Collagen in the scarless fetal skin wound: Detection with Picrosirius-polarization

Our group has developed an ovine model of deep dermal, partial-thickness burn where the fetus heals scarlessly and the lamb heals with scar. The comparison of collagen structure between these two different mechanisms of healing may elucidate the process of scarless wound healing. Picrosirius staining followed by polarized light microscopy was used to visualize collagen fibers, with digital capture and analysis. Collagen deposition increased with fetal age and the fibers became thicker, changing from green (type III collagen) to yellow/red (type I collagen). The ratio of type III collagen to type I was high in the fetus (166), whereas the lamb had a much lower ratio (0.2). After burn, the ratios of type III to type I collagen did not differ from those in control skin for either fetus or lamb. The fetal tissue maintained normal tissue architecture after burn while the lamb tissue showed irregular collagen organization. In conclusion, the type or amount of collagen does not alter significantly after injury. Tissue architecture differed between fetal and lamb tissue, suggesting that scar development is related to collagen cross-linking or arrangement. This study indicates that healing in the scarless fetal wound is representative of the normal fetal growth pattern, rather than a response to burn injury.

Evidence for sensitisation of DNA to oxidative damage during isolation

The oxidative base lesion 8-oxo-deoxyguanosine (8-oxo-dG) has been identified in DNA isolated from normal tissue and may occur at elevated levels during disease. However, the use of phenol during DNA extraction may artificially elevate the detected levels of this lesion. Herein, we have performed a comparative methodological study using both pronase E and phenol extraction techniques; native or oxidatively stressed DNA was isolated to determine the validity of each extraction technique for the subsequent determination of 8-oxo-dG. Whilst the yields of DNA were comparable, after pronase E extraction there was no detectable induction of 8-oxo-dG in reextracted naked DNA or peripheral blood mononuclear cell DNA that had been oxidatively stressed. However, phenol extraction enhanced the basal levels of 8-oxo-dG detected, and also induced a significant increase in levels of the modified base after exposure to oxidative stress. The latter was dependent on the presence of foetal calf serum in the extracellular medium. We have confirmed that phenol extraction sensitises native DNA to subsequent oxidative damage. In addition, this work shows that the extent of sensitisation occurring during phenol extraction varies with the degree of oxidative damage already incurred and infers that labile guanine sites generated during oxidative stress may be detected as 8-oxo-dG residues after phenol extraction.

Inhibitory effects of persistent apoptotic cells on monoclonal antibody production in vitro:simple removal of non-viable cells improves antibody productivity by hybridoma cells in culture

Cells undergoing apoptosis in vivo are rapidly detected and cleared by phagocytes. Swift recognition and removal of apoptotic cells is important for normal tissue homeostasis and failure in the underlying clearance mechanisms has pathological consequences associated with inflammatory and auto-immune diseases. Cell cultures in vitro usually lack the capacity for removal of non-viable cells because of the absence of phagocytes and, as such, fail to emulate the healthy in vivo micro-environment from which dead cells are absent. While a key objective in cell culture is to maintain viability at maximal levels, cell death is unavoidable and non-viable cells frequently contaminate cultures in significant numbers. Here we show that the presence of apoptotic cells in monoclonal antibody-producing hybridoma cultures has markedly detrimental effects on antibody productivity. Removal of apoptotic hybridoma cells by macrophages at the time of seeding resulted in 100% improved antibody productivity that was, surprisingly to us, most pronounced late on in the cultures. Furthermore, we were able to recapitulate this effect using novel super-paramagnetic Dead-Cert Nanoparticles to remove non-viable cells simply and effectively at culture seeding. These results (1) provide direct evidence that apoptotic cells have a profound influence on their non-phagocytic neighbors in culture and (2) demonstrate the effectiveness of a simple dead-cell removal strategy for improving antibody manufacture in vitro.

Em Algorithm for MLE of a Probit Model for Multiple Ordinal Outcomes

The correlated probit model is frequently used for multiple ordered data since it allows to incorporate seamlessly different correlation structures. The estimation of the probit model parameters based on direct maximization of the limited information maximum likelihood is a numerically intensive procedure. We propose an extension of the EM algorithm for obtaining maximum likelihood estimates for a correlated probit model for multiple ordinal outcomes. The algorithm is implemented in the free software environment for statistical computing and graphics R. We present two simulation studies to examine the performance of the developed algorithm. We apply the model to data on 121 women with cervical or endometrial cancer. Patients developed normal tissue reactions as a result of post-operative external beam pelvic radiotherapy. In this work we focused on modeling the effects of a genetic factor on early skin and early urogenital tissue reactions and on assessing the strength of association between the two types of reactions. We established that there was an association between skin reactions and polymorphism XRCC3 codon 241 (C>T) (rs861539) and that skin and urogenital reactions were positively correlated. ACM Computing Classification System (1998): G.3.

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.

Reverse Engineering of Modified Genes by Bayesian Network Analysis Defines Molecular Determinants Critical to the Development of Glioblastoma

In this study we have identified key genes that are critical in development of astrocytic tumors. Meta-analysis of microarray studies which compared normal tissue to astrocytoma revealed a set of 646 differentially expressed genes in the majority of astrocytoma. Reverse engineering of these 646 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 were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. All of these genes were up-regulated, except MPP2 (down regulated). These 10 genes were able to predict tumor status with 96–100% confidence when using logistic regression, cross validation, and the support vector machine analysis. Markov genes interact with NFkβ, ERK, MAPK, VEGF, growth hormone and collagen to produce a network whose top biological functions are cancer, neurological disease, and cellular movement. Three of the 10 genes - EGFR, COL4A1, and CDK4, in particular, seemed to be potential ‘hubs of activity’. Modified expression of these 10 Markov Blanket genes increases lifetime risk of developing glioblastoma compared to the normal population. The glioblastoma risk estimates were dramatically increased with joint effects of 4 or more than 4 Markov Blanket genes. Joint interaction effects of 4, 5, 6, 7, 8, 9 or 10 Markov Blanket genes produced 9, 13, 20.9, 26.7, 52.8, 53.2, 78.1 or 85.9%, respectively, increase in lifetime risk of developing glioblastoma compared to normal population. In summary, it appears that modified expression of several ‘key genes’ may be required for the development of glioblastoma. Further studies are needed to validate these ‘key genes’ as useful tools for early detection and novel therapeutic options for these tumors.

Towards the prediction of mutations in genomic sequences

Bio-systems are inherently complex information processing systems. Furthermore, physiological complexities of biological systems limit the formation of a hypothesis in terms of behavior and the ability to test hypothesis. More importantly the identification and classification of mutation in patients are centric topics in today's cancer research. Next generation sequencing (NGS) technologies can provide genome-wide coverage at a single nucleotide resolution and at reasonable speed and cost. The unprecedented molecular characterization provided by NGS offers the potential for an individualized approach to treatment. These advances in cancer genomics have enabled scientists to interrogate cancer-specific genomic variants and compare them with the normal variants in the same patient. Analysis of this data provides a catalog of somatic variants, present in tumor genome but not in the normal tissue DNA. In this dissertation, we present a new computational framework to the problem of predicting the number of mutations on a chromosome for a certain patient, which is a fundamental problem in clinical and research fields. We begin this dissertation with the development of a framework system that is capable of utilizing published data from a longitudinal study of patients with acute myeloid leukemia (AML), who's DNA from both normal as well as malignant tissues was subjected to NGS analysis at various points in time. By processing the sequencing data at the time of cancer diagnosis using the components of our framework, we tested it by predicting the genomic regions to be mutated at the time of relapse and, later, by comparing our results with the actual regions that showed mutations (discovered at relapse time). We demonstrate that this coupling of the algorithm pipeline can drastically improve the predictive abilities of searching a reliable molecular signature. Arguably, the most important result of our research is its superior performance to other methods like Radial Basis Function Network, Sequential Minimal Optimization, and Gaussian Process. In the final part of this dissertation, we present a detailed significance, stability and statistical analysis of our model. A performance comparison of the results are presented. This work clearly lays a good foundation for future research for other types of cancer.^

Development and Optimization of Four-dimensional Magnetic Resonance Imaging (4D-MRI) for Radiation Therapy

A tenet of modern radiotherapy (RT) is to identify the treatment target accurately, following which the high-dose treatment volume may be expanded into the surrounding tissues in order to create the clinical and planning target volumes. Respiratory motion can induce errors in target volume delineation and dose delivery in radiation therapy for thoracic and abdominal cancers. Historically, radiotherapy treatment planning in the thoracic and abdominal regions has used 2D or 3D images acquired under uncoached free-breathing conditions, irrespective of whether the target tumor is moving or not. Once the gross target volume has been delineated, standard margins are commonly added in order to account for motion. However, the generic margins do not usually take the target motion trajectory into consideration. That may lead to under- or over-estimate motion with subsequent risk of missing the target during treatment or irradiating excessive normal tissue. That introduces systematic errors into treatment planning and delivery. In clinical practice, four-dimensional (4D) imaging has been popular in For RT motion management. It provides temporal information about tumor and organ at risk motion, and it permits patient-specific treatment planning. The most common contemporary imaging technique for identifying tumor motion is 4D computed tomography (4D-CT). However, CT has poor soft tissue contrast and it induce ionizing radiation hazard. In the last decade, 4D magnetic resonance imaging (4D-MRI) has become an emerging tool to image respiratory motion, especially in the abdomen, because of the superior soft-tissue contrast. Recently, several 4D-MRI techniques have been proposed, including prospective and retrospective approaches. Nevertheless, 4D-MRI techniques are faced with several challenges: 1) suboptimal and inconsistent tumor contrast with large inter-patient variation; 2) relatively low temporal-spatial resolution; 3) it lacks a reliable respiratory surrogate. In this research work, novel 4D-MRI techniques applying MRI weightings that was not used in existing 4D-MRI techniques, including T2/T1-weighted, T2-weighted and Diffusion-weighted MRI were investigated. A result-driven phase retrospective sorting method was proposed, and it was applied to image space as well as k-space of MR imaging. Novel image-based respiratory surrogates were developed, improved and evaluated.

The Feasibly of Functionally Guided Intensity Modulated Radiation Therapy Treatment Planning Using Perfluoropropane-Enhanced MRI for Lung Cancer

Radiotherapy is commonly used to treat lung cancer. However, radiation induced damage to lung tissue is a major limiting factor to its use. To minimize normal tissue lung toxicity from conformal radiotherapy treatment planning, we investigated the use of Perfluoropropane(PFP)-enhanced MR imaging to assess and guide the sparing of functioning lung. Fluorine Enhanced MRI using Perfluoropropane(PFP) is a dynamic multi-breath steady state technique enabling quantitative and qualitative assessments of lung function(1).

Imaging data was obtained from studies previously acquired in the Duke Image Analysis Laboratory. All studies were approved by the Duke IRB. The data was de-identified for this project, which was also approved by the Duke IRB. Subjects performed several breath-holds at total lung capacity(TLC) interspersed with multiple tidal breaths(TB) of Perfluoropropane(PFP)/oxygen mixture. Additive wash-in intensity images were created through the summation of the wash-in phase breath-holds. Additionally, model based fitting was utilized to create parametric images of lung function(1).

Varian Eclipse treatment planning software was used for putative treatment planning. For each subject two plans were made, a standard plan, with no regional functional lung information considered other than current standard models. Another was created using functional information to spare functional lung while maintaining dose to the target lesion. Plans were optimized to a prescription dose of 60 Gy to the target over the course of 30 fractions.

A decrease in dose to functioning lung was observed when utilizing this functional information compared to the standard plan for all five subjects. PFP-enhanced MR imaging is a feasible method to assess ventilatory lung function and we have shown how this can be incorporated into treatment planning to potentially decrease the dose to normal tissue.

Epigenetics and the overhealing wound: the role of DNA methylation in fibrosis

Fibrosis is a progressive and potentially fatal process that can occur in numerous organ systems. Characterised by the excessive deposition of extracellular matrix proteins such as collagens and fibronectin, fibrosis affects normal tissue architecture and impedes organ function. Although a considerable amount of research has focused on the mechanisms underlying disease pathogenesis, current therapeutic options do not directly target the pro-fibrotic process. As a result, there is a clear unmet clinical need to develop new agents. Novel findings implicate a role for epigenetic modifications contributing to the progression of fibrosis by alteration of gene expression profiles. This review will focus on DNA methylation; its association with fibroblast differentiation and activation and the consequent buildup of fibrotic scar tissue. The potential use of therapies that modulate this epigenetic pathway for the treatment of fibrosis in several organ systems is also discussed.

Modelling responses to spatially fractionated radiation fields using preclinical image-guided radiotherapy

OBJECTIVES: Radiotherapy is planned to achieve the optimal physical dose distribution to the target tumour volume whilst minimising dose to the surrounding normal tissue. Recent in vitro experimental evidence has demonstrated an important role for intercellular communication in radiobiological responses following non-uniform exposures. This study aimed to model the impact of these effects in the context of techniques involving highly modulated radiation fields or spatially fractionated treatments such as GRID therapy.

METHODS: Using the small animal radiotherapy research platform (SARRP) as a key enabling technology to deliver precision imaged-guided radiotherapy, it is possible to achieve spatially modulated dose distributions that model typical clinical scenarios. In this work, we planned uniform and spatially fractionated dose distributions using multiple isocentres with beam sizes of 0.5 - 5 mm to obtain 50% volume coverage in a subcutaneous murine tumour model, and applied a model of cellular response that incorporates intercellular communication to assess the potential impact of signalling effects with different ranges.

RESULTS: Models of GRID treatment plans which incorporate intercellular signalling showed increased cell killing within the low dose region. This results in an increase in the Equivalent Uniform Dose (EUD) for GRID exposures compared to standard models, with some GRID exposures being predicted to be more effective than uniform delivery of the same physical dose.

CONCLUSIONS: This study demonstrates the potential impact of radiation induced signalling on tumour cell response for spatially fractionated therapies and identifies key experiments to validate this model and quantify these effects in vivo.

ADVANCES IN KNOWLEDGE: This study highlights the unique opportunities now possible using advanced preclinical techniques to develop a foundation for biophysical optimisation in radiotherapy treatment planning.

Virtual Clinical Trials in PET Imaging for Improved Diagnosis of and Evaluation of Therapies for Cancer

Thesis (Ph.D.)--University of Washington, 2016-08

Giant condyloma acuminatum quickly growing. Case report

Background. Giant Condyloma Acuminatum (GCA) is a rare, slow growing, large cauliflower tumor of the penile foreskin and perianal region with benign histologic appearance but high propensity for local invasion and recurrences. GCA is associated with Human Papilloma Virus (HPV) types 6 and 11 and it also has considerable risk of neoplastic transformation into fully invasive squamous cell carcinoma into about 5 years. Objective. Because of the rarity of perianal GCA, to date there is no general agreement on the best method for treatment. We wanted to know if surgical approach only was a good method to treat our case. Case report. A 28 years old man, HIV-negative, with a 4 years history of perianal GCA quickly growing underwent full tickness local excision at least 0,7 cm margin of normal tissue with skin grafting taken from the thighs. Fecal contamination was avoided by diet and loperamide per os. At two years follow-up no recurrence was detected. Conclusion. Surgical approach with full tickness excision and immediate skin-grafting and regular follow-up demonstrated effective to treat GCA and to minimize disease recurrence.

Biological ageing and colorectal cancer: fetuin A, sirtuins and telomeres at the interface between inflammation, metabolism and cancer

Colorectal cancer is a common, age-associated disease with significant comorbidity and mortality. Biomarkers of ageing may have prognostic or predictive value in colorectal cancer. Fetuin A, members of the sirtuin family of proteins and telomeres have shown promise as potential biomarkers of ageing. AIM: To evaluate these potential biomarkers in the context of colorectal cancer. METHODS: Two cohorts of patients were used. Telomere length was measured in peripheral blood leukocytes (PBL), and for a subset of patients, in normal colorectal and colorectal tumour tissue. Serum fetuin A was measured for these patients and data on clinico-pathological factors of accepted significance in colorectal cancer was collected prospectively. Telomere length in the matched samples of leukocytes, normal colorectal and colorectal tumour tissue was compared. Associations between telomere length in the different tissues, serum fetuin A and clinico-pathological factors of accepted significance in colorectal cancer were evaluated. A systematic review of the literature was performed to examine the evidence for correlation between telomere length in different tissues in humans. Tissue from colorectal tumours from the second cohort patients was mounted in a tissue microarray (TMA) and stained for sirtuin proteins (SIRT2-SIRT7). This TMA also contained tissue from a subset of matched samples of adjacent normal colorectal mucosa. Staining of normal colorectal and colorectal tumour tissue was evaluated by the weighted Histoscore method and compared. The effect of staining in tumour tissue on cancer-specific survival was examined. Associations between Histoscores and clinico-pathological factors of accepted significance in colorectal cancer were assessed. RESULTS: Systematic review of the literature did not show robust evidence of correlation between telomere length in different tissues in humans. Telomere length in peripheral blood leukocytes did not show correlation with telomere length in normal colorectal mucosa, or in colorectal tumour tissue. PBL telomere length was potentially related to the presence of distant metastases. Fetuin A was inversely associated with markers of systemic inflammation and with T stage. Novel nuclear localisation was described for SIRT4 and SIRT5. Protein expression of the sirtuins was reduced in tumour tissue in comparison to normal colorectal mucosa, apart from SIRT3 cytoplasmic and nuclear and SIRT6 nuclear stainng. Lowest and highest quartile SIRT2 expression was associated with worse survival. Sirtuin protein expression levels and localisation correlate with increased systemic inflammation and pathological markers of poor prognosis in tumour tissue. Intercorrelations between sirtuin expression levels in normal tissue are not seen in tumour tissue, possibly indicating a breakdown of signalling and control.

Cell-cell communication in three dimensional microenvironments

Cellular behavior is dependent on a variety of extracellular cues required for normal tissue function, wound healing, and activation of the immune system. Removed from their in vivo microenvironment and cultured in vitro, cells lose many environmental cues and that may result in abberant behavior, making it difficult to study cellular processes. In order to mimic native tissue environments, optical tweezer and microfluidic technologies were used to place cells within defined areas of the culture environment. To provide three dimensional supports found in natural tissues, hydrogel scaffolds of poly (ethylene glycol) diacrylate and the basement membrane matrix Matrigel were used. Optical tweezer technology allowed precision placement and formation of homotypic and heterotypic arrays of human U937, HEK 293, and porcine mesenchymal stem cells. Alternatively, two microfluidic devices were designed to pattern Matrigel scaffolds. The first microfluidic device utilized laminar flow to spatially pattern multiple cell types within the device. Gradients of soluble molecules were then be formed and manipulated across the Matrigel scaffolds. Patterning Matrigel using laminar flow techniques require microfluidic expertise and do not produce consistent patterning conditions, limiting their use difficult in most cell culture laboratories. Thus, a buried Matrigel polydimethylsiloxane (PDMS) device was developed for spatial patterning of biological scaffolds. Matrigel is injected into micron sized channels of PDMS fabricated by soft lithography and allowed to thermally cure. Following curing, a second PDMS device was placed on top of the buried Matrigel channels to support media flow. In order to validate these systems, a cell-cell communication model system was developed utilizing LPS and TNFα signaling with fluorescent reporter systems to monitor communication in real time. We demonstrated the utility of microfluidic devices to support the cell-cell communication model system by co culturing three cell types within Matrigel scaffolds and monitoring signaling activity via fluorescent reporters.