Primary prevention is the only means to reduce breast cancer incidence, yet many aspects of primary prevention need to be informed by a better understanding of the molecular mechanisms of risk leading to cancer onset, of the means and biomarkers to evaluate cancer risk in individuals (in order to tailor interventions to the risk level), and of socioeconomic impacts of primary prevention programs. In addition, the global burden of breast cancer, particularly in young women, requires that we integrate noninvasive screening methods that are scalable to better assess risk. The goal of this special issue is to gather information and solutions to help reduce breast cancer incidence from all concerned disciplines in the life science, social science, engineering and data science, medicine and humanities. Particular interest is in studies that are analyzing and identifying the impact of risk factors and protective factors on the molecular mechanisms of cellular homeostasis and on the mammary epigenome, and studies that are researching biomarkers of risk. Other topics of interest include basic and population research on synthetic and natural chemopreventive agents and on the protective effects of nutrition and exercise that constitute important pillars of an intervention program. Such investigations will be well integrated with projects in which engineering approaches are used to develop methods to measure risk and the impact of the environment on breast homeostasis. Here we define the environment as any external stimulus with an impact on the organism; therefore, this notion encompasses at minimum diet, pollution, stress and exercise. The interaction between environment and cells is likely to generate tremendous amounts of data (or big data), notably via ‘omics’ studies, which makes data science an important aspect for the success of primary prevention, especially for tailoring interventions and biomarkers to specific subpopulations and possibly individuals in the future. This special issue of Frontiers in Medicine will welcome not only data science perspectives, but also economic and ethical reflections on the process of working with individuals who present risk for a disease, but are not actually considered ill, and on the impact of data science of cancer risk on society and populations. Finally, considering that breast cancer is a global burden, articles representing diversity around the world are sought after, as well as studies that research the influence of diversity in finding solutions to reduce breast cancer incidence.
Primary prevention is the only means to reduce breast cancer incidence, yet many aspects of primary prevention need to be informed by a better understanding of the molecular mechanisms of risk leading to cancer onset, of the means and biomarkers to evaluate cancer risk in individuals (in order to tailor interventions to the risk level), and of socioeconomic impacts of primary prevention programs. In addition, the global burden of breast cancer, particularly in young women, requires that we integrate noninvasive screening methods that are scalable to better assess risk. The goal of this special issue is to gather information and solutions to help reduce breast cancer incidence from all concerned disciplines in the life science, social science, engineering and data science, medicine and humanities. Particular interest is in studies that are analyzing and identifying the impact of risk factors and protective factors on the molecular mechanisms of cellular homeostasis and on the mammary epigenome, and studies that are researching biomarkers of risk. Other topics of interest include basic and population research on synthetic and natural chemopreventive agents and on the protective effects of nutrition and exercise that constitute important pillars of an intervention program. Such investigations will be well integrated with projects in which engineering approaches are used to develop methods to measure risk and the impact of the environment on breast homeostasis. Here we define the environment as any external stimulus with an impact on the organism; therefore, this notion encompasses at minimum diet, pollution, stress and exercise. The interaction between environment and cells is likely to generate tremendous amounts of data (or big data), notably via ‘omics’ studies, which makes data science an important aspect for the success of primary prevention, especially for tailoring interventions and biomarkers to specific subpopulations and possibly individuals in the future. This special issue of Frontiers in Medicine will welcome not only data science perspectives, but also economic and ethical reflections on the process of working with individuals who present risk for a disease, but are not actually considered ill, and on the impact of data science of cancer risk on society and populations. Finally, considering that breast cancer is a global burden, articles representing diversity around the world are sought after, as well as studies that research the influence of diversity in finding solutions to reduce breast cancer incidence.