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Most chemotherapeutics elevate intracellular levels of reactive oxygen species (ROS), and many can alter redox-homeostasis of cancer cells. It is widely accepted that the anticancer effect of these chemotherapeutics is due to the induction of oxidative stress and ROS-mediated cell injury in cancer. However, various new therapeutic approaches targeting intracellular ROS levels have yielded mixed results. Since it is impossible to quantitatively detect dynamic ROS levels in tumors during and after chemotherapy in clinical settings, it is of increasing interest to apply mathematical modeling techniques to predict ROS levels for understanding complex tumor biology during chemotherapy. This review outlines the current understanding of the role of ROS in cancer cells during carcinogenesis and during chemotherapy, provides a critical analysis of the methods used for quantitative ROS detection and discusses the application of mathematical modeling in predicting treatment responses. Finally, we provide insights on and perspectives for future development of effective therapeutic ROS-inducing anticancer agents or antioxidants for cancer treatment.

Hair follicles (HFs) upon development enter a lifelong cycle of growth, regression, and resting. These phases have been extensively studied at the cellular and molecular levels for individual HFs. However, HFs group into domains with coordinated cycling strongly influenced by their environment. These macroscopic hair domains have been difficult to study and can be influenced by physiological or pathological conditions, such as pregnancy or skin wounds. To robustly address this issue, we generated a mouse model for quantitative monitoring of β-catenin activity reflecting HF cycle dynamics macroscopically by using live bioluminescence imaging. These mice allowed live tracking of HF cycles and development, and highlighted hair regenerative patterns known to occur through macro-environmental cues, including initiation events, propagating anagen and border stability, and allowed refinement of a mechanistic mathematical model that integrates epidermal cell population dynamics into an excitable reaction-diffusion model. HF cycling could be studied in situations of pregnancy, wound healing, hair plucking, as well as in response to cyclosporine or Wnt3a stimulation. In conclusion, we developed a model for analysis of HF cycling at the macroscopic level that will allow refined analysis of hair cycle kinetics as well as its propagation dynamics.

Epidemiological studies suggest that ultraviolet B exposure (UVR) during childhood is the most important environmental risk factor for melanoma. In accordance, neonatal, but not adult, UVR exacerbates melanoma incidence in mouse models. The inability of neonates, as opposed to adults, to mount a proper neutrophil inflammatory response in the skin upon UVR exposure has been one of the driving hypotheses explaining this observation for the past decade. However, this aspect remains controversial. Here, we evaluated the UVR-induced inflammatory response in neonatal versus adult mice. In neonates, a significant neutrophil infiltration could be identified and quantified using three different antibodies by flow cytometry or immunohistochemistry. On day 1 after UVR, neutrophils were increased by 84-fold and on day 4 macrophages increased by 37-fold compared with nonexposed age-matched skin. When compared with adults, neonatal skin harbored a higher proportion of neutrophils in the myeloid compartment without significant differences in absolute counts. This response was reproduced with different kinetics in C57Bl/6 and FVB mice with a more rapid attenuation of neutrophil counts in the latter. Overall, our results suggest that the greatly increased sensitivity to melanomagenesis in neonates does not result from their incompetence in terms of myeloid inflammatory response to UVR.