The potential role of environmental exposures and genomic signaling in development of central nervous system tumors

The etiology of central nervous system tumors (CNSTs) is mainly unknown. Aside from extremely rare genetic conditions, such as neurofibromatosis and tuberous sclerosis, the only unequivocally identified risk factor is exposure to ionizing radiation, and this explains only a very small fraction of cases. Using meta-analysis, gene networking and bioinformatics methods, this dissertation explored the hypothesis that environmental exposures produce genetic and epigenetic alterations that may be involved in the etiology of CNSTs. A meta-analysis of epidemiological studies of pesticides and pediatric brain tumors revealed a significantly increased risk of brain tumors among children whose mothers had farm-related exposures during pregnancy. A dose response was recognized when this risk estimate was compared to those for risk of brain tumors from maternal exposure to non-agricultural pesticides during pregnancy, and risk of brain tumors among children exposed to agricultural activities. Through meta-analysis of several microarray studies which compared normal tissue to astrocytomas, we were able to identify a list of 554 genes which were differentially expressed in the majority of astrocytomas. Many of these genes have in fact been implicated in development of astrocytoma, including EGFR, HIF-1α, c-Myc, WNT5A, and IDH3A. Reverse engineering of these 554 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I-IV), and ‘key genes’ within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme (GBM) were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. Lastly, bioinformatics analysis of environmental databases and curated published results on GBM was able to identify numerous potential pathways and geneenvironment interactions that may play key roles in astrocytoma development. Findings from this research have strong potential to advance our understanding of the etiology and susceptibility to CNSTs. Validation of our ‘key genes’ and pathways could potentially lead to useful tools for early detection and novel therapeutic options for these tumors.

Understanding Ten-Eleven Translocation-2 in Hematological and Nervous Systems

I proposed the study of two distinct aspects of Ten-Eleven Translocation 2 (TET2) protein for understanding specific functions in different body systems. In Part I, I characterized the molecular mechanisms of Tet2 in the hematological system. As the second member of Ten-Eleven Translocation protein family, TET2 is frequently mutated in leukemic patients. Previous studies have shown that the TET2 mutations frequently occur in 20% myelodysplastic syndrome/myeloproliferative neoplasm (MDS/MPN), 10% T-cell lymphoma leukemia and 2% B-cell lymphoma leukemia. Genetic mouse models also display distinct phenotypes of various types of hematological malignancies. I performed 5-hydroxymethylcytosine (5hmC) chromatin immunoprecipitation sequencing (ChIP-Seq) and RNA sequencing (RNA-Seq) of hematopoietic stem/progenitor cells to determine whether the deletion of Tet2 can affect the abundance of 5hmC at myeloid, T-cell and B-cell specific gene transcription start sites, which ultimately result in various hematological malignancies. Subsequent Exome sequencing (Exome-Seq) showed that disease-specific genes are mutated in different types of tumors, which suggests that TET2 may protect the genome from being mutated. The direct interaction between TET2 and Mutator S Homolog 6 (MSH6) protein suggests TET2 is involved in DNA mismatch repair. Finally, in vivo mismatch repair studies show that the loss of Tet2 causes a mutator phenotype. Taken together, my data indicate that TET2 binds to MSH6 to protect genome integrity. In Part II, I intended to better understand the role of Tet2 in the nervous system. 5-hydroxymethylcytosine regulates epigenetic modification during neurodevelopment and aging. Thus, Tet2 may play a critical role in regulating adult neurogenesis. To examine the physiological significance of Tet2 in the nervous system, I first showed that the deletion of Tet2 reduces the 5hmC levels in neural stem cells. Mice lacking Tet2 show abnormal hippocampal neurogenesis along with 5hmC alternations at different gene promoters and corresponding gene expression downregulation. Through the luciferase reporter assay, two neural factors Neurogenic differentiation 1 (NeuroD1) and Glial fibrillary acidic protein (Gfap) were down-regulated in Tet2 knockout cells. My results suggest that Tet2 regulates neural stem/progenitor cell proliferation and differentiation in adult brain.

Understanding ten-eleven translocation-2 in hematological and nervous systems

I proposed the study of two distinct aspects of Ten-Eleven Translocation 2 (TET2) protein for understanding specific functions in different body systems. ^ In Part I, I characterized the molecular mechanisms of Tet2 in the hematological system. As the second member of Ten-Eleven Translocation protein family, TET2 is frequently mutated in leukemic patients. Previous studies have shown that the TET2 mutations frequently occur in 20% myelodysplastic syndrome/myeloproliferative neoplasm (MDS/MPN), 10% T-cell lymphoma leukemia and 2% B-cell lymphoma leukemia. Genetic mouse models also display distinct phenotypes of various types of hematological malignancies. I performed 5-hydroxymethylcytosine (5hmC) chromatin immunoprecipitation sequencing (ChIP-Seq) and RNA sequencing (RNA-Seq) of hematopoietic stem/progenitor cells to determine whether the deletion of Tet2 can affect the abundance of 5hmC at myeloid, T-cell and B-cell specific gene transcription start sites, which ultimately result in various hematological malignancies. Subsequent Exome sequencing (Exome-Seq) showed that disease-specific genes are mutated in different types of tumors, which suggests that TET2 may protect the genome from being mutated. The direct interaction between TET2 and Mutator S Homolog 6 (MSH6) protein suggests TET2 is involved in DNA mismatch repair. Finally, in vivo mismatch repair studies show that the loss of Tet2 causes a mutator phenotype. Taken together, my data indicate that TET2 binds to MSH6 to protect genome integrity. ^ In Part II, I intended to better understand the role of Tet2 in the nervous system. 5-hydroxymethylcytosine regulates epigenetic modification during neurodevelopment and aging. Thus, Tet2 may play a critical role in regulating adult neurogenesis. To examine the physiological significance of Tet2 in the nervous system, I first showed that the deletion of Tet2 reduces the 5hmC levels in neural stem cells. Mice lacking Tet2 show abnormal hippocampal neurogenesis along with 5hmC alternations at different gene promoters and corresponding gene expression downregulation. Through the luciferase reporter assay, two neural factors Neurogenic differentiation 1 (NeuroD1) and Glial fibrillary acidic protein (Gfap) were down-regulated in Tet2 knockout cells. My results suggest that Tet2 regulates neural stem/progenitor cell proliferation and differentiation in adult brain.^

Off-line and on-line affective recognition of a computer user through a biosignal processing approach

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. ^ In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment ("relaxation" vs. "stress") are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. ^ For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). ^ In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the "relaxation" vs. "stress" states.^

Specific Increase in MDR1 Mediated Drug-Efflux in Human Brain Endothelial Cells following Co-Exposure to HIV-1 and Saquinavir

Persistence of HIV-1 reservoirs within the Central Nervous System (CNS) remains a significant challenge to the efficacy of potent anti-HIV-1 drugs. The primary human Brain Microvascular Endothelial Cells (HBMVEC) constitutes the Blood Brain Barrier (BBB) which interferes with anti-HIV drug delivery into the CNS. The ATP binding cassette (ABC) transporters expressed on HBMVEC can efflux HIV-1 protease inhibitors (HPI), enabling the persistence of HIV-1 in CNS. Constitutive low level expression of several ABC-transporters, such as MDR1 (a.k.a. P-gp) and MRPs are documented in HBMVEC. Although it is recognized that inflammatory cytokines and exposure to xenobiotic drug substrates (e.g HPI) can augment the expression of these transporters, it is not known whether concomitant exposure to virus and anti-retroviral drugs can increase drug-efflux functions in HBMVEC. Our in vitro studies showed that exposure of HBMVEC to HIV-1 significantly up-regulates both MDR1 gene expression and protein levels; however, no significant increases in either MRP-1 or MRP-2 were observed. Furthermore, calcein-AM dye-efflux assays using HBMVEC showed that, compared to virus exposure alone, the MDR1 mediated drug-efflux function was significantly induced following concomitant exposure to both HIV-1 and saquinavir (SQV). This increase in MDR1 mediated drug-efflux was further substantiated via increased intracellular retention of radiolabeled [3H-] SQV. The crucial role of MDR1 in 3H-SQV efflux from HBMVEC was further confirmed by using both a MDR1 specific blocker (PSC-833) and MDR1 specific siRNAs. Therefore, MDR1 specific drug-efflux function increases in HBMVEC following co-exposure to HIV-1 and SQV which can reduce the penetration of HPIs into the infected brain reservoirs of HIV-1. A targeted suppression of MDR1 in the BBB may thus provide a novel strategy to suppress residual viral replication in the CNS, by augmenting the therapeutic efficacy of HAART drugs.

Off-line and On-line Affective Recognition of a Computer User through A Biosignal Processing Approach

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment (“relaxation” vs. “stress”) are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the “relaxation” vs. “stress” states.