Browsing by Subject "systems biology"

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  • Zusinaite, Eva; Ianevski, Aleksandr; Niukkanen, Diana; Poranen, Minna M.; Bjoras, Magnar; Afset, Jan Egil; Tenson, Tanel; Velagapudi, Vidya; Merits, Andres; Kainov, Denis E. (2018)
    There are dozens of approved, investigational and experimental antiviral agents. Many of these agents cause serious side effects, which can only be revealed after drug administration. Identification of the side effects prior to drug administration is challenging. Here we describe an ex vivo approach for studying immuno- and neuro-modulatory properties of antiviral agents, which may be associated with potential side effects of these therapeutics. The current approach combines drug toxicity/efficacy tests and transcriptomics, which is followed by mRNA, cytokine and metabolite profiling. We demonstrated the utility of this approach with several examples of antiviral agents. We also showed that the approach can utilize different immune stimuli and cell types. It can also include other omics techniques, such as genomics and epigenomics, to allow identification of individual markers associated with adverse reactions to antivirals with immuno- and neuro-modulatory properties.
  • Marques, Francine Z.; Prestes, Priscilla R.; Byars, Sean G.; Ritchie, Scott C.; Wurtz, Peter; Patel, Sheila K.; Booth, Scott A.; Rana, Indrajeetsinh; Minoda, Yosuke; Berzins, Stuart P.; Curl, Claire L.; Bell, James R.; Wai, Bryan; Srivastava, Piyush M.; Kangas, Antti J.; Soininen, Pasi; Ruohonen, Saku; Kahonen, Mika; Lehtimaki, Terho; Raitoharju, Emma; Havulinna, Aki; Perola, Markus; Raitakari, Olli; Salomaa, Veikko; Ala-Korpela, Mika; Kettunen, Johannes; McGlynn, Maree; Kelly, Jason; Wlodek, Mary E.; Lewandowski, Paul A.; Delbridge, Lea M.; Burrell, Louise M.; Inouye, Michael; Harrap, Stephen B.; Charchar, Fadi J. (2017)
    Background-Cardiac hypertrophy increases the risk of developing heart failure and cardiovascular death. The neutrophil inflammatory protein, lipocalin-2 (LCN2/NGAL), is elevated in certain forms of cardiac hypertrophy and acute heart failure. However, a specific role for LCN2 in predisposition and etiology of hypertrophy and the relevant genetic determinants are unclear. Here, we defined the role of LCN2 in concentric cardiac hypertrophy in terms of pathophysiology, inflammatory expression networks, and genomic determinants. Methods and Results-We used 3 experimental models: a polygenic model of cardiac hypertrophy and heart failure, a model of intrauterine growth restriction and Lcn2-knockout mouse; cultured cardiomyocytes; and 2 human cohorts: 114 type 2 diabetes mellitus patients and 2064 healthy subjects of the YFS (Young Finns Study). In hypertrophic heart rats, cardiac and circulating Lcn2 was significantly overexpressed before, during, and after development of cardiac hypertrophy and heart failure. Lcn2 expression was increased in hypertrophic hearts in a model of intrauterine growth restriction, whereas Lcn2-knockout mice had smaller hearts. In cultured cardiomyocytes, Lcn2 activated molecular hypertrophic pathways and increased cell size, but reduced proliferation and cell numbers. Increased LCN2 was associated with cardiac hypertrophy and diastolic dysfunction in diabetes mellitus. In the YFS, LCN2 expression was associated with body mass index and cardiac mass and with levels of inflammatory markers. The single-nucleotide polymorphism, rs13297295, located near LCN2 defined a significant cis-eQTL for LCN2 expression. Conclusions-Direct effects of LCN2 on cardiomyocyte size and number and the consistent associations in experimental and human analyses reveal a central role for LCN2 in the ontogeny of cardiac hypertrophy and heart failure.
  • Kozłowska, Emilia (Helsingin yliopisto, 2019)
    Cancer is one of the world’s most lethal diseases. Although our understanding of this disease is expanding continuously, treatments for many types of cancers are still ineffective. The main reason for the high mortality of cancer patients is resistant to therapy. Since resistance to therapy is a complex and dynamical process, an interdisciplinary approach is necessary to understand it. The emergence of a new field called integrative mathematical oncology can tackle many urgent clinical problems in the treatment of cancer that are impossible to address using, for example, an in vitro or in vivo approach. The primary goal of this new field is to translate the biological complexity of a tumor into a precise language, such as mathematical formulas, and to perform model simulations. Therefore, integrative mathematical oncology allows for biological experiments to be performed inexpensively and rapidly. This thesis applies the integrative mathematical oncology approach to investigate resistance to treatment in solid tumors at the molecular and cellular levels. A mathematical model of the most commonly dysregulated pathway in cancer (the p53 signaling pathway) underwent a bifurcation analysis to investigate the possibility of restoring its proper dynamics in two types of cancer: osteosarcoma and breast cancer. Next, a stochastic model of resistance to platinum compounds was developed to improve our understanding of chemo-resistance to this group of drugs in advanced high-grade serous ovarian cancer (HGSOC). Finally, virtual clinical trial simulations (VCTS) were performed to identify a novel drug combination in ovarian cancer. The application of integrative mathematical oncology deepened our understanding of radio- and chemo-resistance in solid tumors. Firstly, the results from the bifurcation analysis of the p53 signaling pathway suggested silencing Mdm2 using siRNA to overcome radio-resistance in breast cancer and osteosarcoma. Next, the stochastic model of platinum resistance was utilized to answer two urgent clinical questions about ovarian cancer: i) how many platinum resistance mechanisms are active at diagnosis, and ii) how many drug-resistance mechanisms must be targeted to improve patient outcomes. Finally, the clinical trial simulations suggested a novel drug combination to overcome platinum resistance in advanced high-grade serous ovarian cancer.