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: Over the years, numerous groups have employed human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) as a superb human-compatible model for investigating the function and dysfunction of cardiomyocytes, drug screening and toxicity, disease modeling and for the development of novel drugs for heart diseases. In this review, we discuss the broad use of iPSC-CMs for drug development and disease modeling, in two related themes. In the first theme-drug development, adverse drug reactions, mechanisms of cardiotoxicity and the need for efficient drug screening protocols-we discuss the critical need to screen old and new drugs, the process of drug development, marketing and Adverse Drug reactions (ADRs), drug-induced cardiotoxicity, safety screening during drug development, drug development and patient-specific effect and different mechanisms of ADRs. In the second theme-using iPSC-CMs for disease modeling and developing novel drugs for heart diseases-we discuss the rationale for using iPSC-CMs and modeling acquired and inherited heart diseases with iPSC-CMs.

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BACKGROUND: Not all the mutations are equally important for the development of metastasis. What about their order? The survival of cancer cells from the primary tumour site to the secondary seeding sites depends on the occurrence of very few driver mutations promoting oncogenic cell behaviours. Usually these driver mutations are among the most effective clinically actionable target markers. The quantitative evaluation of the effects of a mutation across primary and secondary sites is an important challenging problem that can lead to better predictability of cancer progression trajectory. RESULTS: We introduce a quantitative model in the framework of Cellular Automata to investigate the effects of metabolic mutations and mutation order on cancer stemness and tumour cell migration from breast, blood to bone metastasised sites. Our approach models three types of mutations: driver, the order of which is relevant for the dynamics, metabolic which support cancer growth and are estimated from existing databases, and non-driver mutations. We integrate the model with bioinformatics analysis on a cancer mutation database that shows metabolism-modifying alterations constitute an important class of key cancer mutations. CONCLUSIONS: Our work provides a quantitative basis of how the order of driver mutations and the number of mutations altering metabolic processis matter for different cancer clones through their progression in breast, blood and bone compartments. This work is innovative because of multi compartment analysis and could impact proliferation of therapy-resistant clonal populations and patient survival. Mathematical modelling of the order of mutations is presented in terms of operators in an accessible way to the broad community of researchers in cancer models so to inspire further developments of this useful (and underused in biomedical models) methodology. We believe our results and the theoretical framework could also suggest experiments to measure the overall personalised cancer mutational signature.

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Since Otto Warburg made the first observation that tumor cells exhibit altered metabolism and bioenergetics in the 1920s, many scientists have tried to further the understanding of tumor bioenergetics. Particularly, in the past decade, the application of the state-of the-art metabolomics and genomics technologies has revealed the remarkable plasticity of tumor metabolism and bioenergetics. Firstly, a wide array of tumor cells have been shown to be able to use not only glucose, but also glutamine for generating cellular energy, reducing power, and metabolic building blocks for biosynthesis. Secondly, many types of cancer cells generate most of their cellular energy via mitochondrial respiration and oxidative phosphorylation. Glutamine is the preferred substrate for oxidative phosphorylation in tumor cells. Thirdly, tumor cells exhibit remarkable versatility in using bioenergetics substrates. Notably, tumor cells can use metabolic substrates donated by stromal cells for cellular energy generation via oxidative phosphorylation. Further, it has been shown that mitochondrial transfer is a critical mechanism for tumor cells with defective mitochondria to restore oxidative phosphorylation. The restoration is necessary for tumor cells to gain tumorigenic and metastatic potential. It is also worth noting that heme is essential for the biogenesis and proper functioning of mitochondrial respiratory chain complexes. Hence, it is not surprising that recent experimental data showed that heme flux and function are elevated in non-small cell lung cancer (NSCLC) cells and that elevated heme function promotes intensified oxygen consumption, thereby fueling tumor cell proliferation and function. Finally, emerging evidence increasingly suggests that clonal evolution and tumor genetic heterogeneity contribute to bioenergetic versatility of tumor cells, as well as tumor recurrence and drug resistance. Although mutations are found only in several metabolic enzymes in tumors, diverse mutations in signaling pathways and networks can cause changes in the expression and activity of metabolic enzymes, which likely enable tumor cells to gain their bioenergetic versatility. A better understanding of tumor bioenergetics should provide a more holistic approach to investigate cancer biology and therapeutics. This review therefore attempts to comprehensively consider and summarize the experimental data supporting our latest view of cancer bioenergetics.