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Dissecting the Intracellular Molecular Mechanisms to Address Pathogenesis of Multifactorial Diseases

蒲, 香苗 筑波大学 DOI:10.15068/00160403

2020.07.21

概要

Since the introduction of molecular biology to disease research, various molecules have been identified as the cause or trigger of disease and have been studied as targets for therapeutic development. However, such molecular targeted drugs based on identification of one or few mutated genes would produce very little to benefit the patients while causing unexpected life- threatening side-effects. While the isolated specific molecules are parts of the highly heterogeneous biology, they should not be always considered as ‘target’ for therapy as they may sometime have little or no value on their own for translational purposes for patients. As cellular function is controlled in the context of complex gene regulatory networks, not individual genes, a disease is rarely a consequence of an abnormality in a single gene but reflects the perturbations of the complex intracellular network. Therefore, a disruptive approach for understanding multifactorial diseases by performing inference on the set of intracellular molecular interactions is required in order to bridge the gap between genotype and phenotype, leading to significantly improve the success rate of drug discovery.

To understand the mechanisms of disease systematically, patient stratification by the data-driven matching of patients to the appropriate investigational therapy is critical and important way to enable effective drug discovery and development in the age of precision medicine. Here, I investigate patient segment-specific molecular mechanism in two diseases focused on transcriptome profiling, which has been one of the most utilized approaches to expose expression patterns to define cellular states at the molecular level. First, through the validation of differential gene expression data following treatment with Lysine-specific demethylase (LSD) 1 inhibitor in acute myeloid leukemia cells, prediction of transcriptional regulators involved in mediating the transcriptional response revealed certain acute myeloid leukemia subtypes-specific core regulatory network that are required for their development and maintenance, which could be targeted in personalized therapies. Second, systematic in silico screening to analyze the correlation of Crohn’s disease patient-derived gene signature and gene expression profile of existing drugs revealed the abnormality of MAPK pathway in even anti-TNFα responders that would be the cause of recurrence of Crohn’s disease. Based on these two studies, transcriptome analysis of patient segment-specific gene expressions provides more insights to evaluate biological dysfunctions and helps to explore detailed and underlying molecular changes of human diseases that are emergent properties of biological networks, not the result of changes of single genes. In addition, systematic in silico computational approach offers a versatile platform to explore systematically the molecular complexity of a particular disease, leading to the identification of disease modules and pathways effectively and to better understanding unmet medical needs for precision medicine.

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