Assessing the carcinogenic potential of low-dose exposures to chemical mixtures in the environment: the challenge ahead.

Lifestyle factors are responsible for a considerable portion of cancer incidence worldwide, but credible estimates from the World Health Organization and the International Agency for Research on Cancer (IARC) suggest that the fraction of cancers attributable to toxic environmental exposures is between 7% and 19%. To explore the hypothesis that low-dose exposures to mixtures of chemicals in the environment may be combining to contribute to environmental carcinogenesis, we reviewed 11 hallmark phenotypes of cancer, multiple priority target sites for disruption in each area and prototypical chemical disruptors for all targets, this included dose-response characterizations, evidence of low-dose effects and cross-hallmark effects for all targets and chemicals. In total, 85 examples of chemicals were reviewed for actions on key pathways/mechanisms related to carcinogenesis. Only 15% (13/85) were found to have evidence of a dose-response threshold, whereas 59% (50/85) exerted low-dose effects. No dose-response information was found for the remaining 26% (22/85). Our analysis suggests that the cumulative effects of individual (non-carcinogenic) chemicals acting on different pathways, and a variety of related systems, organs, tissues and cells could plausibly conspire to produce carcinogenic synergies. Additional basic research on carcinogenesis and research focused on low-dose effects of chemical mixtures needs to be rigorously pursued before the merits of this hypothesis can be further advanced. However, the structure of the World Health Organization International Programme on Chemical Safety 'Mode of Action' framework should be revisited as it has inherent weaknesses that are not fully aligned with our current understanding of cancer biology

The Importance of Constraints and Control in Biological Mechanisms: Insights from Cancer Research

Research on diseases such as cancer reveals that primary mechanisms, which have been the focus of study by the new mechanists in philosophy of science, are often subject to control by other mechanisms. Cancer cells employ the same primary mechanisms as healthy cells, but control them differently. I use cancer research to highlight just how widespread control is in individual cells. To provide a framework for understanding control, I reconceptualize mechanisms as imposing constraints on flows of free energy, with control mechanisms operating on flexible constraints in primary mechanisms. Control mechanisms themselves often form complex, integrated networks

The role of acidity in tumour development

Acidic pH is a common characteristic of human tumours. It has a significant impact on tumour progression and response to therapies. In this thesis, we utilise mathematical modelling to examine the role of acidosis in the interaction between normal and tumour cell populations. In the first section we investigate the cell–microenvironmental interactions that mediate somatic evolution of cancer cells. The model predicts that selective forces in premalignant lesions act to favour cells whose metabolism is best suited to respond to local changes in oxygen, glucose and pH levels. In particular the emergent cellular phenotype, displaying increased acid production and resistance to acid-induced toxicity, has a significant proliferative advantage because it will consistently acidify the local environment in a way that is toxic to its competitors but harmless to itself. In the second section we analyse the role of acidity in tumour growth. Both vascular and avascular tumour dynamics are investigated, and a number of different behaviours are observed. Whilst an avascular tumour always proceeds to a benign steady state, a vascular tumour may display either benign or invasive dynamics, depending on the value of a critical parameter. Extensions of the model show that cellular quiescence, or non-proliferation, may provide an explanation for experimentally observed cycles of acidity within tumour tissue. Analysis of both models allows assessment of novel therapies directed towards changing the level of acidity within the tumour. Finally we undertake a comparison between experimental tumour pH images and the models of acid dynamics set out in previous chapters. This analysis will allow us to assess and verify the previous modelling work, giving the mathematics a firm biological foundation. Moreover, it provides a methodology of calculating important diagnostic parameters from pH images

Hallmarks of Cancer: The Next Generation

The hallmarks of cancer comprise six biological capabilities acquired during the multistep development of human tumors. The hallmarks constitute an organizing principle for rationalizing the complexities of neoplastic disease. They include sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis. Underlying these hallmarks are genome instability, which generates the genetic diversity that expedites their acquisition, and inflammation, which fosters multiple hallmark functions. Conceptual progress in the last decade has added two emerging hallmarks of potential generality to this list—reprogramming of energy metabolism and evading immune destruction. In addition to cancer cells, tumors exhibit another dimension of complexity: they contain a repertoire of recruited, ostensibly normal cells that contribute to the acquisition of hallmark traits by creating the “tumor microenvironment.” Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer

Cell-Free Enabled Bioproduction and Biological Discovery

As our understanding of the microbial world has progressed, so too has the backlog of information and open questions generated from the thousands of uncharacterized proteins and metabolites with potential applications as biofuels, therapeutics, and biomaterials. To address this problem, new tools need to be developed in order to rapidly test and take advantage of uncharacterized proteins and metabolites. Cell-free systems have developed into a high-throughput and scalable tool for synthetic biology and metabolic engineering with applications across multiple disciplines. The work presented in this dissertation leverages cell-free systems as a conduit for the exploration of protein function and metabolite production using two complementary approaches. The first elucidates interaction networks associated with secondary metabolite production using a computationally assisted pathway description pipeline that employs bioinformatic searches of genome databases, structural modeling, and ligand-docking simulations to predict the gene products most likely to be involved in a metabolic pathway. In vitro reconstructions of the pathway are then modularly assembled and chemically verified in Escherichia coli lysates in order to differentiate between active and inactive pathways. The second takes a systems and synthetic biology approach to engineer Escherichia coli extracts capable of directing flux towards specific metabolites. Using growth and genome engineering-based methods, we produced cell-free proteomes capable of creating unconventional metabolic states with minimal impact on the cell in vivo. As a result of this work, we have significantly expanded our ability to use cell extracts outside of their native context to solve metabolic engineering problems and provide engineers new tools that can rapidly explore the functions of proteins and test novel metabolic pathways

Dealing with diversity in computational cancer modeling.

This paper discusses the need for interconnecting computational cancer models from different sources and scales within clinically relevant scenarios to increase the accuracy of the models and speed up their clinical adaptation, validation, and eventual translation. We briefly review current interoperability efforts drawing upon our experiences with the development of in silico models for predictive oncology within a number of European Commission Virtual Physiological Human initiative projects on cancer. A clinically relevant scenario, addressing brain tumor modeling that illustrates the need for coupling models from different sources and levels of complexity, is described. General approaches to enabling interoperability using XML-based markup languages for biological modeling are reviewed, concluding with a discussion on efforts towards developing cancer-specific XML markup to couple multiple component models for predictive in silico oncology

Understanding the Warburg Phenotype and the Metabolic Plasticity of Proliferative Mammalian Cells Using \u3csup\u3e13\u3c/sup\u3eC Metabolic Flux Analysis

Proliferative cells, including many types of cancer and pluripotent stem cells, rely primarily on glycolysis and lactate metabolism for energy, regardless of oxygen availability. This metabolic phenotype – referred to as the Warburg effect – results in wasteful lactate accumulation. Although cancer cells and pluripotent stem cells share this central metabolic characteristic, the sensitivities of each of these cell types to lactate stress appear contradictory. While lactate accumulation is thought to adversely impact pluripotent stem cell proliferation and differentiation capacities, cancer cells have been shown to possess bioenergetic plasticity to utilize lactate catabolism for fuel. As a result, lactate buildup within the hypoxic tumor microenvironment has been hypothesized to promote cancer progression and malignancy, in part by selecting for cancer populations capable of catabolizing lactate. Moreover, lactate has been shown to promote stemness gene expression in cancer, suggesting that lactate plays a functional role in regulating pluripotency gene expression. However, an incomplete understanding of the impact of lactate on intracellular metabolism for proliferative cells remains. In this work, 13C-metabolic flux analysis was used to quantify the intracellular metabolic responses of breast cancer cells and induced pluripotent stem cells (iPSCs) to high extracellular lactate; in particular, to determine the role of lactate as a metabolic substrate. In this research, it was demonstrated that both iPSCs and breast cancer cells employ dual consumption of glucose and lactate to support growth. In addition, this is the first study to determine and quantify intracellular contribution of lactate in proliferative iPSC metabolism. These results provide insight into the metabolic flexibility of highly proliferative cells with respect to lactate metabolism and suggest that, much like many types of cancer cells, iPSCs possess the capacity to metabolize lactate to promote exponential growth and maintain pluripotency