ß-Adrenoreceptors in Human Cancers.
Zoltan KrabothBernadette KalmanPublished in: International journal of molecular sciences (2023)
Cancer is the leading cause of death and represents a significant economic burden worldwide. The numbers are constantly growing as a result of increasing life expectancy, toxic environmental factors, and adoption of Western lifestyle. Among lifestyle factors, stress and the related signaling pathways have recently been implicated in the development of tumors. Here we present some epidemiological and preclinical data concerning stress-related activation of the ß-adrenoreceptors (ß-ARs), which contributes to the formation, sequential transformation, and migration of different tumor cell types. We focused our survey on research results for breast and lung cancer, melanoma, and gliomas published in the past five years. Based on the converging evidence, we present a conceptual framework of how cancer cells hijack a physiological mechanism involving ß-ARs toward a positive modulation of their own survival. In addition, we also highlight the potential contribution of ß-AR activation to tumorigenesis and metastasis formation. Finally, we outline the antitumor effects of targeting the ß-adrenergic signaling pathways, methods for which primarily include repurposed ß-blocker drugs. However, we also call attention to the emerging (though as yet largely explorative) method of chemogenetics, which has a great potential in suppressing tumor growth either by selectively modulating neuronal cell groups involved in stress responses affecting cancer cells or by directly manipulating specific (e.g., the ß-AR) receptors on a tumor and its microenvironment.
Keyphrases
- signaling pathway
- cell therapy
- single cell
- metabolic syndrome
- endothelial cells
- cardiovascular disease
- electronic health record
- weight loss
- physical activity
- papillary thyroid
- human health
- type diabetes
- south africa
- epithelial mesenchymal transition
- systematic review
- cross sectional
- risk assessment
- stress induced
- machine learning
- squamous cell
- mesenchymal stem cells
- climate change
- young adults
- childhood cancer
- cell proliferation
- deep learning
- pluripotent stem cells
- skin cancer
- oxidative stress