Patients who had undergone local excision from 1990 through 2007 at MD Anderson Cancer Center with a final diagnosis of DCIS (n=794) were included in this part. Clinicopathologic factors and the performance of the Memorial Sloan-Kettering Cancer Center nomogram for prediction of IBTR were assessed for 734 patients with complete data. Nomogram for prediction of 5- and 10-year IBTR probabilities were found to demonstrate imperfect calibration and discrimination, with an area under the receiver operating characteristic curve of .63 and a concordance index of .63. In conclusion, predictive models for IBTR in DCIS patients treated with local excision are imperfect. Our current ability to accurately predict recurrence based on clinical parameters is limited.^ The American Joint Committee on Cancer (AJCC) staging of breast cancer is widely used to determine prognosis, yet survival within each AJCC stage shows wide variation and remains unpredictable. For the third part of this dissertation, biologic markers were hypothesized to be responsible for some of this variation, and the addition of biologic markers to current AJCC staging were examined for possibly provide improved prognostication. The initial cohort included patients treated with surgery as first intervention at MDACC from 1997 to 2006. Cox proportional hazards models were used to create prognostic scoring systems. AJCC pathologic staging parameters and biologic tumor markers were investigated to devise the scoring systems. Surveillance Epidemiology and End Results (SEER) data was used as the external cohort to validate the scoring systems. Binary indicators for pathologic stage (PS), estrogen receptor status (E), and tumor grade (G) were summed to create PS+EG scoring systems devised to predict 5-year patient outcomes. These scoring systems facilitated separation of the study population into more refined subgroups than the current AJCC staging system. The ability of the PS+EG score to stratify outcomes was confirmed in both internal and external validation cohorts. The current study proposes and validates a new staging system by incorporating tumor grade and ER status into current AJCC staging. We recommend that biologic markers be incorporating into revised versions of the AJCC staging system for patients receiving surgery as the first intervention.^ Chapter 1 focuses on developing a Bayesian method to solve misclassified relapse status and application to breast cancer data. Chapter 2 focuses on evaluation of a breast cancer nomogram for predicting risk of IBTR in patients with DCIS after local excision gives the statement of the problem in the clinical research. Chapter 3 focuses on validation of a novel staging system for disease-specific survival in patients with breast cancer treated with surgery as the first intervention. ^

Spatial analysis of cardiovascular disease mortality and air pollution in Harris County, Texas

The association between fine particulate matter air pollution (PM2.5) and cardiovascular disease (CVD) mortality was spatially analyzed for Harris County, Texas, at the census tract level. The objective was to assess how increased PM2.5 exposure related to CVD mortality in this area while controlling for race, income, education, and age. An estimated exposure raster was created for Harris County using Kriging to estimate the PM2.5 exposure at the census tract level. The PM2.5 exposure and the CVD mortality rates were analyzed in an Ordinary Least Squares (OLS) regression model and the residuals were subsequently assessed for spatial autocorrelation. Race, median household income, and age were all found to be significant (p<0.05) predictors in the model. This study found that for every one μg/m3 increase in PM2.5 exposure, holding age and education variables constant, an increase of 16.57 CVD deaths per 100,000 would be predicted for increased minimum exposure values and an increase of 14.47 CVD deaths per 100,000 would be predicted for increased maximum exposure values. This finding supports previous studies associating PM2.5 exposure with CVD mortality. This study further identified the areas of greatest PM2.5 exposure in Harris County as being the geographical locations of populations with the highest risk of CVD (i.e., predominantly older, low-income populations with a predominance of African Americans). The magnitude of the effect of PM2.5 exposure on CVD mortality rates in the study region indicates a need for further community-level studies in Harris County, and suggests that reducing excess PM2.5 exposure would reduce CVD mortality.^

Slope estimation in a parametric measurement error model: A simulation study

In regression analysis, covariate measurement error occurs in many applications. The error-prone covariates are often referred to as latent variables. In this proposed study, we extended the study of Chan et al. (2008) on recovering latent slope in a simple regression model to that in a multiple regression model. We presented an approach that applied the Monte Carlo method in the Bayesian framework to the parametric regression model with the measurement error in an explanatory variable. The proposed estimator applied the conditional expectation of latent slope given the observed outcome and surrogate variables in the multiple regression models. A simulation study was presented showing that the method produces estimator that is efficient in the multiple regression model, especially when the measurement error variance of surrogate variable is large.^

Spatial distribution of orofacial cleft birth defects and uranium-radium concentrations in tap water in Atascosa, Bee, Brooks, Calhoun, Duval, Goliad, Hidalgo, Jim Hogg, Jim Wells, Karnes, Kleberg, Live Oak, McMullen, Nueces, San Patricio, Refugio, Starr, Victoria, Webb, and Zavala Counties, Texas

Background Past and recent evidence shows that radionuclides in drinking water may be a public health concern. Developmental thresholds for birth defects with respect to chronic low level domestic radiation exposures, such as through drinking water, have not been definitely recognized, and there is a strong need to address this deficiency in information. In this study we examined the geographic distribution of orofacial cleft birth defects in and around uranium mining district Counties in South Texas (Atascosa, Bee, Brooks, Calhoun, Duval, Goliad, Hidalgo, Jim Hogg, Jim Wells, Karnes, Kleberg, Live Oak, McMullen, Nueces, San Patricio, Refugio, Starr, Victoria, Webb, and Zavala), from 1999 to 2007. The probable association of cleft birth defect rates by ZIP codes classified according to uranium and radium concentrations in drinking water supplies was evaluated. Similar associations between orofacial cleft birth defects and radium/radon in drinking water were reported earlier by Cech and co-investigators in another of the Gulf Coast region (Harris County, Texas).50, 55 Since substantial uranium mining activity existed and still exists in South Texas, contamination of drinking water sources with radiation and its relation to birth defects is a ground for concern. ^ Methods Residential addresses of orofacial cleft birth defect cases, as well as live births within the twenty Counties during 1999-2007 were geocoded and mapped. Prevalence rates were calculated by ZIP codes and were mapped accordingly. Locations of drinking water supplies were also geocoded and mapped. ZIP codes were stratified as having high combined uranium (≥30μg/L) vs. low combined uranium (<30μg/L). Likewise, ZIP codes having the uranium isotope, Ra-226 in drinking water, were also stratified as having elevated radium (≥3 pCi/L) vs. low radium (<3 pCi/L). A linear regression was performed using STATA® generalized linear model (GLM) program to evaluate the probable association between cleft birth defect rates by ZIP codes and concentration of uranium and radium via domestic water supply. These rates were further adjusted for potentially confounding variables such as maternal age, education, occupation, and ethnicity. ^ Results This study showed higher rates of cleft births in ZIP codes classified as having high combined uranium versus ZIP codes having low combined uranium. The model was further improved by adding radium stratified as explained above. Adjustment for maternal age and ethnicity did not substantially affect the statistical significance of uranium or radium concentrations in household water supplies. ^ Conclusion Although this study lacks individual exposure levels, the findings suggest a significant association between elevated uranium and radium concentrations in tap water and high orofacial birth defect rates by ZIP codes. Future case-control studies that can measure individual exposure levels and adjust for contending risk factors could result in a better understanding of the exposure-disease association.^

Bcr: A conditional inhibitor of Bcr -Abl oncoprotein

Chronic myelogenous leukemia (CML) is characterized cytogenetically by the presence of the Philadelphia chromosome and clinically by the clonal expansion of the hematopoietic stem cells and the accumulation of large numbers of myeloid cells. Philadelphia chromosome results from the reciprocal translocation between chromosomes 9 and 22 [t(9;22)(324;q11)], which fuses parts of the ABL proto-oncogene to 5′ portions of the BCR gene. The product of the fused gene is Bcr-Abl oncoprotein. Bcr-Abl oncoprotein has elevated protein tyrosine kinase activity, and is the cause of Philadelphia chromosome associated leukemias. The Bcr sequence in the fusion protein is crucial for the activation of Abl kinase activity and transforming phenotype of Bcr-Abl oncoprotein. Although the Bcr-Abl oncoprotein has been studied extensively, its normal counterpart, the Bcr protein, has been less studied and its function is not well understood. At this point, Bcr is known to encode a novel serine/threonine protein kinase. In Bcr-Abl positive leukemia cells, we found that the serine kinase activity of Bcr is impaired by tyrosine phosphorylation. Both the Bcr protein sequences within Bcr-Abl and the normal cellular Bcr protein lack serine/threonine kinase activity when they become phosphorylated on tyrosine residues by Bcr-Abl. Therefore, the goal of this study was to investigate the role of Bcr in Bcr-Abl positive leukemia cells. We found that overexpression of Bcr can inhibit Bcr-Abl tyrosine kinase activity, and the inhibition is dependent on its intact serine/threonine kinase function. Using the tet repressible promoter system, we demonstrated that Bcr when induced in Bcr-Abl positive leukemia cells inhibited the Bcr-Abl oncoprotein tyrosine kinase. Furthermore, induction of Bcr also increased the number of cells undergoing apoptosis and inhibited the transforming ability of Bcr-Abl. In contrast to the wild-type Bcr, the kinase-inactive mutant of Bcr (Y328F/Y360F) had no effects on Bcr-Abl tyrosine kinase in cells. Results from other experiments indicated that phosphoserine-containing Bcr sequences within the first exon, which are known to bind to the Abl SH2 domain, are responsible for observed inhibition of the Bcr-Abl tyrosine kinase. Several lines of evidence suggest that the phosphoserine form of Bcr, which binds to the Abl SH2 domain, strongly inhibits the Abl tyrosine kinase domain of Bcr-Abl Previously published findings from our laboratory have also shown that Bcr is phosphorylated on tyrosine residue 177 in Bcr-Abl positive cells and that this form of Bcr recruits the Grb2 adaptor protein, which is known to activate the Ras pathway. These findings implicate Bcr as an effector of Bcr-Abl's oncogenic activity. Therefore based on the findings presented above, we propose a model for dual Function of Bcr in Bcr-Abl positive leukemia cells. Bcr, when active as a serine/threonine kinase and thus autophosphorylating its own serine residues, inhibits Bcr-Abl's oncogenic functions. However, when Ber is tyrosine phosphorylated, its Bcr-Abl inhibitory function is neutralized thus allowing Bcr-Abl to exert its full oncogenic potential. Moreover, tyrosine phosphorylated Bcr would compliment Bcr-Abl's neoplastic effects by the activation of the Ras signaling pathway. ^