McDonald, John F.

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Now showing 1 - 10 of 24
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    The Potential of Machine Learning for Improved Diagnostics and Treatment
    (Georgia Institute of Technology, 2019-06-12) McDonald, John F.
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    The Smart Grid and Energy Data: Measurement and Management
    (Georgia Institute of Technology, 2011-03-30) McDonald, John F. ; Khan, Musaddeq ; Malik, Sanjoy
    The Smart Grid has the potential to provide overwhelming amounts of data about residential, commercial and industrial energy consumption. Further, it offers the possibilities of two-way interaction between consumer and provider. What is a vision of data management as the Smart Grid is deployed? From user and provider perspectives, what anticipated changes to data management will occur as increased intelligence and digital infrastructure is deployed? What solutions are economically viable? The March program will explore the topic of Smart Grid data management and will provide insightful solutions from established and emerging businesses.
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    Chemosensitization of cancer cells by siRNA using targeted nanogel delivery
    (Georgia Institute of Technology, 2010-01-11) Dickerson, Erin B. ; Blackburn, William H. ; Kapa, Laura B. ; Lyon, L. Andrew ; McDonald, John F.
    Background. Chemoresistance is a major obstacle in cancer treatment. Targeted therapies that enhance cancer cell sensitivity to chemotherapeutic agents have the potential to increase drug efficacy while reducing toxic effects on untargeted cells. Targeted cancer therapy by RNA interference (RNAi) is a relatively new approach that can be used to reversibly silence genes in vivo by selectively targeting genes such as the epidermal growth factor receptor (EGFR), which has been shown to increase the sensitivity of cancer cells to taxane chemotherapy. However, delivery represents the main hurdle for the broad development of RNAi therapeutics. Methods. We report here the use of core/shell hydrogel nanoparticles (nanogels) functionalized with peptides that specially target the EphA2 receptor to deliver small interfering RNAs (siRNAs) targeting EGFR. Expression of EGFR was determined by immunoblotting, and the effect of decreased EGFR expression on chemosensitization of ovarian cancer cells after siRNA delivery was investigated. Results. Treatment of EphA2 positive Hey cells with siRNA-loaded, peptide-targeted nanogels decreased EGFR expression levels and significantly increased the sensitivity of this cell line to docetaxel (P < 0.05). Nanogel treatment of SK-OV-3 cells, which are negative for EphA2 expression, failed to reduce EGFR levels and did not increase docetaxel sensitivity (P > 0.05).
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    Gene expression profiling supports the hypothesis that human ovarian surface epithelia are multipotent and capable of serving as ovarian cancer initiating cells
    (Georgia Institute of Technology, 2009-12-29) Bowen, Nathan J. ; Walker, L. DeEtte ; Matyunina, Lilya V. ; Logani, Sanjay ; Totten, Kimberly A. ; Benigno, Benedict B. ; McDonald, John F.
    Background Accumulating evidence suggests that somatic stem cells undergo mutagenic transformation into cancer initiating cells. The serous subtype of ovarian adenocarcinoma in humans has been hypothesized to arise from at least two possible classes of progenitor cells: the ovarian surface epithelia (OSE) and/or an as yet undefined class of progenitor cells residing in the distal end of the fallopian tube. Methods Comparative gene expression profiling analyses were carried out on OSE removed from the surface of normal human ovaries and ovarian cancer epithelial cells (CEPI) isolated by laser capture micro-dissection (LCM) from human serous papillary ovarian adenocarcinomas. The results of the gene expression analyses were randomly confirmed in paraffin embedded tissues from ovarian adenocarcinoma of serous subtype and non-neoplastic ovarian tissues using immunohistochemistry. Differentially expressed genes were analyzed using gene ontology, molecular pathway, and gene set enrichment analysis algorithms. Results Consistent with multipotent capacity, genes in pathways previously associated with adult stem cell maintenance are highly expressed in ovarian surface epithelia and are not expressed or expressed at very low levels in serous ovarian adenocarcinoma. Among the over 2000 genes that are significantly differentially expressed, a number of pathways and novel pathway interactions are identified that may contribute to ovarian adenocarcinoma development.
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    Ovarian Cancer Detection from Metabolomic Liquid Chromatography/Mass Spectrometry Data by Support Vector Machines
    (Georgia Institute of Technology, 2009-08-22) Guan, Wei ; Zhou, Manshui ; Hampton, Christina Young ; Benigno, Benedict B. ; Walker, L. DeEtte ; Gray, Alexander ; McDonald, John F. ; Fernández, Facundo M.
    Background: The majority of ovarian cancer biomarker discovery efforts focus on the identification of proteins that can improve the predictive power of presently available diagnostic tests. We here show that metabolomics, the study of metabolic changes in biological systems, can also provide characteristic small molecule fingerprints related to this disease. Results: In this work, new approaches to automatic classification of metabolomic data produced from sera of ovarian cancer patients and benign controls are investigated. The performance of support vector machines (SVM) for the classification of liquid chromatography/time-of-flight mass spectrometry (LC/TOF MS) metabolomic data focusing on recognizing combinations or "panels" of potential metabolic diagnostic biomarkers was evaluated. Utilizing LC/TOF MS, sera from 37 ovarian cancer patients and 35 benign controls were studied. Optimum panels of spectral features observed in positive or/and negative ion mode electrospray (ESI) MS with the ability to distinguish between control and ovarian cancer samples were selected using state-of-the-art feature selection methods such as recursive feature elimination and L1-norm SVM. Conclusion: Three evaluation processes (leave-one-out-cross-validation, 12-fold-cross-validation, 52-20-split-validation) were used to examine the SVM models based on the selected panels in terms of their ability for differentiating control vs. disease serum samples. The statistical significance for these feature selection results were comprehensively investigated. Classification of the serum sample test set was over 90% accurate indicating promise that the above approach may lead to the development of an accurate and reliable metabolomic-based approach for detecting ovarian cancer.
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    Development of a human retrochip to detect epigenetic changes in ovarian ...
    (Georgia Institute of Technology, 2009-06-05) McDonald, John F.
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    Cancer Nanotechnology
    (Georgia Institute of Technology, 2009-05-01) Nie, Shuming ; McDonald, John F. ; El-Sayed, Mostafa A.
    Shuming Nie is the Wallace H. Coulter Distinguished Chair Professor in Biomedical Engineering at Emory University and the Georgia Institute of Technology. His research interest is broadly in biomolecular engineering and nanotechnology. John McDonald is taking an integrated systems approach to the study of cancer. This means that he views cancer not as a defect in any particular gene or protein, but as a de-regulated cellular/ inter-cellular process. Mostafa El-Sayed is the Julius Brown Chair and Regents Professor in the School of Chemistry and Biochemistry at Georgia Tech. He researches Nanoscience and also investigates how Nanoparticles can be used in Nanomedicine, Nano Catalysis, and Nanophotonics.
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    Aurora kinase inhibitors synergize with paclitaxel to induce apoptosis in ovarian cancer cells
    (Georgia Institute of Technology, 2008-12-11) Scharer, Christopher D. ; Laycock, Noelani ; Osunkoya, Adeboye O. ; Logani, Sanjay ; McDonald, John F. ; Benigno, Benedict B. ; Moreno, Carlos S.
    Background: A large percentage of patients with recurrent ovarian cancer develop resistance to the taxane class of chemotherapeutics. While mechanisms of resistance are being discovered, novel treatment options and a better understanding of disease resistance are sorely needed. The mitotic kinase Aurora-A directly regulates cellular processes targeted by the taxanes and is overexpressed in several malignancies, including ovarian cancer. Recent data has shown that overexpression of Aurora-A can confer resistance to the taxane paclitaxel. Methods: We used expression profiling of ovarian tumor samples to determine the most significantly overexpressed genes. In this study we sought to determine if chemical inhibition of the Aurora kinase family using VE-465 could synergize with paclitaxel to induce apoptosis in paclitaxel-resistant and sensitive ovarian cancer cells. Results: Aurora-A kinase and TPX2, an activator of Aurora-A, are two of the most significantly overexpressed genes in ovarian carcinomas. We show that inhibition of the Aurora kinases prevents phosphorylation of a mitotic marker and demonstrate a dose-dependent increase of apoptosis in treated ovarian cancer cells. We demonstrate at low doses that are specific to Aurora-A, VE-465 synergizes with paclitaxel to induce 4.5-fold greater apoptosis than paclitaxel alone in 1A9 cells. Higher doses are needed to induce apoptosis in paclitaxel-resistant PTX10 cells. Conclusion: Our results show that VE-465 is a potent killer of taxane resistant ovarian cancer cells and can synergize with paclitaxel at low doses. These data suggest patients whose tumors exhibit high Aurora-A expression may benefit from a combination therapy of taxanes and Aurora-A inhibition.
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    Identification of metabolites with anticancer properties by computational metabolomics
    (Georgia Institute of Technology, 2008-06-17) Arakaki, Adrian K. ; Mezencev, Roman ; Bowen, Nathan J. ; Huang, Ying ; McDonald, John F. ; Skolnick, Jeffrey
    Background: Certain endogenous metabolites can influence the rate of cancer cell growth. For example, diacylglycerol, ceramides and sphingosine, NAD+ and arginine exert this effect by acting as signaling molecules, while carrying out other important cellular functions. Metabolites can also be involved in the control of cell proliferation by directly regulating gene expression in ways that are signaling pathway-independent, e.g. by direct activation of transcription factors or by inducing epigenetic processes. The fact that metabolites can affect the cancer process on so many levels suggests that the change in concentration of some metabolites that occurs in cancer cells could have an active role in the progress of the disease. Results: CoMet, a fully automated Computational Metabolomics method to predict changes in metabolite levels in cancer cells compared to normal references has been developed and applied to Jurkat T leukemia cells with the goal of testing the following hypothesis: Up or down regulation in cancer cells of the expression of genes encoding for metabolic enzymes leads to changes in intracellular metabolite concentrations that contribute to disease progression. All nine metabolites predicted to be lowered in Jurkat cells with respect to lymphoblasts that were examined (riboflavin, tryptamine, 3- sulfino-L-alanine, menaquinone, dehydroepiandrosterone, α-hydroxystearic acid, hydroxyacetone, seleno-L-methionine and 5,6-dimethylbenzimidazole), exhibited antiproliferative activity that has not been reported before, while only two (bilirubin and androsterone) of the eleven tested metabolites predicted to be increased or unchanged in Jurkat cells displayed significant antiproliferative activity. Conclusion: These results: a) demonstrate that CoMet is a valuable method to identify potential compounds for experimental validation, b) indicate that cancer cell metabolism may be regulated to reduce the intracellular concentration of certain antiproliferative metabolites, leading to uninhibited cellular growth and c) suggest that many other endogenous metabolites with important roles in carcinogenesis are awaiting discovery.
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    LTR retrotransposons and the evolution of dosage compensation in Drosophila
    (Georgia Institute of Technology, 2008-06-04) Matyunina, Lilya V. ; Bowen, Nathan J. ; McDonald, John F.
    Background: Dosage compensation in Drosophila is the epigenetic process by which the expression of genes located on the single X-chromosome of males is elevated to equal the expression of X-linked genes in females where there are two copies of the X-chromosome. While epigenetic mechanisms are hypothesized to have evolved originally to silence transposable elements, a connection between transposable elements and the evolution of dosage compensation has yet to be demonstrated. Results: We show that transcription of the Drosophila melanogaster copia LTR (long terminal repeat) retrotransposon is significantly down regulated when in the hemizygous state. DNA digestion and chromatin immunoprecipitation (ChIP) analyses demonstrate that this down regulation is associated with changes in chromatin structure mediated by the histone acetyltransferase, MOF. MOF has previously been shown to play a central role in the Drosophila dosage compensation complex by binding to the hemizygous X-chromosome in males. Conclusion: Our results are consistent with the hypothesis that MOF originally functioned to silence retrotransposons and, over evolutionary time, was co-opted to play an essential role in dosage compensation in Drosophila.