• Laboraroty Animal Research
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• v.34 no.4
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• pp.160-165
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• 2018

Breast cancer remains the second leading cause of cancer death among woman, worldwide, despite advances in identifying novel targeted therapies and the development of treating strategies. Classification of clinical subtypes (ER+, PR+, HER2+, and TNBC (Triple-negative)) increases the complexity of breast cancers, which thus necessitates further investigation. Mouse models used in breast cancer research provide an essential approach to examine the mechanisms and genetic pathway in cancer progression and metastasis and to develop and evaluate clinical therapeutics. In this review, we summarize tumor transplantation models and genetically engineered mouse models (GEMMs) of breast cancer and their applications in the field of human breast cancer research and anti-cancer drug development. These models may help to improve the knowledge of underlying mechanisms and genetic pathways, as well as creating approaches for modeling clinical tumor subtypes, and developing innovative cancer therapy.

• Journal of Medicine and Life Science
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• v.15 no.2
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• pp.42-45
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• 2018

Colorectal cancer (CRC) is a third leading cause of cancer-related death in cancer patients. Sporadic and inflammation-related colon carcinogenesis are major mechanism of colorectal cancer. In vivo CRC models have been developed and implicated to understand their mechanisms upon a different type of CRC. Moreover, recently animal models have played important roles in chemopreventive and preclinical trials over the years. In this mini-review, the aim is to introduce various animal models of CRC and help the understanding to establish in vivo experimental plans according to the cancer type of CRC.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.5
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• pp.1759-1764
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• 2015

Purpose: To establish the concept of lung cancer hazard assessment theoretical models, evaluating the degree of lung cancer risk of Beijing for regional population lung cancer hazard assessment to provide a basis for technical support. Materials and Methods: ISO standards were used to classify stratified analysis for the entire population, life cycle, processes and socioeconomic management. Associated risk factors were evaluated as lung cancer hazard risk assessment first class indicators. Study design: Using the above materials, indicators were given the weight coefficients, building lung cancer risk assessment theoretical models. Regional data for Beijing were entered into the theoretical model to calculate the parameters of each indicator and evaluate the degree of local lung cancer risk. Results: Adopting the concept of lung cancer hazard assessment and theoretical models for regional populations, we established a lung cancer hazard risk assessment system, including 2 first indicators, 8 secondary indicators and 18 third indicators. All indicators were given weight coefficients and used as information sources. Score of hazard for lung cancer was 84.4 in Beijing. Conclusions: Comprehensively and systematically building a lung cancer risk assessment theoretical model for regional populations in conceivable, evaluating the degree of lung cancer risk of Beijing, providing technical support and scientific basis for interventions for prevention.

• Korean Journal of Exercise Nutrition
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• v.24 no.2
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• pp.22-29
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• 2020

[Purpose] Exercise is thought to have a significant effect on chemotherapy, and previous studies have reported that exercise can increase patient survival. Thus, in this review, we aimed to summarize various animal models to analyze the effects of exercise on breast cancer. [Methods] We summarized types of breast cancer animal models from various reports and analyzed the effects of exercise on anti-cancer factors in breast cancer animal models. [Results] This review aimed to systematically investigate if exercise could aid in suppressing breast cancer. Our study includes (a) increase in survival rate through exercise; (b) the intensity of exercise should be consistent and increased; (c) a mechanism for inhibiting carcinogenesis through exercise; (d) effects of exercise on anti-cancer function. [Conclusion] This review suggested the necessity of a variety of animal models for preclinical studies prior to breast cancer clinical trials. It also provides evidence to support the view that exercise plays an important role in the prevention or treatment of breast cancer by influencing anticancer factors.

• Journal of Gastric Cancer
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• v.14 no.2
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• pp.67-86
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• 2014

Gastric cancer is one of the most common cancers in the world. Animal models have been used to elucidate the details of the molecular mechanisms of various cancers. However, most inbred strains of mice have resistance to gastric carcinogenesis. Helicobacter infection and carcinogen treatment have been used to establish mouse models that exhibit phenotypes similar to those of human gastric cancer. A large number of transgenic and knockout mouse models of gastric cancer have been developed using genetic engineering. A combination of carcinogens and gene manipulation has been applied to facilitate development of advanced gastric cancer; however, it is rare for mouse models of gastric cancer to show aggressive, metastatic phenotypes required for preclinical studies. Here, we review current mouse models of gastric carcinogenesis and provide our perspectives on future developments in this field.

• Journal of Radiation Protection and Research
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• v.42 no.2
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• pp.130-140
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• 2017

Background: With the need for a domestic level 3 probabilistic safety assessment (PSA), it is essential to develop a Korea-specific code. Health effect assessments study radiation-induced impacts; in particular, long-term health effects are evaluated in terms of cancer risk. The objective of this study was to analyze the latest cancer risk models developed by foreign organizations and to compare the methodology of how they were developed. This paper also provides suggestions regarding the development of Korean cancer risk models. Materials and Methods: A review of cancer risk models was carried out targeting the latest models: the NUREG model (1993), the BEIR VII model (2006), the UNSCEAR model (2006), the ICRP 103 model (2007), and the U.S. EPA model (2011). The methodology of how each model was developed is explained, and the cancer sites, dose and dose rate effectiveness factor (DDREF) and mathematical models are also described in the sections presenting differences among the models. Results and Discussion: The NUREG model was developed by assuming that the risk was proportional to the risk coefficient and dose, while the BEIR VII, UNSCEAR, ICRP, and U.S. EPA models were derived from epidemiological data, principally from Japanese atomic bomb survivors. The risk coefficient does not consider individual characteristics, as the values were calculated in terms of population-averaged cancer risk per unit dose. However, the models derived by epidemiological data are a function of sex, exposure age, and attained age of the exposed individual. Moreover, the methodologies can be used to apply the latest epidemiological data. Therefore, methodologies using epidemiological data should be considered first for developing a Korean cancer risk model, and the cancer sites and DDREF should also be determined based on Korea-specific studies.

• Journal of Embryo Transfer
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• v.31 no.1
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• pp.97-107
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• 2016

Although many diseases could be treated by the development of modern medicine, there are some incurable diseases including brain cancer, Alzheimer disease, etc. To study human brain cancer, various animal models were reported. Among these animal models, mouse models are valuable tools for understanding brain cancer characteristics. In spite of many mouse brain cancer models, it has been difficult to find a new target molecule for the treatment of brain cancer. One of the reasons is absence of large animal model which makes conducting preclinical trials. In this article, we review a recent study of molecular characteristics of human brain cancer, their genetic mutation and comparative analysis of the mouse brain cancer model. Finally, we suggest the need for development of large animal models using somatic cell nuclear transfer in translational research.

• The Korean Journal of Urological Oncology
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• 제15권3호
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• pp.103-110
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• 2017

Cancer is the tissue complex consisted with heterogeneous cellular compositions, and microenvironmental cues. During the various stages of cancer initiation, development, and metastasis, cell-cell interactions as well as cell-extracellular matrix play major roles. Conventional cancer models both 2-dimensional and 3-dimensional (3D) present numerous limitations, which restrict their use as biomimetic models for drug screening and fundamental cancer biology studies. Recently, bioprinting biofabrication platform enables the creation of high-resolution 3D structures. Moreover this platform has been extensively used to model multiple organs and diseases, and this versatile technique has further found its creation of accurate models that figure out the complexity of the cancer microenvironment. In this review we will focus on cancer biology and limitations with current cancer models and we discuss vascular structures bioprinting that are critical to the construction of complex 3D cancer organoids. We finally conclude with current literature on bioprinting cancer models and propose future perspectives.

• Journal of Preventive Medicine and Public Health
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• v.46 no.2
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• pp.74-81
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• 2013

Objectives: The objective of this study was to evaluate the performance of risk-adjusted mortality models for colorectal cancer surgery. Methods: We investigated patients (n=652) who had undergone colorectal cancer surgery (colectomy, colectomy of the rectum and sigmoid colon, total colectomy, total proctectomy) at five teaching hospitals during 2008. Mortality was defined as 30-day or in-hospital surgical mortality. Risk-adjusted mortality models were constructed using claims data (basic model) with the addition of TNM staging (TNM model), physiological data (physiological model), surgical data (surgical model), or all clinical data (composite model). Multiple logistic regression analysis was performed to develop the risk-adjustment models. To compare the performance of the models, both c-statistics using Hanley-McNeil pair-wise testing and the ratio of the observed to the expected mortality within quartiles of mortality risk were evaluated to assess the abilities of discrimination and calibration. Results: The physiological model (c=0.92), surgical model (c=0.92), and composite model (c=0.93) displayed a similar improvement in discrimination, whereas the TNM model (c=0.87) displayed little improvement over the basic model (c=0.86). The discriminatory power of the models did not differ by the Hanley-McNeil test (p>0.05). Within each quartile of mortality, the composite and surgical models displayed an expected mortality ratio close to 1. Conclusions: The addition of clinical data to claims data efficiently enhances the performance of the risk-adjusted postoperative mortality models in colorectal cancer surgery. We recommended that the performance of models should be evaluated through both discrimination and calibration.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6751-6755
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• 2013

Background: Research on cancers with a high rate of mortality such as those occurring in the stomach requires using models which can provide a closer examination of disease processes and provide researchers with more accurate data. Various models have been designed based on this issue and the present study aimed at evaluating such models. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at Iran Cancer Institute from 1995 to 1999 were analyzed. Cox-Snell Residuals and Akaike Information Criterion were used to compare parametric and semi-parametric Cox models in modeling transition rates among different states of a multi-state model. R 2.15.1 software was used for all data analyses. Results: Analysis of Cox-Snell Residuals and Akaike Information Criterion for all probable transitions among different states revealed that parametric models represented a better fitness. Log-logistic, Gompertz and Log-normal models were good choices for modeling transition rate for relapse hazard (state $1{\rightarrow}state$ 2), death hazard without a relapse (state $1{\rightarrow}state$ 3) and death hazard with a relapse (state $2{\rightarrow}state$ 3), respectively. Conclusions: Although the semi-parametric Cox model is often used by most cancer researchers in modeling transition rates of multistate models, parametric models in similar situations- as they do not need proportional hazards assumption and consider a specific statistical distribution for time to occurrence of next state in case this assumption is not made - are more credible alternatives.