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This dissertation proposes tools and analysis of mutational signatures in human cancer and their application to the stratification of patients for drug response. To provide a comprehensive workflow for preprocessing, analysis, and visualization of mutational signatures, I created the Mutational Signature Comprehensive Analysis Toolkit (musicatk) package. musicatk enables users to select different schemas for counting mutation types and easily combine count tables from different schemas. Multiple distinct methods are available to deconvolute signatures and exposures or to predict exposures in individual samples given a pre-existing set of signatures. Additional exploratory features include the ability to compare signatures to the COSMIC database, embed tumors in two dimensions with UMAP, cluster tumors into subgroups based on exposure frequencies, identify differentially active exposures between tumor subgroups, and plot exposure distributions across user-defined annotations such as tumor type. I then use musicatk to analyze the largest tumor sequencing dataset from a Chinese population to date. I identified differences in the levels of signature exposures compared to similar data from a Western cohort. Specifically, COSMIC signature SBS25 was higher in the Chinese dataset for Melanoma and Renal Cell Carcinoma patients and Melanoma patients had lower levels of SBS7a/b (Ultraviolet Light). My analysis also revealed a putative novel signature enriched in pancreatic cancers. Lastly, I assess the ability of mutational signatures to identify patients who may respond to irofulven, a drug for late-stage cancer patients who have defects in the Transcription Coupled Nucleotide Excision Repair (TC-NER) pathway. As the functional understanding of which mutations successfully disrupt this pathway is incomplete, I develop an approach that classifies patients based on evidence of this pathway being disrupted based on levels of mutational signatures. I build a model that successfully predicts patients who will respond to treatment without a known relevant mutation in the TC-NER pathway. The work from this study furthers our understanding of mutational signatures in different populations and demonstrates the feasibility of using mutational signatures to identify patients eligible for drug trials.

Indiana University-Purdue University Indianapolis (IUPUI) / In this study we compared the distribution of HPV types in cervical cancer specimens from women living in either Indiana or Botswana. Paraffin-embedded blocks of formalin-fixed cervical cancer specimens were identified from women living in Indiana (n=51) or Botswana (n=171)

Genomic DNA is constantly exposed to assaults, which if not dealt with, can lead to genomic instability and carcinogenesis. In response to stress including either Ionising Radiation (IR) or replication stress, ATM and ATR promote the activation of cell cycle checkpoints and initiate repair of DNA damage. Recent studies have revealed that ATM signalling can activate LATS1 via a cascade through RASSF1A and MST2. LATS1 is a tumour suppressor, which forms a barrier to carcinogenesis restricting cell proliferation and promoting apoptosis by stabilising a YAP/p73 transcriptional complex, hence upregulating p73 responsive genes. LATS1 is inactivated through promoter hypermethylation in a number of cancer types including breast cancer and soft tissue sarcoma. This research project seeks to define the mechanism through which LATS1 is involved in IR-induced DNA damage signalling. The data presented in this thesis shows that LATS1 controls CDK2 and regulates phosphorylation of S3291 on BRCA2. Cells lacking LATS1 exhibited enhanced accumulation of damage-induced Rad51 foci leading to cell cycle arrest at the G₂/M checkpoint. Furthermore, the data presented here suggests that LATS1 may not be required for homologous recombination. This work supports the hypothesis that LATS1 inhibits CDK2-dependent phosphorylation of BRCA2 at S3291, hence protecting stalled replication forks from nucleolytic degradation.

Cette thèse propose un algorithme de mosaïquage pour la construction d'images panoramiques des parois internes de la vessie. Le temps de construction de ces images correspondant aux parties intéressantes de la vessie doit être inférieur à la durée d'un examen clinique standard. La méthode de mosaïquage doit aussi être robuste vis-à-vis des variabilités inter-examens liées aux patients et aux instruments. Ces images panoramiques pourront être utilisées par le clinicien comme référence pour guider des examens ultérieurs, pour l'archivage des données et pour suivre l'évolution des lésions. La première étape de l'algorithme est le pré-traitement des images cystoscopiques consistant en l'atténuation des inhomogénéités d'illumination et du motif de fibres optiques visible dans les images acquises par un fibroscope. La deuxième étape est le recalage des images. La solution retenue consiste en la corrélation par les transformées de Fourier des images qui fournit des translations initiales à un algorithme itératif basé sur la différence d'intensité entre les images. Ce dernier délivre les paramètres de la transformation perspective reliant deux images successives de la séquence. Dans la troisième étape nous projetons les images dans un repère commun en utilisant des transformations globales calculées avec les résultats des recalages. Nous utilisons un moyennage pondéré des intensités des pixels pour atténuer les bords visibles lors de la projection. Les résultats quantitatifs obtenus avec un fantôme et des résultats qualitatifs calculés pour des séquences réelles montrent que notre approche automatique de mosaïquage est robuste et rapide (temps compatible avec la durée d'un examen cystoscopique clinique). Nos tests ont également prouvé que l'algorithme de recalage fonctionne pour des transformations géométriques plus grandes que celles rencontrées typiquement entre images d'une séquence vidéo (90% de recouvrement entre images consécutives pour ces dernières) / This work describes a mosaicing algorithm for constructing panoramic images of internal walls of the bladder. Time relating to the construction of panoramic images including the interesting parts must be shorter than that required by a standard cystoscopic examination. The mosaicing algorithm must be robust against lighting conditions, morphologic and texture variations relating to instruments and patient anatomy. These panoramic images could be used by a clinician for guiding further exams, storing non-redundant data and following-up evolution of lesions. The preprocessing of cystoscopic images is the first stage of the algorithm. Preprocessing consists of shading correction and fiber optics pattern attenuation occurring in fiberscope acquired images. The second stage is image registration. The chosen solution consist of cross-correlating images (using their Fourier transforms) in order to have initial translations for an iterative registration algorithm based on the sum of squared differences of images. In the third stage, images are projected in the coordinate system of the panoramic image using global transformations computed with matrices given by the iterative registration. We use a weighted average of pixel intensities to blend visible borders of images produced in the projection process. Numerical results obtained with a phantom and qualitative results obtained with real sequences show that our automatic approach is robust and allows for a fast construction of panoramic images in a period of time that is shorter than the duration of a clinical cystoscopic examination. Our experiments showed that the registration algorithm can handle geometric transformations that are larger than those existing typically in a video-sequence (90% of superposition between successive images in this case)

Das Leben und Überleben einer Zelle wird auf verschiedenen Ebenen streng reguliert. Diese Ebenen sind eng miteinander verknüpft: (i) Signalwege leiten extrazelluläre Signale in den Zellkern, wo (ii) Genregulation sie zu Proteinen übersetzt, und (iii) Proteine kontrollieren metabolische Funktionen, die Nährstoffe zu Energie und zellulären Bausteinen konvertieren. Diese Systeme sind hochkomplex und werden oft nur einzeln betrachtet. Systembiologie ist ein interdisziplinäres Forschungsgebiet, das Methoden anbietet, um Informationen aus heutigen Hochdurchsatz-Experimenttechnologien zu extrahieren. Diese Methoden können effektiv sein, um die vorgenannten Systeme einzeln oder im Ganzen zu untersuchen. In dieser Doktorarbeit wende ich Methoden an, um Signalwege und Zellmetabolismus zu erforschen, und ich präsentiere neue Arbeitsabläufe für das Modellieren und Analysieren dieser Systeme. Beide Methoden sind auf großskalige Netzwerkrekonstruktionen fokussiert. Da die Erhältlichkeit von xperimentellen Daten eines der größten Probleme der Systembiologie darstellt, befassen sich die Methoden explizit mit dem Umgang mit Wissenslücken. Sie werden auf den Snf1 Signalweg und den Metabolismus von Hefezellen angewendet und vermitteln neue Erkenntnisse über diesen Modellorganismus. Des Weiteren präsentiert diese Arbeit eine eingehende Analyse vom metabolischen Reprogrammieren in Darmkrebszellen, welche bisher unbekannte Zusammenhänge von metabolischer Funktionalität und Onkogenen beinhaltet. Zum Abschluss stelle ich unseren Vorschlag für ein standardisiertes Datenaustauschformat vor, welches seinen Schwerpunkt auf Datentabellen der Systembiologie legt. Zusammenfassend behandelt diese Doktorarbeit die Signalwege und den Metabolismus von Zellen, inklusive neuer Modellierabläufe und biologischer Erkenntnisse. Diese Erkenntnisse werden in den Kontext unseres aktuellen Wissensstandes gesetzt und darauf aufbauend werden neue potentielle Ansatzpunkte für Experimente vorgeschlagen. / Cellular life is governed on different layers of regulation, which are tightly interconnected: (i) Signalling pathways transmit extracellular signals to the cells’ nucleus, where (ii) gene regulation translates these signals into proteins, and (iii) proteins control metabolic functions, which convert nutrients to energy and cell building blocks. Due to the complexity of each of these systems, they are often analysed individually or only partially. Systems Biology is an interdisciplinary field of research that offers techniques to harvest the information of todays high-throughput experiments. These techniques can be powerful approaches to investigate the aforementioned regulatory layers of a cell either individually or as a whole. In this thesis, I am employing means of Systems Biology to explore signalling pathways and metabolism, and I provide novel workflows for modelling and exploring these systems. Both workflows are focussed on accurate large-scale network reconstructions of the target system. Since one of the major problems in Systems Biology is the availability of experimental data, the workflows put emphasis on the handling of knowledge gaps. They are applied on the Snf1 pathway and metabolism in yeast and provide new findings about this model organism. Furthermore, this thesis presents an in-depth analysis of metabolic reprogramming in colorectal cancer cells, which yields previously unknown coherences of metabolic function and oncogenes. Finally, I am presenting a proposal for a standardised data format in Systems Biology, which is based on data tables. In summary, this thesis comprises works on signalling pathways and cell metabolism, which includes novel modelling workflows and new biological findings, analyses their impact on the scientific state of the art, and proposes directions for new experimental targets.

The purpose of this research is to validate various forms of mathematical modeling of glioblastoma multiforme (GBM) expressed as differential equations, numerically. The first work was involved in the numerical solution of the reaction-convection model, efficacy of which is expressed in terms of survival time. It was calculated using simple numerical scheme for the standard-of-care treatment in clinics which includes surgery followed by the radiation and chemotherapy. Survival time using all treatment options increased significantly to 57 weeks compared to that of surgery close to 14 weeks. It was also observed that survival time increased significantly to 90 weeks if tumor is totally resected. In reaction-diffusion model using simple numerical scheme, tumor cell density patterns due to variation in patient specific tumor parameters such as net proliferation rate and diffusion coefficient were computed. Significant differences were observed in the patterns while using dominant diffusion and proliferation rate separately. Numerical solution of the tumor growth model under the anti-angiogenic therapy revealed some impacts in optimum tumor growth control however it was not significant. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection

Ovarian Cancer is the 5th most common cause of cancer death in women and the second most common gynaecological cancer in the UK. Worldwide, around 152,000 women were estimated to have died from ovarian cancer in 2012. Survival rates for women with epithelial ovarian cancer have not significantly changed since platinum-based treatment was introduced over 30 years ago. This is particularly disconcerting considering the fact that there is a less than 5% five year survival rate for patients diagnosed with late stage high grade serous ovarian cancer. This thesis examines the role of BMP signalling in ovarian cancer using in vitro cancer cell models. It builds upon the initial published work by the Inman lab identifying autocrine BMP9 as a promoter of ovarian cancer cell proliferation. The findings of Chapters 3-5 provide strong evidence indicating BMP9 as a context specific modulator of ovarian cancer cell proliferation. This significantly builds upon on the sole pro-proliferative BMP9 growth response previously described. Responding cell lines were subjected to a microarray with and without BMP9 treatment In order to determine early BMP target genes which were subsequently transiently knocked down in order to determine their role in the aetiology of said growth phenotype. ID1 gene expression was found to significantly contribute to the BMP9 proproliferative phenotype. Moreover several other BMP genes identified significantly alter basal cell proliferation. It was subsequently determined that BMP9 implemented a cell growth phenotype by negating apoptosis. .Excitingly, preliminary evidence suggests a marked reduction in detectable levels of a recently described Bax isoform, Bax β that coincide with BMP9 addition and the resultant anti-apoptotic phenotype observed. This is very interesting as no prior evidence correlating the BMP family and Bax β currently exists. These findings provide an enhanced understanding of BMP9s contribution to ovarian cancer pathogenesis that may result in the development of effective and targeted therapeutic interventions upon further stratification of the contextuality of the BMP induced growth response.

Epigenetics plays an important role in carcinogenesis with heritable changes in DNA methylation and histone modifications intricately linked to the initiation, promotion, and progression of cancer. Evidence shows that a number of chemical and physical agents can induce epigenetic changes during carcinogenesis. Two such agents, estrogen and ionizing radiation, are generally recognized as being carcinogenic. Yet the epigenetic repercussions of these carcinogens remain relatively unknown. More importantly, the combined effect of these carcinogens has never been addressed in vivo from an epigenetic standpoint. Therefore, we focused on the effect of estrogen and ionizing radiation applied separately or in conjunction. We have found that the exposure to estrogen, either alone or in combination with radiation, induced pronounced morphological alterations, which was paralleled by modifications to the epigenomic landscape in the mammary gland. The results obtained from these rodent models can potentially be extrapolated to humans. / xiv, 190 leaves : ill. (chiefly col.) ; 29 cm