Spatiotemporal modeling and model restructuration approaches in studies of intracellular signalling pathways

The main focus of the research is to understand the complex phenomena of cell transduction pathways and cell biology in a single cell. Mathematical modeling and experimental evaluation are widely used approaches for this kind of research. Firstly, A multiscale framework for protein-protein interaction has been established using Brownian dynamics algorithm. Sit specific feature, steric collision, diffusion, co-localization and complex formation with time and space has been included in this spatial modeling framework. By implementation of the time adaptive feature in this framework, the computation time reduces in an order of magnitude compared with traditional modeling framework. This multiscale Brownian framework has been used for the investigation FcεRI aggregation which is an important signaling pathway for immune cells. Using the spatial modeling framework, FcεRI aggregation in the presence of trivalent antigen showed consistent results with current experimental studies. Secondly, the rule-based modeling approach is an excellent way of performing large biochemical network modeling for a single cell as it considers the site-specific features. However, the major difficulty of rule-based modeling approach is combinatorial complexity. In this study, model restructuring approaches have been applied to overcome this problem for cell signaling pathway modeling. These mechanistic modeling approaches are very effective to model large network of signaling pathways together without compromising the accuracy. Finally, Cell size dependent cellular uptake study carried out using confocal microscopy and flow cytometer. To understand the particle uptake behavior with time and steady state condition, reaction-diffusion and kinetics model has been developed in these work. After a detailed analysis of experimental data and models, it showed that total particle uptake is increasing with cell size, however, particle flux is reducing in larger cells --Abstract, page iv

Identification of mechanisms of gemcitabine resistance using a whole genome shRNA screen in a novel in vitro coculture model of pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most difficult to treat major cancers, with a 5-year survival of less than 5%, and little to no improvement in prognosis over the previous fifty years. The complexity and heterogeneity of the pancreatic tumour and its highly desmoplastic stromal microenvironment present major physical and biochemical barriers to the delivery and efficacy of therapeutics. Improving the success rate of therapeutic interventions for this cancer requires both a detailed understanding of stromal dynamics and drug resistance within the tumour, as well validated in vitro and in vivo models through which novel therapeutic targets can be identified and investigated. Within this project I focused initially on further developing, validating, and evaluating mechanistically a coculture model of gemcitabine resistance, established previously. I demonstrated that the gemcitabine resistance observed in coculture was a product of cell-cell contact, transient in nature, and related to cell density-mediated signalling processes. I discovered that the mesenchymal-like cell lines thought to drive the resistance effect within the model were epithelial cancer cells in origin, rather than a cancer associated fibroblast (CAF) line, verified through genotype and protein signature experiments. This finding was expanded through demonstration that true pancreatic CAFs did not induce gemcitabine resistance in the coculture model and hence demonstrated the real challenge in isolating true pancreatic CAFs from genetically engineered mouse PDAC tumour tissue using canonical techniques. Nevertheless, the in vitro coculture model data was congruent with in vivo and clinical gemcitabine efficacy data, suggesting it may have utility as a lower cost model for evaluating efficacy of novel drug combinations with the aim of subsequent translation into the clinic. The coculture model was used as the foundation of a genome-wide shRNA depletion screen to identify sensitizers of gemcitabine resistance in PDAC in vitro culture. The primary screen and subsequent validation screen identified 19 high confidence genes with potential translational value, of which knockdown sensitised to gemcitabine within this model. This is alongside an expanded list of 444 genes significantly contributing to the resistance phenotype, representing pathways such as MTORC signalling and DNA damage response. This dataset serves as the first shRNA-mediated coculture screen for gemcitabine resistance in PDAC. My findings lay credence to the value of this model of gemcitabine resistance for preclinical use and provides a robust and voluminous shRNA dataset supporting target identification for the ablation of gemcitabine chemoresistance in PDAC.Cancer Research UK PhD Studentshi

New Advances in Melanoma

Melanoma is a very aggressive tumor which is derived from the transformation of pigment-producing cells termed the melanocytes. This cancer type accounts for most of the deaths associated with skin cancer as well as its incidence and is in constant evolution. Because of the rapid and very high metastatic potential of this tumor, melanoma prognosis has been quite poor for a long time. In the past decade, groundbreaking discoveries in the melanoma research field have led to the development of two main treatment strategies: combination therapies targeting specific kinases or combination therapies focused on immune checkpoint inhibitors (ICIs). These treatment approaches have become the standard of care in most cancer centers and significantly improved the prognosis and overall survival of advanced melanoma patients. Nevertheless, many patients do not benefit from or even respond to these treatments. It is therefore essential to better comprehend the phenomenon of drug resistance, immune escape mechanisms, as well as to search for alternative treatment strategies. In addition, strong predictive biomarkers are desperately needed to improve clinical efficacy. The aim of this Special Issue is to present recent advances in the field of melanoma research, in which the abovementioned areas represent the primary focus, and other relevant themes are also discussed

Regulation of metabolism by the oncoprotein c-Myc

c-Myc (hereafter Myc), a transcription factor that regulates a variety of cellular functions including growth and differentiation, is deregulated in many different types of cancers. Myc regulates the Warburg effect and oncogenic biosynthesis, but also many aspects of metabolism, believed to be a pivotal point of transformation. Myc is known to control glycolysis and glutaminolysis but little is known about the interplay between glucose, amino acid, and fatty acid oxidation. We hypothesize Myc integrates glucose, amino acid, and fatty acid utilization for energy, and either loss- or gain-of-function will disrupt metabolic homeostasis. Loss of Myc in rat fibroblasts elicits a severe energy deficit, including diminished acetyl-coA levels, to which they respond by enhancing FAO and lipid uptake and storage. Using an in vivo model, we found murine hepatocytes respond to Myc ablation with a milder phenotype. They display metabolic defects, including reduced respiratory chain capacity and an increased metabolic rate when fed a high-fat diet. Additionally, hepatocytes had major lipid defects including transcriptional deregulation, lipid accumulation and increased FAO. Reduced ATP in Myc KO fibroblasts constitutively activates AMPK, a protein which limits anabolism for catabolism, leading us to hypothesize AMPK may play a role in Myc deregulated phenotypes. We found AMPK controls mitochondrial structure and function in conjunction with Myc over-expression, via redox state, electron transport chain (ETC) capacity, and TCA cycle dehydrogenases. Additionally, AMPK KO cells demonstrate transcriptional and translational differences and differential responses in regulating glycolysis, which results in REGULATION OF METABOLISM BY THE ONCOPROTEIN C-MYC Lia Rae Edmunds, Ph.D. University of Pittsburgh, 2015 v metabolite dysfunction, when exposed to Myc over-expression. Thus, AMPK is critical to supporting metabolic pathways in response to Myc deregulation. To ascertain if Myc plays a role in hepatic proliferative capacity, we turned to a mouse model of hereditary tyrosinemia. We definitively proved that Myc is not required for prolonged hepatocyte proliferation, even in direct competition with Myc-replete hepatocytes. Proliferating KO hepatocytes were associated with a pro-inflammatory environment that correlated with worsening lipid accumulation and lipid oxidation-mediated liver damage, a phenotype reminiscent of non-alcoholic fatty liver-like disease. Throughout this work, we reveal Myc-regulated metabolism is vital for maintaining lipid homeostasis and energy production, but dispensable for sustained hepatic proliferation