Co-expression networks in generation of induced pluripotent stem cells.

We developed an adenoviral vector, in which Yamanaka's four reprogramming factors (RFs) were controlled by individual CMV promoters in a single cassette (Ad-SOcMK). This permitted coordinated expression of RFs (SOX2, OCT3/4, c-MYC and KLF4) in a cell for a transient period of time, synchronizing the reprogramming process with the majority of transduced cells assuming induced pluripotent stem cell (iPSC)-like characteristics as early as three days post-transduction. These reprogrammed cells resembled human embryonic stem cells (ESCs) with regard to morphology, biomarker expression, and could be differentiated into cells of the germ layers in vitro and in vivo. These iPSC-like cells, however, failed to expand into larger iPSC colonies. The short and synchronized reprogramming process allowed us to study global transcription changes within short time intervals. Weighted gene co-expression network analysis (WGCNA) identified sixteen large gene co-expression modules, each including members of gene ontology categories involved in cell differentiation and development. In particular, the brown module contained a significant number of ESC marker genes, whereas the turquoise module contained cell-cycle-related genes that were downregulated in contrast to upregulation in human ESCs. Strong coordinated expression of all four RFs via adenoviral transduction may constrain stochastic processes and lead to silencing of genes important for cellular proliferation

Doctor of Philosophy

dissertationUncertainty Quantification is a growing field of study with critical implications in assessing the reliability of complex computational models. In the biomedical field, use of computational modeling and simulation is increasing in both research and clinical applications. Even with the inherent and ubiquitous uncertainties in its data, the biomedical domain has not seen an accompanying establishment of clear Uncertainty Quantification frameworks and best practices when compared to other computationally intensive fields. In this dissertation, a review of an Uncertainty Quantification framework is discussed with current applications and techniques presently implemented in the biomedical field. Afterward, the impact of uncertainty associated with self-reported family-health history on four frequently used breast and ovarian cancer risk prediction models is estimated using Monte Carlo simulations. Following this, we present an example of co-expression network analysis to identify genetic modules associated with Spinocerebellar Ataxia Type 2 disease pathogenesis. Lastly, we present an assessment of analytical and experimental design uncertainty on the identified gene co-expression network, using a systematic approach for multiple pipeline analysis and Monte Carlo simulations

Co-expression networks in generation of induced pluripotent stem cells.

We developed an adenoviral vector, in which Yamanaka's four reprogramming factors (RFs) were controlled by individual CMV promoters in a single cassette (Ad-SOcMK). This permitted coordinated expression of RFs (SOX2, OCT3/4, c-MYC and KLF4) in a cell for a transient period of time, synchronizing the reprogramming process with the majority of transduced cells assuming induced pluripotent stem cell (iPSC)-like characteristics as early as three days post-transduction. These reprogrammed cells resembled human embryonic stem cells (ESCs) with regard to morphology, biomarker expression, and could be differentiated into cells of the germ layers in vitro and in vivo. These iPSC-like cells, however, failed to expand into larger iPSC colonies. The short and synchronized reprogramming process allowed us to study global transcription changes within short time intervals. Weighted gene co-expression network analysis (WGCNA) identified sixteen large gene co-expression modules, each including members of gene ontology categories involved in cell differentiation and development. In particular, the brown module contained a significant number of ESC marker genes, whereas the turquoise module contained cell-cycle-related genes that were downregulated in contrast to upregulation in human ESCs. Strong coordinated expression of all four RFs via adenoviral transduction may constrain stochastic processes and lead to silencing of genes important for cellular proliferation

Co-expression networks in generation of induced pluripotent stem cells

We developed an adenoviral vector, in which Yamanaka's four reprogramming factors (RFs) were controlled by individual CMV promoters in a single cassette (Ad-SOcMK). This permitted coordinated expression of RFs (SOX2, OCT3/4, c-MYC and KLF4) in a cell for a transient period of time, synchronizing the reprogramming process with the majority of transduced cells assuming induced pluripotent stem cell (iPSC)-like characteristics as early as three days post-transduction. These reprogrammed cells resembled human embryonic stem cells (ESCs) with regard to morphology, biomarker expression, and could be differentiated into cells of the germ layers in vitro and in vivo. These iPSC-like cells, however, failed to expand into larger iPSC colonies. The short and synchronized reprogramming process allowed us to study global transcription changes within short time intervals. Weighted gene co-expression network analysis (WGCNA) identified sixteen large gene co-expression modules, each including members of gene ontology categories involved in cell differentiation and development. In particular, the brown module contained a significant number of ESC marker genes, whereas the turquoise module contained cell-cycle-related genes that were downregulated in contrast to upregulation in human ESCs. Strong coordinated expression of all four RFs via adenoviral transduction may constrain stochastic processes and lead to silencing of genes important for cellular proliferation

Co-expression networks in generation of induced pluripotent stem cells

We developed an adenoviral vector, in which Yamanaka's four reprogramming factors (RFs) were controlled by individual CMV promoters in a single cassette (Ad-SOcMK). This permitted coordinated expression of RFs (SOX2, OCT3/4, c-MYC and KLF4) in a cell for a transient period of time, synchronizing the reprogramming process with the majority of transduced cells assuming induced pluripotent stem cell (iPSC)-like characteristics as early as three days post-transduction. These reprogrammed cells resembled human embryonic stem cells (ESCs) with regard to morphology, biomarker expression, and could be differentiated into cells of the germ layers in vitro and in vivo. These iPSC-like cells, however, failed to expand into larger iPSC colonies. The short and synchronized reprogramming process allowed us to study global transcription changes within short time intervals. Weighted gene co-expression network analysis (WGCNA) identified sixteen large gene co-expression modules, each including members of gene ontology categories involved in cell differentiation and development. In particular, the brown module contained a significant number of ESC marker genes, whereas the turquoise module contained cell-cycle-related genes that were downregulated in contrast to upregulation in human ESCs. Strong coordinated expression of all four RFs via adenoviral transduction may constrain stochastic processes and lead to silencing of genes important for cellular proliferation

Repeat Associated Non-AUG Translation (RAN Translation) Dependent on Sequence Downstream of the ATXN2 CAG Repeat.

Spinocerebellar ataxia type 2 (SCA2) is a progressive autosomal dominant disorder caused by the expansion of a CAG tract in the ATXN2 gene. The SCA2 disease phenotype is characterized by cerebellar atrophy, gait ataxia, and slow saccades. ATXN2 mutation causes gains of toxic and normal functions of the ATXN2 gene product, ataxin-2, and abnormally slow Purkinje cell firing frequency. Previously we investigated features of ATXN2 controlling expression and noted expression differences for ATXN2 constructs with varying CAG lengths, suggestive of repeat associated non-AUG translation (RAN translation). To determine whether RAN translation occurs for ATXN2 we assembled various ATXN2 constructs with ATXN2 tagged by luciferase, HA or FLAG tags, driven by the CMV promoter or the ATXN2 promoter. Luciferase expression from ATXN2-luciferase constructs lacking the ATXN2 start codon was weak vs AUG translation, regardless of promoter type, and did not increase with longer CAG repeat lengths. RAN translation was detected on western blots by the anti-polyglutamine antibody 1C2 for constructs driven by the CMV promoter but not the ATXN2 promoter, and was weaker than AUG translation. Strong RAN translation was also observed when driving the ATXN2 sequence with the CMV promoter with ATXN2 sequence downstream of the CAG repeat truncated to 18 bp in the polyglutamine frame but not in the polyserine or polyalanine frames. Our data demonstrate that ATXN2 RAN translation is weak compared to AUG translation and is dependent on ATXN2 sequences flanking the CAG repeat

Co-expression networks in generation of induced pluripotent stem cells

We developed an adenoviral vector, in which Yamanaka's four reprogramming factors (RFs) were controlled by individual CMV promoters in a single cassette (Ad-SOcMK). This permitted coordinated expression of RFs (SOX2, OCT3/4, c-MYC and KLF4) in a cell for a transient period of time, synchronizing the reprogramming process with the majority of transduced cells assuming induced pluripotent stem cell (iPSC)-like characteristics as early as three days post-transduction. These reprogrammed cells resembled human embryonic stem cells (ESCs) with regard to morphology, biomarker expression, and could be differentiated into cells of the germ layers in vitro and in vivo. These iPSC-like cells, however, failed to expand into larger iPSC colonies. The short and synchronized reprogramming process allowed us to study global transcription changes within short time intervals. Weighted gene co-expression network analysis (WGCNA) identified sixteen large gene co-expression modules, each including members of gene ontology categories involved in cell differentiation and development. In particular, the brown module contained a significant number of ESC marker genes, whereas the turquoise module contained cell-cycle-related genes that were downregulated in contrast to upregulation in human ESCs. Strong coordinated expression of all four RFs via adenoviral transduction may constrain stochastic processes and lead to silencing of genes important for cellular proliferation

Evaluation of the relevance and access of EHR-based variables to support personalized medicine in breast cancer

Background: The increasing number of available cancer therapies render medical decision-making (MDM) less straightforward. Patients want to know about the outcomes of similarly treated patients. Objective: The goal of this study was to design a breast cancer dashboard (BCD) tool that presents survival information to support MDM activities. Methods: Clinical variables during the clinic visit were determined via provider meetings and evaluated for accessibility from medical databases. Women with breast cancer (BC) were interviewed about their health care experiences after cancer diagnosis. We created a cohort of BC adult women treated at our institution from 1995 to 2012, from which clinical scenarios were defined and used to test survival outcomes. For the BCD, a simple, graphical user interface was built to present point-of-care clinical and survival data. Results: It is feasible to build the BCD using our institution’s databases and generate survival plots to facilitate MDM activities. Patients with early-stage BC had the highest survival rate (82.3%) and the longest mean life years of 7.0 (SD 4.5) years. In late-stage BC, poor prognosis outweighs the influence of number of comorbidities on mortality. The BCD tool promotes more predictive, personalized, and collaborative health care

<i>ATXN2-luc</i> expression driven by the native <i>ATXN2</i> promoter, dependent upon CAG length and the presence of a start codon.

<p>(A) Plasmid constructs used in luciferase assays. (B) Luciferase assays to evaluate <i>ATXN2</i> expression driven by 1062 bp of its native upstream sequence, demonstrated increasing expression with increasing CAG length (ATG constructs). When the start codon was mutated, expression significantly higher than the control was observed only for <i>ATXN2</i>s with CAG repeat lengths of 57 or 102 (CTG constructs). For the longest repeat expression was 25-fold reduced when the start codon was substituted with CTG. Values are mean±SD of three independent experiments. All constructs were cotransfected with SV40-Renilla luciferase and values are represented as mean FLuc / RLuc, the ratio of firefly luciferase to Renilla luciferase. (C) RAN translation products were not observed by western blotting using anti-luciferase (luc) or 1C2 antibodies. Note that polyglutamine proteins detected with the 1C2 anti-polyglutamine antibody are more easily seen as the length of the polyglutamine is increased. Loading was controlled by detecting actin. The mobilities of the smaller ataxin-2-luciferase bands are not consistent with RAN translation bands. (D) Analysis of the luciferase assay results for only the CTG-<i>ATXN2-luc</i> constructs in B revealed significantly increased expression for constructs with 22 or greater CAG repeats but no increasing luciferase expression with increasing CAG repeat length. P<0.001 (**), Bonferroni post-hoc probability of significance. Assays utilized HEK293T cells with assays made 24 hrs after transfection.</p

Program in Personalized Health Care

Abstract: Background: The increasing number of available cancer therapies render medical decision-making (MDM) less straightforward. Patients want to know about the outcomes of similarly treated patients. Objective: The goal of this study was to design a breast cancer dashboard (BCD) tool that presents survival information to support MDM activities. Methods: Clinical variables during the clinic visit were determined via provider meetings and evaluated for accessibility from medical databases. Women with breast cancer (BC) were interviewed about their health care experiences after cancer diagnosis. We created a cohort of BC adult women treated at our institution from 1995 to 2012, from which clinical scenarios were defined and used to test survival outcomes. For the BCD, a simple, graphical user interface was built to present point-of-care clinical and survival data. Results: It is feasible to build the BCD using our institution&apos;s databases and generate survival plots to facilitate MDM activities. Patients with early-stage BC had the highest survival rate (82.3%) and the longest mean life years of 7.0 (SD 4.5) years. In late-stage BC, poor prognosis outweighs the influence of number of comorbidities on mortality. The BCD tool promotes more predictive, personalized, and collaborative health care. ABOUT THE AUTHORS The authors work across the University of Utah Health Sciences in oncology clinical practice, bioinformatics, and pharmacotherapy outcomes research. Our work is aimed at improving patient care via outcomes research and assessment. The Center&apos;s personnel have expertise in health economics, modeling, various clinical subspecialties (including oncology), drug information, statistical analysis and programming, and database management. PUBLIC INTEREST STATEMENT As more breast cancer treatment options become available, the shared medical decision-making relationship between physician and patient is becoming less straightforward. To support this important interaction, we have created an institution-specific medical communication tool. Decision aids have been shown to improve the health care experience of patients and ultimately lead to the achievement of higher-quality decisions. Our communication tool, named the breast cancer dashboard (BCD), was designed to be used during the clinic visit. It specifically address patients&apos; needs to know about the survival outcomes of similar patients treated at our cancer specialty hospital. The BCD brings together comprehensive and breast cancerspecific clinical information. It allows both the provider and patient to navigate the information using a patient-friendly graphic interface. By enhancing shared decision-making, there would be a shift toward patient care that is more predictive, preventive, personalized, and collaborative