Facing metastasis is the most pressing challenge of cancer research. In this review, we discuss recent advances in understanding phenotypic plasticity of cancer cells, highlighting the kinetics of cancer stem cell and the role of the epithelial mesenchymal transition for metastasis. It appears that the tumor micro-environment plays a crucial role in triggering phenotypic transitions, as we illustrate discussing the challenges posed by macrophages and cancer associated fibroblasts. To disentangle the complexity of environmentally induced phenotypic transitions, there is a growing need for novel advanced algorithms as those proposed in our recent work combining single cell data analysis and numerical simulations of gene regulatory networks. We conclude discussing recent developments in artificial intelligence and its applications to personalized cancer treatment.

Explaining the dynamics of tumor aggressiveness : at the crossroads between biology, artificial intelligence and complex systems / C.A.M. La Porta, S. Zapperi. - In: SEMINARS IN CANCER BIOLOGY. - ISSN 1044-579X. - 53(2018 Dec), pp. 42-47. [10.1016/j.semcancer.2018.07.003]

Explaining the dynamics of tumor aggressiveness : at the crossroads between biology, artificial intelligence and complex systems

C.A.M. La Porta
;
S. Zapperi
2018

Abstract

Facing metastasis is the most pressing challenge of cancer research. In this review, we discuss recent advances in understanding phenotypic plasticity of cancer cells, highlighting the kinetics of cancer stem cell and the role of the epithelial mesenchymal transition for metastasis. It appears that the tumor micro-environment plays a crucial role in triggering phenotypic transitions, as we illustrate discussing the challenges posed by macrophages and cancer associated fibroblasts. To disentangle the complexity of environmentally induced phenotypic transitions, there is a growing need for novel advanced algorithms as those proposed in our recent work combining single cell data analysis and numerical simulations of gene regulatory networks. We conclude discussing recent developments in artificial intelligence and its applications to personalized cancer treatment.
Cancer stem cells; Metastasis; Phenotypic switching; Precision medicine
Settore MED/04 - Patologia Generale
Settore FIS/03 - Fisica della Materia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/582187
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