Systems medicine has revolutionized the understanding of complex, multifactorial diseases, such as cancer. Viewing cancer through a systems approach lens provides a more accurate perspective on the rules that dictate its pathogenesis and appropriate management. This strategy perceives the human body as an arrangement of networks-within-networks and makes a coordinated effort to understand the properties of this system as a whole instead of focusing on its individual components. To this end, the rapidly increasing amounts of high-throughput data and other relevant quantitative biomedical data that are becoming available and accessible are exploited. Information from multiple disciplines including developmental biology, stem cell research and tissue engineering are combined with preclinical cancer studies, aided by computational and mathematical tools, to understand disease phenotypes based on common mechanisms and in an integrative manner.
Disease progression is fueled by a complex and dynamic interplay between intratumoral heterogeneity and tumor microenvironment (TME), while these interactions are further shaped by environmental cues. Crosstalks are established among heterogeneous cancer cell subpopulations and cellular and non-cellular components of the TME, creating sophisticated pro-metastatic networks. Developmental and cell differentiation pathways, as well as tissue-restricted gene regulatory programs may also be reactivated off-context to increase metastatic competence. Hence, there is an urgent need to understand cancer progression as a complex, adaptive system and develop a suite of experimental and theoretical methods to unveil how these components are rewired towards metastatic fates. Such approaches could catalyze a paradigm shift in personalized cancer management.
This Research Topic aims to create a conceptual framework for the implementation of the rules governing systems medicine in unveiling the complexity of the networks that underlie cancer aggressiveness and therapy resistance. We welcome experimental and computational studies and combinations thereof, as well as Original Research and Review articles that are focused on the newest trends in:
- Mechanisms of cancer progression and remission
- Treatment responses and adverse events, with emphasis on immunotherapy
- Mechanisms and models of cell reprogramming
- Non-cancer related developmental phenotypes regulated by p73, p53 and p63
Research using non-traditional animal models and 3D model systems is highly welcome.
Systems medicine has revolutionized the understanding of complex, multifactorial diseases, such as cancer. Viewing cancer through a systems approach lens provides a more accurate perspective on the rules that dictate its pathogenesis and appropriate management. This strategy perceives the human body as an arrangement of networks-within-networks and makes a coordinated effort to understand the properties of this system as a whole instead of focusing on its individual components. To this end, the rapidly increasing amounts of high-throughput data and other relevant quantitative biomedical data that are becoming available and accessible are exploited. Information from multiple disciplines including developmental biology, stem cell research and tissue engineering are combined with preclinical cancer studies, aided by computational and mathematical tools, to understand disease phenotypes based on common mechanisms and in an integrative manner.
Disease progression is fueled by a complex and dynamic interplay between intratumoral heterogeneity and tumor microenvironment (TME), while these interactions are further shaped by environmental cues. Crosstalks are established among heterogeneous cancer cell subpopulations and cellular and non-cellular components of the TME, creating sophisticated pro-metastatic networks. Developmental and cell differentiation pathways, as well as tissue-restricted gene regulatory programs may also be reactivated off-context to increase metastatic competence. Hence, there is an urgent need to understand cancer progression as a complex, adaptive system and develop a suite of experimental and theoretical methods to unveil how these components are rewired towards metastatic fates. Such approaches could catalyze a paradigm shift in personalized cancer management.
This Research Topic aims to create a conceptual framework for the implementation of the rules governing systems medicine in unveiling the complexity of the networks that underlie cancer aggressiveness and therapy resistance. We welcome experimental and computational studies and combinations thereof, as well as Original Research and Review articles that are focused on the newest trends in:
- Mechanisms of cancer progression and remission
- Treatment responses and adverse events, with emphasis on immunotherapy
- Mechanisms and models of cell reprogramming
- Non-cancer related developmental phenotypes regulated by p73, p53 and p63
Research using non-traditional animal models and 3D model systems is highly welcome.