[China Pharmaceutical Network Technology News] " Cancer Immunotherapy" is destined to be a hot topic during this period, and most people have objections to this therapy. How do cancer patient differences affect the efficacy and toxicity of cancer immunotherapy, and how can it be better modeled in animal studies based on different host environments? 
Early mouse experiments predicted the success of checkpoint suppression immunotherapy in cancer patients, but these animal studies did not accurately predict the many limitations and toxicity of clinical treatment. One of the possible reasons for this difference is that young, healthy mice are almost universally used in animal testing, compared to different ages, weights, diets, and health conditions. These variables affect the patient's immunity and metabolism, as well as the outcome of immunotherapy. The authors believe that the design of preclinical trials should take these factors into account.
On April 19th, Cell's Trends in Immunology published a review article entitled "Adapting Cancer Immunotherapy Models for the Real World." The article summarizes four major trends: 1) The mouse model of cancer immunotherapy fails to summarize the clinically observed variable response and potential toxicity; 2) the variable results of immunotherapy are affected by age and obesity. Effects; 3) Microbial populations have a wide-ranging impact on tumor immunity, and different symbionts may have synergistic or resistive effects on immunotherapy; 4) Extended immunotherapy preclinical studies should include young and old mice, lean mice And fat mice and mice carrying different microbiotas are necessary to explore more accurate disease models.
Host factors determine the success of cancer immunotherapy
The success of checkpoint suppression immunotherapy has changed the current state of treatment for many cancers, but only a subset of patients respond to this therapy, and the therapy also has toxic effects. The challenge now is to expand the range of patients benefiting from immunotherapy while minimizing treatment-related adverse events. So, what kind of biological mechanism will enable patients to respond to this therapy? Can these mechanisms be useful biomarkers for predicting patient outcomes? Answering these questions requires further understanding of the multifaceted factors that the host determines for different treatment outcomes.
One of the obstacles to the development of predictive biomarkers is that animal model studies do not summarize the specific characteristics of cancer patients. For example, cancer is usually associated with aging. The American Cancer Society reports that less than 10% of young people under the age of 45 are new in cancer cases in 2013, and more than 50% of patients are over 65 years old. Another influencing factor is obesity. According to the US Centers for Disease Control and Prevention, more than 78 million adults in the United States are obese, and this trend is rising. Coupled with the rising incidence of cancer in obese people, there will be a large number of obese cancer patients in the future.
In addition, the microbiota that is symbiotic with us may also cause malignant tumors. However, despite so many influencing factors, most preclinical immunotherapy studies have been conducted in young, lean inbred mice. These animals either did not experience the same level of toxicity or variability observed in the patient, or these problems were ignored and were not reported. To overcome these limitations, some recent immunotherapeutic studies have used animal models that reflect the important effects of patient variability.
They reported different outcomes associated with increased age, obesity, and microbiota composition. The effects of these factors are also not mutually exclusive, and all factors may affect a range of immune responses in different patient populations. The complexity of these important elements necessitates the diversification of preclinical research animal models. In this review, the authors review these recent advances and provide a roadmap for designing more useful preclinical immunotherapy studies.
The article mainly summarizes 8 parts, including: 1) ageing for testing cancer immunotherapy, 2) establishing old mouse model, 3) obesity affecting immunity, 4) obesity and immunotherapy, 5) modeling of obese mice 6) Microbial population and cancer immune response, 7) Cancer immunotherapy is affected by the microbiota, and 8) Explore the microbial population of the mouse model.
The Challenges of Immunotherapy in Obese Mice (Source: Trends in Immunology)
The Effects of Commensal Microbiota on CancerI mmunotherapy (Source: Trends in Immunology)
Summary and Outlook <br> <br> immunotherapy save the lives of cancer patients strength is undeniable, of which the most striking is undoubtedly open the door to regulation of immune checkpoint inhibitor PD-1 CTLA-4 antibody and. However, patients respond differently to this type of therapy, with some patients receiving only a small therapeutic effect and others even having serious adverse events. At present, some studies have begun to focus on the mechanisms behind these different responses. What determines the success of immunotherapy in different patient groups?
Recent mouse studies have shown that age, obesity, and the microbiota have profound effects on the natural immunity of cancer and the ability to respond to immunotherapy. Although this area of ​​research is in its infancy, these results are sufficient to support the research direction of how human cancer immunotherapy can better model mice. The authors believe that only systematic testing of different types of mice (young/aged, fat/skinny, carrying different microbiota) can truly unravel the complexity of human cancer immunotherapy.
Early mouse experiments predicted the success of checkpoint suppression immunotherapy in cancer patients, but these animal studies did not accurately predict the many limitations and toxicity of clinical treatment. One of the possible reasons for this difference is that young, healthy mice are almost universally used in animal testing, compared to different ages, weights, diets, and health conditions. These variables affect the patient's immunity and metabolism, as well as the outcome of immunotherapy. The authors believe that the design of preclinical trials should take these factors into account.
On April 19th, Cell's Trends in Immunology published a review article entitled "Adapting Cancer Immunotherapy Models for the Real World." The article summarizes four major trends: 1) The mouse model of cancer immunotherapy fails to summarize the clinically observed variable response and potential toxicity; 2) the variable results of immunotherapy are affected by age and obesity. Effects; 3) Microbial populations have a wide-ranging impact on tumor immunity, and different symbionts may have synergistic or resistive effects on immunotherapy; 4) Extended immunotherapy preclinical studies should include young and old mice, lean mice And fat mice and mice carrying different microbiotas are necessary to explore more accurate disease models.
Host factors determine the success of cancer immunotherapy
The success of checkpoint suppression immunotherapy has changed the current state of treatment for many cancers, but only a subset of patients respond to this therapy, and the therapy also has toxic effects. The challenge now is to expand the range of patients benefiting from immunotherapy while minimizing treatment-related adverse events. So, what kind of biological mechanism will enable patients to respond to this therapy? Can these mechanisms be useful biomarkers for predicting patient outcomes? Answering these questions requires further understanding of the multifaceted factors that the host determines for different treatment outcomes.
One of the obstacles to the development of predictive biomarkers is that animal model studies do not summarize the specific characteristics of cancer patients. For example, cancer is usually associated with aging. The American Cancer Society reports that less than 10% of young people under the age of 45 are new in cancer cases in 2013, and more than 50% of patients are over 65 years old. Another influencing factor is obesity. According to the US Centers for Disease Control and Prevention, more than 78 million adults in the United States are obese, and this trend is rising. Coupled with the rising incidence of cancer in obese people, there will be a large number of obese cancer patients in the future.
In addition, the microbiota that is symbiotic with us may also cause malignant tumors. However, despite so many influencing factors, most preclinical immunotherapy studies have been conducted in young, lean inbred mice. These animals either did not experience the same level of toxicity or variability observed in the patient, or these problems were ignored and were not reported. To overcome these limitations, some recent immunotherapeutic studies have used animal models that reflect the important effects of patient variability.
They reported different outcomes associated with increased age, obesity, and microbiota composition. The effects of these factors are also not mutually exclusive, and all factors may affect a range of immune responses in different patient populations. The complexity of these important elements necessitates the diversification of preclinical research animal models. In this review, the authors review these recent advances and provide a roadmap for designing more useful preclinical immunotherapy studies.
The article mainly summarizes 8 parts, including: 1) ageing for testing cancer immunotherapy, 2) establishing old mouse model, 3) obesity affecting immunity, 4) obesity and immunotherapy, 5) modeling of obese mice 6) Microbial population and cancer immune response, 7) Cancer immunotherapy is affected by the microbiota, and 8) Explore the microbial population of the mouse model.
The Challenges of Immunotherapy in Obese Mice (Source: Trends in Immunology)
The Effects of Commensal Microbiota on CancerI mmunotherapy (Source: Trends in Immunology)
Recent mouse studies have shown that age, obesity, and the microbiota have profound effects on the natural immunity of cancer and the ability to respond to immunotherapy. Although this area of ​​research is in its infancy, these results are sufficient to support the research direction of how human cancer immunotherapy can better model mice. The authors believe that only systematic testing of different types of mice (young/aged, fat/skinny, carrying different microbiota) can truly unravel the complexity of human cancer immunotherapy.
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